Vagrant Gautam
Vagrant Gautam has 5 papers in our library, in 2023–2026, most of them on Language models & pretraining, English, Coreference resolution; often with Anne Lauscher, Dietrich Klakow, Iryna Gurevych.
OpenAlex · ORCID · h-index 3 · 47 works · 104 citations OpenAlex, 2026-10-14
📄 5 works in our library · 🔗 Cited 26 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #10473
Affiliations
Fields, topics and concepts
📚 Shelves 9The field of science this work belongs to (OpenAlex fields).Computer Science · 5 worksArtificial Intelligence · 5 worksArts and Humanities · 4 worksLanguage and Linguistics · 4 worksSocial Sciences · 3 worksSafety Research · 2 worksComputer Vision and Pattern Recognition · 1 workInformation Systems · 1 workSociology and Political Science · 1 work
🧭 Topics 6Research subjects and languages the work is about.English · 2 worksCoreference resolution · 1 workLanguage models & pretraining · 2 worksBias, fairness & safety · 1 workInterpretability · 1 workReasoning · 1 work
Works by year
2020s
Papers
- WinoPron: Revisiting English Winogender Schemas for Consistency, Coverage, and Grammatical Case (2024 · 9 citations)
Winogender Schemas are a widely used benchmark for gender bias in coreference resolution. The authors audit it and find problems that make its measurements unreliable. Pronoun forms in different grammatical cases are counted as if they were interchangeable, and their counts are very uneven. Some paired templates… - A Lightweight Method to Generate Unanswerable Questions in English (2023 · 6 citations)
Extractive QA systems tend to produce a plausible-looking span even when the passage does not contain the answer. - Aligned Probing: Relating Toxic Behavior and Model Internals (2026 · 1 citation)
Work on LM toxicity usually judges models only by what they generate and treats toxicity as one uniform category. - Whose Facts Win? LLM Source Preferences under Knowledge Conflicts (2026 · 1 citation)
LLMs used in retrieval-augmented generation often receive passages that contradict each other. Earlier work on these inter-context knowledge conflicts did not ask whether the attributed source affects which version a model believes, and this paper addresses that gap. The authors built a controlled English testbed.… - GRUFF: LLM Pronoun Fidelity, Reasoning, and Biases in German (2026)
Pronoun fidelity asks whether a model, after learning which pronoun a person uses, keeps using that pronoun later even when sentences about other people come in between.
All works
- Robust Pronoun Fidelity with English LLMs: Are they Reasoning, Repeating, or Just Biased? ↗Transactions of the Association for Computational Linguistics · no summary yetVagrant Gautam et al.2024 · 17 citations
- WinoPron: Revisiting English Winogender Schemas for Consistency, Coverage, and Grammatical CaseWorkshop on Computational Models of Reference, Anaphora and Coreference (CRAC)Vagrant Gautam, Julius Steuer, Eileen Bingert, et al.2024 · 9 citations
- A Lightweight Method to Generate Unanswerable Questions in EnglishFindings of the Association for Computational LinguisticsVagrant Gautam, Miaoran Zhang, Dietrich Klakow2023 · 6 citations
- Aligned Probing: Relating Toxic Behavior and Model InternalsTransactions of the Association for Computational Linguistics (TACL)Andreas Waldis, Vagrant Gautam, Anne Lauscher, et al.2026 · 1 citation
- Whose Facts Win? LLM Source Preferences under Knowledge ConflictsAnnual Meeting of the Association for Computational Linguistics (ACL)Jakob Schuster, Vagrant Gautam, Katja Markert2026 · 1 citation
- GRUFF: LLM Pronoun Fidelity, Reasoning, and Biases in GermanarXiv:2605.30214Fabian Mewes, Anne Lauscher, Vagrant Gautam2026
Co-authors here
Venues
- Transactions of the Association for Computational Linguistics (TACL) ×2: Transactions of the Association for Computational Linguistics (TACL) 2026
- Annual Meeting of the Association for Computational Linguistics (ACL): ACL 2026
- Workshop on Computational Models of Reference, Anaphora and Coreference (CRAC): CRAC 2024
- Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2023
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