Isabelle Augenstein

Pepa Atanasova, Jakob Grue Simonsen, Christina Lioma, Isabelle Augenstein. Fact Checking with Insufficient Evidence. Transactions of the Association for Computational Linguistics (TACL), Vol 10 (2022). [Dataset], [Code]

Momchil Hardalov, Arnav Arora, Preslav Nakov, Isabelle Augenstein. Cross-Domain Label-Adaptive Stance Detection. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 2021), November 2021. [Code]

Pepa Atanasova, Jakob Grue Simonsen, Christina Lioma, Isabelle Augenstein. Generating Fact Checking Explanations. In Proceedings of 2020 Annual Conference of the Association for Computational Linguistics (ACL 2020), July 2020. [Video]

Farhad Nooralahzadeh, Giannis Bekoulis, Johannes Bjerva, Isabelle Augenstein. Zero-Shot Cross-Lingual Transfer with Meta Learning. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020), November 2020. [Code]

Alexander Hoyle, Lawrence Wolf-Sonkin, Hanna Wallach, Isabelle Augenstein, Ryan Cotterell. Unsupervised Discovery of Gendered Language through Latent-Variable Modeling. Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL 2019), August 2019. [Code], [Slides]

Gayane Ghazaryan*, Erik Arakelyan*, Pasquale Minervini, Isabelle Augenstein. SynDARin: Synthesising Datasets for Automated Reasoning in Low-Resource Languages. In Proceedings of the 31st International Conference on Computational Linguistics (Coling 2025), January 2025, to appear.

Shuzhou Yuan, Jingyi Sun, Ran Zhang, Michael Färber, Steffen Eger, Pepa Atanasova, Isabelle Augenstein. Graph-Guided Textual Explanation Generation Framework. CoRR, abs/2412.12318, December 2024.

Marta Marchiori Manerba, Karolina Stańczak, Riccardo Guidotti, Isabelle Augenstein. Social Bias Probing: Fairness Benchmarking for Language Models. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP 2024), November 2024. [Data]

Anej Svete, Nadav Borenstein, Mike Zhou, Isabelle Augenstein, Ryan Cotterell. Can Transformers Learn n-gram Language Models? In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP 2024), November 2024.

Sara Vera Marjanović*, Haeun Yu*, Pepa Atanasova, Maria Maistro, Christina Lioma, Isabelle Augenstein. DYNAMICQA: Tracing Internal Knowledge Conflicts in Language Models. In Findings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP 2024), November 2024. [Code], [Data]

Dustin Wright, Arnav Arora, Nadav Borenstein, Srishti Yadav, Serge Belongie, Isabelle Augenstein. LLM Tropes: Revealing Fine-Grained Values and Opinions in Large Language Models. In Findings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP 2024), November 2024. [Code], [Data]

Yuxia Wang, Revanth Gangi Reddy, Zain Muhammad Mujahid, Arnav Arora, Aleksandr Rubashevskii, Jiahui Geng, Osama Mohammed Afzal, Liangming Pan, Nadav Borenstein, Aditya Pillai, Isabelle Augenstein, Iryna Gurevych, Preslav Nakov. Factcheck-Bench: Fine-Grained Evaluation Benchmark for Automatic Fact-checkers. In Findings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP 2024), November 2024. [Code, Data]

Siddhesh Milind Pawar, Junyeong Park, Jiho Jin, Arnav Arora, Junho Myung, Srishti Yadav, Faiz Ghifari Haznitrama, Inhwa Song, Alice Oh, Isabelle Augenstein. Survey of Cultural Awareness in Language Models: Text and Beyond. CoRR, abs/2411.00860, August 2024. [HuggingFace]

Erik Arakelyan, Pasquale Minervini, Pat Verga, Patrick Lewis, Isabelle Augenstein. FLARE: Faithful Logic-Aided Reasoning and Exploration. CoRR, abs/2410.11900, October 2024.

Alphaeus Dmonte, Roland Oruche, Marcos Zampieri, Prasad Calyam, Isabelle Augenstein. Claim Verification in the Age of Large Language Models: A Survey. CoRR, abs/2408.14317, August 2024.

Isabelle Augenstein, Timothy Baldwin, Meeyoung Cha, Tanmoy Chakraborty, Giovanni Luca Ciampaglia, David Corney, Renee DiResta, Emilio Ferrara, Scott Hale, Alon Halevy, Eduard Hovy, Heng Ji, Filippo Menczer, Ruben Miguez, Preslav Nakov, Dietram Scheufele, Shivam Sharma, Giovanni Zagni. Factuality Challenges in the Era of Large Language Models. Nature Machine Intelligence, August 2024.

Karolina Stańczak, Kevin Du, Adina Williams, Isabelle Augenstein, Ryan Cotterell. Grammatical Gender's Influence on Distributional Semantics: A Causal Perspective. Transactions of the Association for Computational Linguistics (TACL), Vol 12 (2024). [Dataset, Code]

Jingyi Sun, Pepa Atanasova, Isabelle Augenstein. A Unified Framework for Input Feature Attribution Analysis. CoRR, abs/2406.15085, June 2024. [Code]

Amalie Brogaard Pauli, Isabelle Augenstein, Ira Assent. Measuring and Benchmarking Large Language Models' Capabilities to Generate Persuasive Language. CoRR, abs/2406.17753, June 2024. [Code], [Data]

Haeun Yu, Pepa Atanasova, Isabelle Augenstein. Revealing the Parametric Knowledge of Language Models: A Unified Framework for Attribution Methods. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024), August 2024. [Code]

Nadav Borenstein, Anej Svete, Robin Chan, Josef Valvoda, Franz Nowak, Isabelle Augenstein, Eleanor Chodroff, Ryan Cotterell. What Languages are Easy to Language-Model? A Perspective from Learning Probabilistic Regular Languages. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024), August 2024.

Sara Vera Marjanović, Isabelle Augenstein, Christina Lioma. Investigating the Impact of Model Instability on Explanations and Uncertainty. In Findings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024), August 2024. [Code]

Amelie Wührl, Dustin Wright, Roman Klinger, Isabelle Augenstein. Understanding Fine-grained Distortions in Reports of Scientific Findings. In Findings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024), August 2024. [Data]

Veerle C Eijsbroek, Katarina Kjell, H Andrew Schwartz, Jan R Boehnke, Eiko I Fried, Daniel N Klein, Peik Gustafsson, Isabelle Augenstein, Patrick M M Bossuyt, Oscar Kjell. The LEADING Guideline Reporting Standards for Expert Panel, Best-Estimate Diagnosis, and Longitudinal Expert All Data (LEAD) Studies. medRxiv, 2024.03.19.24304526, March 2024.

Nadav Borenstein, Arnav Arora, Lucie-Aimée Kaffee, Isabelle Augenstein. Investigating Human Values in Online Communities. CoRR, abs/2402.14177, February 2024. [Code]

Erik Arakelyan*, Zhaoqi Liu*, Isabelle Augenstein. Semantic Sensitivities and Inconsistent Predictions: Measuring the Fragility of NLI Models. In Proceedings of the 18th Annual Meeting of the European Chapter of the Association for Computational Linguistics (EACL 2024), March 2024. Outstanding paper award. [Video]

Yevgeniy Golovchenko, Karolina Stańczak, Rebecca Adler-Nissen, Patrice Wangen, Isabelle Augenstein. Invisible Women in Digital Diplomacy: A Multidimensional Framework for Online Gender Bias Against Women Ambassadors Worldwide. CoRR, abs/2311.17627, November 2023.

Karolina Stańczak, Sagnik Ray Choudhury, Tiago Pimentel, Ryan Cotterell, Isabelle Augenstein. Quantifying Gender Bias Towards Politicians in Cross-Lingual Language Models. PLOS One, November 2023.

Marcos Zampieri, Isabelle Augenstein, Siddharth Krishnan, Joshua Melton, Preslav Nakov. Preface: Special issue on NLP approaches to offensive content online. Natural Language Engineering, Volume 29, Issue 6, November 2023, pp. 1415.

Sagnik Ray Choudhury*, Pepa Atanasova*, Isabelle Augenstein. Explaining Interactions Between Text Spans. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023), December 2023. [Dataset], [Code]

Lucie-Aimée Kaffee*, Arnav Arora*, Isabelle Augenstein. Why Should This Article Be Deleted? Transparent Stance Detection in Multilingual Wikipedia Editor Discussions. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023), December 2023. [Code], [Data]

Indira Sen, Dennis Assenmacher, Mattia Samory, Isabelle Augenstein, Wil Aalst, Claudia Wagner. People Make Better Edits: Measuring the Efficacy of LLM-Generated Counterfactually Augmented Data for Harmful Language Detection. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023), December 2023.

Nadav Borenstein, Phillip Rust, Desmond Elliott, Isabelle Augenstein. PHD: Pixel-Based Language Modeling of Historical Documents. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023), December 2023.

Lucie-Aimée Kaffee, Arnav Arora, Zeerak Talat, Isabelle Augenstein. Thorny Roses: Investigating the Dual Use Dilemma in Natural Language Processing. In Findings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023), December 2023.

Erik Arakelyan, Pasquale Minervini, Daniel Daza, Michael Cochez, Isabelle Augenstein. Adapting Neural Link Predictors for Complex Query Answering. In Proceedings of 2023 Conference on Neural Information Processing Systems (NeurIPS 2023), December 2023.

Andreas Nugaard Holm, Dustin Wright, Isabelle Augenstein. Revisiting Softmax for Uncertainty Approximation in Text Classification. Information 2023, 14(7), 420, July 2023.

Erik Arakelyan, Arnav Arora, Isabelle Augenstein. Topic-Guided Sampling For Data-Efficient Multi-Domain Stance Detection. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (ACL 2023), July 2023.

Pepa Atanasova, Oana-Maria Camburu, Christina Lioma, Thomas Lukasiewicz, Jakob Grue Simonsen, Isabelle Augenstein. Faithfulness Tests for Natural Language Explanations. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (ACL 2023), July 2023.

Nadav Borenstein, Karolina Stańczak, Thea Rolskov, Natacha Klein Käfer, Natália da Silva Perez, Isabelle Augenstein. Measuring Intersectional Biases in Historical Documents. In Findings of the 61st Annual Meeting of the Association for Computational Linguistics (ACL 2023), July 2023.

Nadav Borenstein, Natália da Silva Perez, Isabelle Augenstein. Multilingual Event Extraction from Historical Newspaper Adverts. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (ACL 2023), July 2023.

Arnav Arora, Preslav Nakov, Momchil Hardalov, Sheikh Muhammad Sarwar, Vibha Nayak, Yoan Dinkov, Dimitrina Zlatkova, Kyle Dent, Ameya Bhatawdekar, Guillaume Bouchard, Isabelle Augenstein. Detecting Harmful Content on Online Platforms: What Platforms Need vs. Where Research Efforts Go. ACM Computing Surveys (CSUR), June 2023.

Arnav Arora, Lucie-Aimée Kaffee, Isabelle Augenstein. Probing Pre-Trained Language Models for Cross-Cultural Differences in Values. In Proceedings of the Workshop on Cross-Cultural Considerations in NLP (C3NLP at EACL 2023), May 2023.

Sandra Martinková, Karolina Stańczak, Isabelle Augenstein. Measuring Gender Bias in West Slavic Language Models. In Proceedings of the Workshop on Slavic Natural Language Processing (Slavic NLP at EACL 2023), May 2023.

Andreas Vlachos, Isabelle Augenstein. Findings of the Association for Computational Linguistics: (EACL 2023), April 2021.

Andreas Vlachos, Isabelle Augenstein. Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2023), April 2021.

Karolina Stańczak, Lucas Torroba Hennigen, Adina Williams, Ryan Cotterell, Isabelle Augenstein. A Latent-Variable Model for Intrinsic Probing. In Proceedings of the 37th Conference on Artificial Intelligence (AAAI 2023), February 2023.

Dustin Wright, Jiaxin Pei, David Jurgens, Isabelle Augenstein. Modeling Information Change in Science Communication with Semantically Matched Paraphrases. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022), December 2022. Also cross-presented at the 9th International Conference on Computational Social Science (IC2S2 2023), where it received an honourable mention [Dataset and Code]

Malte Ostendorff, Nils Rethmeier, Isabelle Augenstein, Bela Gipp, Georg Rehm. Neighborhood Contrastive Learning for Scientific Document Representations with Citation Embeddings. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022), December 2022.

Dustin Wright, Isabelle Augenstein. Multi-View Knowledge Distillation from Crowd Annotations for Out-of-Domain Generalization. CoRR, abs/2212.09409, December 2022.

Klim Zaporojets, Lucie-Aimée Kaffee, Johannes Deleu, Thomas Demeester, Chris Develder, Isabelle Augenstein. TempEL: Linking Dynamically Evolving and Newly Emerging Entities. In Proceedings of the 36th Conference on Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track, November 2022.

Shailza Jolly, Pepa Atanasova, Isabelle Augenstein. Generating Fluent Fact Checking Explanations with Unsupervised Post-Editing. MDPI Journal "Information", Special Issue on "Advances in Explainable Artificial Intelligence", October 2022.

Sagnik Ray Choudhury, Anna Rogers, Isabelle Augenstein. Machine Reading, Fast and Slow: When Do Models "Understand" Language? In Proceedings of the 29th International Conference on Computational Linguistics (COLING), October 2022.

Sagnik Ray Choudhury, Nikita Bhutani, Isabelle Augenstein. Can Edge Probing Tasks Reveal Linguistic Knowledge in QA Models?. In Proceedings of the 29th International Conference on Computational Linguistics (COLING), October 2022.

Sara Marjanovic, Karolina Stańczak, Isabelle Augenstein. Quantifying Gender Biases Towards Politicians on Reddit. PLoS ONE, October 2022.

Isabelle Augenstein. Habilitation Abstract: Towards Explainable Fact Checking. KI - Künstliche Intelligenz, Special Issue on Explainable AI, September 2022.

Anna Rogers, Matt Gardner, Isabelle Augenstein. QA Dataset Explosion: A Taxonomy of NLP Resources for Question Answering and Reading Comprehension. ACM Computing Surveys (CSUR), September 2022.

Nils Rethmeier, Isabelle Augenstein. A Primer on Contrastive Pretraining in Language Processing: Methods, Lessons Learned and Perspectives. ACM Computing Surveys (CSUR), September 2022.

Indira Sen, Mattia Samory, Claudia Wagner, Isabelle Augenstein. Counterfactually Augmented Data and Unintended Bias: The Case of Sexism and Hate Speech Detection. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics - Human Language Technologies (NAACL-HLT 2022), July 2022.

Karolina Stańczak, Edoardo Ponti, Lucas Torroba Hennigen, Ryan Cotterell, Isabelle Augenstein. Same Neurons, Different Languages: Probing Morphosyntax in Multilingual Pre-trained Models. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics - Human Language Technologies (NAACL-HLT 2022), July 2022.

Momchil Hardalov, Arnav Arora, Preslav Nakov, Isabelle Augenstein. A Survey on Stance Detection for Mis- and Disinformation Identification. In Findings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics - Human Language Technologies (NAACL-HLT 2022), July 2022.

Andrea Lekkas, Peter Schneider-Kamp, Isabelle Augenstein. Multi-Sense Language Modelling. In Proceedings of the Workshop on Dimensions of Meaning: Distributional and Curated Semantics (DistCurate at NAACL 2022), July 2022.

Pepa Atanasova, Jakob Grue Simonsen, Christina Lioma, Isabelle Augenstein. Fact Checking with Insufficient Evidence. Transactions of the Association for Computational Linguistics (TACL), Vol 10 (2022). [Dataset], [Code]

Dustin Wright, David Wadden, Kyle Lo, Bailey Kuehl, Isabelle Augenstein, Lucy Lu Wang. Generating Scientific Claims for Automatic Scientific Fact Checking. 60th Annual Meeting of the Association for Computational Linguistics (ACL 2022).

Sheikh Muhammad Sarwar, Dimitrina Zlatkova, Momchil Hardalov, Yoan Dinkov, Isabelle Augenstein, Preslav Nakov. A Neighbourhood Framework for Resource-Lean Content Flagging. Transactions of the Association for Computational Linguistics (TACL), Vol 10 (2022).

Andreas Holzinger, Matthias Dehmer, Frank Emmert-Streib, Rita Cucchiara, Isabelle Augenstein, Javier Del Ser, Wojciech Samek, Igor Jurisica, Natalia Díaz-Rodríguez. Information fusion as an integrative cross-cutting enabler to achieve robust, explainable, and trustworthy medical artificial intelligence. Information Fusion (IF), Volume 79, March 2022, Pages 263-278.

Pepa Atanasova, Jakob Grue Simonsen, Christina Lioma, Isabelle Augenstein. Diagnostics-Guided Explanation Generation. In Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2022), February 2022.

Momchil Hardalov, Arnav Arora, Preslav Nakov, Isabelle Augenstein. Few-Shot Cross-Lingual Stance Detection with Sentiment-Based Pre-Training. In Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2022), February 2022.

Andreas Nugaard Holm, Barbara Plank, Dustin Wright, Isabelle Augenstein. Longitudinal Citation Prediction using Temporal Graph Neural Networks. In Proceedings of AAAI 2022 Workshop on Scientific Document Understanding (SDU 2022), February 2022.

Nils Rethmeier, Isabelle Augenstein. Long-Tail Zero and Few-Shot Learning via Contrastive Pretraining on and for Small Data. In Proceedings of AAAI 2022 Workshop on Artificial Intelligence with Biased or Scarce Data (AIBSD 2022), February 2022.

Luna De Bruyne, Pepa Atanasova, Isabelle Augenstein. Joint Emotion Label Space Modelling for Affect Lexica. Computer Speech and Language (CS&L), Volume 71, January 2022, 101257.

Karolina Stańczak, Isabelle Augenstein. A Survey on Gender Bias in Natural Language Processing. CoRR, abs/2112.14168, December 2021.

Dustin Wright, Isabelle Augenstein. Semi-Supervised Exaggeration Detection of Health Science Press Releases. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 2021), November 2021.

Momchil Hardalov, Arnav Arora, Preslav Nakov, Isabelle Augenstein. Cross-Domain Label-Adaptive Stance Detection. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 2021), November 2021. [Code]

Indira Sen, Mattia Samory, Fabian Flöck, Claudia Wagner, Isabelle Augenstein. How Does Counterfactually Augmented Data Impact Models for Social Computing Constructs? In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 2021), November 2021.

Liesbeth Allein, Isabelle Augenstein, Marie-Francine Moens. Time-Aware Evidence Ranking for Fact-Checking. In Journal of Web Semantics, Special Issue on Content Credibility, Volume 71, November 2021.

Isabelle Augenstein, Paolo Papotti, Dustin Wright. Proceedings of the 2021 Truth and Trust Online Conference (TTO 2021). Hacks Hackers, October 2021.

Clara Meister, Stefan Lazov, Isabelle Augenstein, Ryan Cotterell. Is Sparse Attention more Interpretable? In Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021), August 2021.

Dustin Wright, Isabelle Augenstein. CiteWorth: Cite-Worthiness Detection for Improved Scientific Document Understanding. In Findings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021), August 2021. [Dataset and Code] [Pretrained Models]

Wojciech Ostrowski, Arnav Arora, Pepa Atanasova, Isabelle Augenstein. Multi-Hop Fact Checking of Political Claims. In Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI 2021), August 2021. [Dataset and Code]

Wei Zhao, Steffen Eger, Johannes Bjerva, Isabelle Augenstein. Inducing Language-Agnostic Multilingual Representations. In Proceedings of 10th Joint Conference on Lexical and Computational Semantics (*SEM 2021), August 2021. [Code]

Isabelle Augenstein. Determining the Credibility of Science Communication. In Proceedings of the Second Workshop on Scholarly Document Processing (SDP at NAACL 2021), June 2021.

Johannes Bjerva, Isabelle Augenstein. Does Typological Blinding Impede Cross-Lingual Sharing? In Proceedings of 16th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2021), April 2021.

Isabelle Augenstein, Ivan Habernal. Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Tutorial Abstracts (EACL 2021), April 2021.

Thamar Solorio, Mahsa Shafaei, Christos Smailis, Isabelle Augenstein, Margaret Mitchell, Ingrid Stapf, Ioannis Kakadiaris. White Paper - Creating a Repository of Objectionable Online Content: Addressing Undesirable Biases and Ethical Considerations. OpenReview Preprint, February 2021.

Isabelle Augenstein. Towards Explainable Fact Checking. Thesis presented to the University of Copenhagen Faculty of Science in partial fulfillment of the requirements for the degree of Doctor Scientiarum (Dr. Scient.), January 2021.

Lucas Chaves Lima, Dustin Wright, Isabelle Augenstein, Maria Maistro. University of Copenhagen Participation in TREC Health Misinformation Track 2020. In Proceedings of Text Retrieval Conference (TREC) 2020.

Pepa Atanasova, Jakob Grue Simonsen, Christina Lioma, Isabelle Augenstein. A Diagnostic Study of Explainability Techniques for Text Classification. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020), November 2020. [Code]

Pepa Atanasova*, Dustin Wright*, Isabelle Augenstein. Generating Label Cohesive and Well-Formed Adversarial Claims. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020), November 2020. [Code]

Dustin Wright, Isabelle Augenstein. Transformer Based Multi-Source Domain Adaptation. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020), November 2020. [Code]

Johannes Bjerva*, Nikita Bhutani*, Behzad Golshan, Wang-Chiew Tan, Isabelle Augenstein. SubjQA: A Dataset for Subjectivity and Review Comprehension. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020), November 2020. [Dataset]

Farhad Nooralahzadeh, Giannis Bekoulis, Johannes Bjerva, Isabelle Augenstein. Zero-Shot Cross-Lingual Transfer with Meta Learning. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020), November 2020. [Code]

Dustin Wright, Isabelle Augenstein. Claim Check-Worthiness Detection as Positive Unlabelled Learning. In Findings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020), November 2020. [Code]

Anna Rogers, Isabelle Augenstein. What Can We Do to Improve Peer Review in NLP?. In Findings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020), November 2020.

Johannes Bjerva, Elizabeth Salesky, Sabrina J. Mielke, Aditi Chaudhary, Giuseppe G. A. Celano, Edoardo M. Ponti, Ekaterina Vylomova, Ryan Cotterell, Isabelle Augenstein. SIGTYP 2020 Shared Task: Prediction of Typological Features. In Proceedings of TyP-NLP: The Second Workshop on Typology for Polyglot NLP (TyP-NLP at EMNLP 2020), November 2020.

Lukas Muttenthaler, Isabelle Augenstein, Johannes Bjerva. Unsupervised Evaluation for Question Answering with Transformers. In Proceedings of the 3rd Workshop on Analyzing and interpreting neural networks for NLP (BlackboxNLP at EMNLP 2020), November 2020.

Nils Rethmeier, Vageesh Kumar Saxena, Isabelle Augenstein. TX-Ray: Quantifying and Explaining Model-Knowledge Transfer in (Un-)Supervised NLP. In Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI), August 2020. [Code]

Pepa Atanasova, Jakob Grue Simonsen, Christina Lioma, Isabelle Augenstein. Generating Fact Checking Explanations. In Proceedings of 2020 Annual Conference of the Association for Computational Linguistics (ACL 2020), July 2020. [Video]

Pranav A, Isabelle Augenstein. 2kenize: Tying Subword Sequences for Chinese Script Conversion. In Proceedings of 2020 Annual Conference of the Association for Computational Linguistics (ACL 2020), July 2020. [Dataset], [Video]

Zeerak Waseem, Smarika Lulz, Joachim Bingel, Isabelle Augenstein. Disembodied Machine Learning: On the Illusion of Objectivity in NLP. OpenReview Preprint, June 2020.

Alok Debnath, Nikhil Pinnaparaju, Manish Shrivastava, Vasudeva Varma, Isabelle Augenstein. Semantic Textual Similarity of Sentences with Emojis. In Proceedings of the 8th International Workshop on Natural Language Processing for Social Media (SocialNLP at TheWebConf 2020), April 2020.

Johannes Bjerva*, Wouter Kouw*, Isabelle Augenstein. Back to the Future -- Sequential Alignment of Text Representations. Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI 2020), February 2020. [Code]

Isabelle Augenstein, Christina Lioma, Dongsheng Wang, Lucas Chaves Lima, Casper Hansen, Christian Hansen and Jakob Grue Simonsen. MultiFC: A Real-World Multi-Domain Dataset for Evidence-Based Fact Checking of Claims. 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP 2019). [Dataset and Leaderboard], [Poster]

Mareike Hartmann, Yevgeniy Golovchenko, Isabelle Augenstein. Mapping (Dis-)Information Flow about the MH17 Plane Crash. Proceedings of the 2019 Workshop on NLP4IF: censorship, disinformation, and propaganda (NLP4IF at EMNLP 2019), November 2019.

Ana Valeria Gonzalez, Isabelle Augenstein, Anders Søgaard. Retrieval-Based Goal-Oriented Dialogue Generation. 3rd Conversational AI Workshop at NeurIPS 2019, December 2019.

Joachim Bingel, Victor Petrén Bach Hansen, Ana Valeria Gonzalez, Paweł Budzianowski, Isabelle Augenstein, Anders Søgaard. Domain Transfer in Dialogue Systems without Turn-Level Supervision. 3rd Conversational AI Workshop at NeurIPS 2019, December 2019.

Mostafa Abdou, Cezar Sas, Rahul Aralikatte, Isabelle Augenstein, Anders Søgaard. X-WikiRE: A Large, Multilingual Resource for Relation Extraction as Machine Comprehension. Proceedings of the 2nd Workshop on Deep Learning for Low Resource Natural Language Processing (DeepLo at EMNLP 2019), November 2019.

Johannes Bjerva, Katharina Kann, Isabelle Augenstein. Transductive Auxiliary Task Self-Training for Neural Multi-Task Models. Proceedings of the 2nd Workshop on Deep Learning for Low Resource Natural Language Processing (DeepLo at EMNLP 2019), November 2019.

Isabelle Augenstein, Spandana Gella, Sebastian Ruder, Katharina Kann, Burcu Can, Alexis Conneau, Johannes Welbl, Xian Ren, Marek Rei. Proceedings of The Fourth Workshop on Representation Learning for NLP. (Repl4NLP at ACL 2019). [Slides]

Johannes Bjerva, Yova Kementchedjhieva, Ryan Cotterell, Isabelle Augenstein. Uncovering Probabilistic Implications in Typological Knowledge Bases. Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL 2019), August 2019.

Alexander Hoyle, Lawrence Wolf-Sonkin, Hanna Wallach, Isabelle Augenstein, Ryan Cotterell. Unsupervised Discovery of Gendered Language through Latent-Variable Modeling. Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL 2019), August 2019. [Code], [Slides]

Johannes Bjerva, Yova Kementchedjhieva, Ryan Cotterell, Isabelle Augenstein. A Probabilistic Generative Model of Linguistic Typology. Proceedings of the 17th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2019), June 2019. [Slides], [Video]

Alexander Hoyle, Lawrence Wolf-Sonkin, Ryan Cotterell, Hanna Wallach, Isabelle Augenstein. Combining Sentiment Lexica with a Multi-View Variational Autoencoder. Proceedings of the 17th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2019), June 2019. [Code], [Slides], [Video]

Mareike Hartmann, Tallulah Jansen, Isabelle Augenstein, Anders Søgaard. Issue Framing in Online Discussion Fora. Proceedings of the 17th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2019), June 2019. [Code]

Johannes Bjerva, Robert Östling, Maria Han Veiga, Jörg Tiedemann, Isabelle Augenstein. What do Language Representations Really Represent?. Computational Linguistics, Vol. 45, No. 2, June 2019.

Sebastian Ruder, Joachim Bingel, Isabelle Augenstein, Anders Søgaard. Latent multi-task architecture learning. Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI 2019), January 2019. [Code], [Slides]

Yova Kementchedjhieva, Johannes Bjerva, Isabelle Augenstein. Copenhagen at CoNLL--SIGMORPHON 2018: Multilingual Inflection in Context with Explicit Morphosyntactic Decoding. Proceedings of ConLL--SIGMORPHON 2018.

Ana Valeria Gonzalez-Garduño, Isabelle Augenstein, Anders Søgaard. A strong baseline for question relevancy ranking. Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP 2018). [Video]

Miryam de Lhoneux, Johannes Bjerva, Isabelle Augenstein, Anders Søgaard. Parameter sharing between dependency parsers for related languages. Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP 2018). [Poster]

Anders Søgaard, Miryam de Lhoneux, Isabelle Augenstein. Nightmare at test time: How punctuation prevents parsers from generalizing. Proceedings of the Analyzing and interpreting neural networks for NLP (BlackboxNLP at EMNLP 2018).

Dirk Weissenborn, Pasquale Minervini, Tim Dettmers, Isabelle Augenstein, Johannes Welbl, Tim Rocktäschel, Matko Bošnjak, Jeff Mitchell, Thomas Demeester, Pontus Stenetorp, Sebastian Riedel. Jack the Reader – A Machine Reading Framework. Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL 2018), System Demonstrations. [Demo]

Isabelle Augenstein, Kris Cao, He He, Felix Hill, Spandana Gella, Jamie Kiros, Hongyuan Mei, Dipendra Misra. Proceedings of The Third Workshop on Representation Learning for NLP. (Repl4NLP at ACL 2018).

Katharina Kann, Johannes Bjerva, Isabelle Augenstein, Barbara Plank and Anders Søgaard. Character-level Supervision for Low-resource POS Tagging. Proceedings of the 1st Workshop on Deep Learning Approaches for Low Resource Natural Language Processing (DeepLo at ACL 2018).

Isabelle Augenstein*, Sebastian Ruder*, Anders Søgaard. Multi-task Learning of Pairwise Sequence Classification Tasks Over Disparate Label Spaces. Proceedings of the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL HLT 2018). [Code], [Slides], [Video]

Johannes Bjerva, Isabelle Augenstein. From Phonology to Syntax: Unsupervised Linguistic Typology at Different Levels with Language Embeddings. Proceedings of the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL HLT 2018). [Code], [Slides]

Thomas Nyegaard-Signori, Casper Veistrup Helms, Johannes Bjerva, Isabelle Augenstein. KU-MTL at SemEval-2018 Task 1: Multi-task Identification of Affect in Tweets. Proceedings of the International Workshop on Semantic Evaluation (SemEval at NAACL HLT 2018).

Johannes Bjerva, Isabelle Augenstein. Tracking Typological Traits of Uralic Languages in Distributed Language Representations. Fourth International Workshop on Computational Linguistics for Uralic Languages (IWCLUL 2018), January 2018. [Slides]

Arkaitz Zubiaga, Elena Kochkina, Maria Liakata, Rob Procter, Michal Lukasik, Kalina Bontcheva, Trevor Cohn, Isabelle Augenstein. Discourse-Aware Rumour Stance Classification in Social Media Using Sequential Classifiers. Information Processing & Management, Volume 54, Issue 2, March 2018, Pages 273-290.

Benjamin Riedel, Isabelle Augenstein, Georgios Spithourakis, Sebastian Riedel. A simple but tough-to-beat baseline for the Fake News Challenge stance detection task. CoRR, abs/1707.03264, July 2017.

Ed Collins, Isabelle Augenstein, Sebastian Riedel. A Supervised Approach to Extractive Summarisation of Scientific Papers. Proceedings of SIGNLL Conference on Computational Natural Language Learning (CoNLL 2017), July 2017. [Code and Dataset], [Poster]

Isabelle Augenstein, Anders Søgaard. Multi-Task Learning of Keyphrase Boundary Classification. Proceedings of 55th Annual Meeting of the Association for Computational Linguistics (ACL 2017), August 2017. [Poster]

Isabelle Augenstein, Mrinal Das, Sebastian Riedel, Lakshmi Vikraman and Andrew McCallum. SemEval 2017 Task 10: ScienceIE - Extracting Keyphrases and Relations from Scientific Publications. Proceedings of the International Workshop on Semantic Evaluation (SemEval at ACL 2017), July 2017. [Code and Dataset], [Slides]

Elena Kochkina, Maria Liakata and Isabelle Augenstein. Sequential Approach to Rumour Stance Classification. Proceedings of the ACL Workshop on Women and Underrepresented Minorities in Natural Language Processing (WiNLP at ACL 2017), July 2017.

Elena Kochkina, Maria Liakata and Isabelle Augenstein. Turing at SemEval-2017 Task 8: Sequential Approach to Rumour Stance Classification with Branch-LSTM. Proceedings of the International Workshop on Semantic Evaluation (SemEval at ACL 2017), July 2017.

Ziqi Zhang, Anna Lisa Gentile, Isabelle Augenstein, Eva Blomqvist, Fabio Ciravegna (2017). An Unsupervised Data-driven Method to Discover Equivalent Relations in Large Linked Datasets. Semantic Web Journal, Volume 8, Number 2 / 2017.

Isabelle Augenstein, Tim Rocktäschel, Andreas Vlachos, Kalina Bontcheva. Stance Detection with Bidirectional Conditional Encoding. Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP 2016), November 2016. [Poster] [Promo Slide]

George Spithourakis, Isabelle Augenstein, Sebastian Riedel. Numerically Grounded Language Models for Semantic Error Correction. Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP 2016), November 2016. [Poster]

Ben Eisner, Tim Rocktäschel, Isabelle Augenstein, Matko Bosnjak, Sebastian Riedel. emoji2vec: Learning Emoji Representations from their Description. Proceedings of the International Workshop on Natural Language Processing for Social Media (SocialNLP at EMNLP 2016), November 2016. Best Paper, also featured in Denny Britz's AI Newsletter. [Poster].

Isabelle Augenstein. Web Information Extraction using Distant Supervision. PhD theses: Department of Computer Science, University of Sheffield, UK, July 2016.

Piroska Lendvai, Isabelle Augenstein, Dominic Rout, Kalina Bontcheva, Thierry Declerck. Algorithms for Detecting Disputed Information: Final Version. FP7-ICT Collaborative Project ICT-2013-611233 PHEME Deliverable D4.2.2 (WP4), June 2016.

Isabelle Augenstein, Andreas Vlachos and Kalina Bontcheva. USFD at SemEval-2016 Task 6: Any-Target Stance Detection on Twitter with Autoencoders. Proceedings of the International Workshop on Semantic Evaluation (SemEval at NAACL 2016), June 2016. [Poster]

Piroska Lendvai, Isabelle Augenstein, Kalina Bontcheva and Thierry Declerck. Monolingual Social Media Datasets for Detecting Contradiction and Entailment. Proceedings of International Conference on Language Resources and Evaluation (LREC 2016), May 2016.

Diana Maynard, Kalina Bontcheva, Isabelle Augenstein. Natural Language Processing for the Semantic Web. Morgan & Claypool Semantic Web Synthesis Series, December 2016.

Isabelle Augenstein, Diana Maynard, Fabio Ciravegna (2016). Distantly Supervised Web Relation Extraction for Knowledge Base Population. Semantic Web Journal, Volume 7, Number 4 / 2016.

Isabelle Augenstein, Andreas Vlachos, Diana Maynard (2015). Extracting Relations between Non-Standard Entities using Distant Supervision and Imitation Learning. Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP 2015), September 2015 [Poster]

Leon Derczynski, Isabelle Augenstein, Kalina Bontcheva (2015). USFD: Twitter NER with Drift Compensation and Linked Data. Proceedings of the ACL Workshop on Noisy User-generated Text (W-NUT at ACL 2015), July 2015.

Isabelle Augenstein, Diana Maynard, Fabio Ciravegna (2014). Relation Extraction from the Web using Distant Supervision. Proceedings of the 19th International Conference on Knowledge Engineering and Knowledge Management (EKAW 2014), November 2014. Nominated for best research paper award. [Slides]

Isabelle Augenstein (2014). Joint Information Extraction from the Web using Linked Data. Doctoral Consortium Proceedings of the 12th International Semantic Web Conference (ISWC 2014), October 2014.

Isabelle Augenstein (2014). Seed Selection for Distantly Supervised Web-Based Relation Extraction. Proceedings of the Workshop on Semantic Web and Information Extraction (SWAIE at COLING 2014), August 2014. [Slides]

Ziqi Zhang, Anna Lisa Gentile, Isabelle Augenstein (2014). Linked Data as Background Knowledge for Information Extraction on the Web. ACM SIGWEB Newsletter, July 2014.

Ziqi Zhang, Anna Lisa Gentile, Eva Blomqvist, Isabelle Augenstein, Fabio Ciravegna (2013). Statistical Knowledge Patterns: Identifying Synonymous Relations in Large Linked Datasets. Proceedings of the 12th International Semantic Web Conference (ISWC 2013), October 2013.

Eva Blomqvist, Ziqi Zhang, Anna Lisa Gentile, Isabelle Augenstein, Fabio Ciravegna (2013). Statistical Knowledge Patterns for Characterizing Linked Data. Proceedings of the 4th Workshop on Ontology and Semantic Web Patterns (WOP at ISWC 2013), October 2013.

Ziqi Zhang, Anna Lisa Gentile, Isabelle Augenstein, Eva Blomqvist, Fabio Ciravegna (2013). Mining Equivalent Relations from Linked Data. Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL 2013), August 2013.

Anna Lisa Gentile, Ziqi Zhang, Isabelle Augenstein, Fabio Ciravegna (2013). Unsupervised Wrapper Induction using Linked Data. In Proceedings of the 8th International Conference on Knowledge Capture (K-CAP 2013), June 2013.

Isabelle Augenstein, Anna Lisa Gentile, Barry Norton, Ziqi Zhang, Fabio Ciravegna (2013). Mapping Keywords to Linked Data Resources for Automatic Query Expansion. In Post-Proceedings of the 10th Extended Semantic Web Conference (ESWC 2013), May 2013. Best Workshop Paper of the 2nd International Workshop on Knowledge Discovery and Data Mining Meets Linked Open Data (KNOW@LOD at ESWC 2013) [Slides]

Isabelle Augenstein, Sebastian Padó, Sebastian Rudolph (2012). LODifier: Generating Linked Data from Unstructured Text. In Proceedings of the 9th Extended Semantic Web Conference (ESWC 2012), pp. 210-224, May 2012. [Slides]

Isabelle Augenstein (2011). LODifier - Generating RDF from Natural Language. Heidelberg University, Department of Computational Linguistics, July 2011.