Rachel Rudinger
Associate Professor
Studies natural language understanding, commonsense reasoning and social bias in language models.
Rachel Rudinger's lab at UMD works on large language models and reasoning & agents. 37 papers since 2023, 18 at top venues, mostly ACL and EMNLP. 3 alumni.
At a glance
- papers, 2023–2026
- 10/ year
- at T1 venues
- 49%
- PhD students
- 0
- MS students
- 0
- alumni listed
- 3
Papers by yearfrom the lab homepage, 2023–2026
- 5 papers2026 · T1 3 · collecting
- 16 papers2025 · T1 9
- 11 papers2024 · T1 5
- 5 papers2023 · T1 1
T1 venuesOtherVenues: ACL, EMNLP, Findings of ACL, EACL, ICLR
Research focuspaper titles that use each topic's words
- Large language models22 papers
- Reasoning & agents8 papers
- commonsense4 papers
- commonsense reasoning3 papers
- bias0 papers
Paper list
From the lab homepage.
20265 papers
- ACL (T1)Arguments that Alter Minds: LLM Rationales Sway Human (and LLM) Notions of Plausibility (opens in a new tab)
- ACL (T1)BenchMarker: An Education-Inspired Toolkit for Highlighting Flaws in Multiple-Choice Benchmarks (opens in a new tab)
- Findings of ACLReheat Nachos for Dinner? Evaluating AI Support for Cross-Cultural Communication of Neologisms (opens in a new tab)
- Findings of ACLTake Out Your Calculators: Estimating the Real Difficulty of Question Items with LLM Student Simulations (opens in a new tab)
- ACL (T1)Test-Time Reasoners Are Strategic Multiple-Choice Test-Takers (opens in a new tab)
202516 papers
- EMNLP (T1)`Rich Dad, Poor Lad': How do Large Language Models Contextualize Socioeconomic Factors in College Admission ? (opens in a new tab)
- EMNLP (T1)A Good Plan is Hard to Find: Aligning Models with Preferences is Misaligned with What Helps Users (opens in a new tab)
- Proceedings of the International Conference on Computational SemanticsFRIDA to the Rescue! Analyzing Synthetic Data Effectiveness in Object-Based Common Sense Reasoning for Disaster Response (opens in a new tab)
- Proceedings of the Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language TechnologiesLanguage Models Predict Empathy Gaps Between Social In-groups and Out-groups (opens in a new tab)
- NLP4PIMultilingual Large Language Models Leak Human Stereotypes across Language Boundaries (opens in a new tab)
- ACL (T1)Multiple LLM Agents Debate for Equitable Cultural Alignment (opens in a new tab)
- ICLR (T1)Natural Language Inference Improves Compositionality in Vision-Language Models (opens in a new tab)
- Proceedings of the Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language TechnologiesNLI under the Microscope: What Atomic Hypothesis Decomposition Reveals (opens in a new tab)
- ACL (T1)No Questions are Stupid, but some are Poorly Posed: Understanding Poorly-Posed Information-Seeking Questions (opens in a new tab)
- ACL (T1)On the Mutual Influence of Gender and Occupation in LLM Representations (opens in a new tab)
- Proceedings of the Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language TechnologiesReverse Question Answering: Can an LLM Write a Question so Hard (or Bad) that it Can't Answer? (opens in a new tab)
- Proceedings of the International Joint Conference on Natural Language Processing and the Conference of the Asia-Pacific Chapter of the Association for Computational LinguisticsSpeaking the Right Language: The Impact of Expertise (Mis)Alignment in User-AI Interactions (opens in a new tab)
202411 papers
- ACL (T1)Artifacts or Abduction: How Do LLMs Answer Multiple-Choice Questions Without the Question? (opens in a new tab)
- Proceedings of the Annual Meeting of the Cognitive Science SocietyAssessing Common Ground through Language-based Cultural Consensus in Humans and Large Language Models (opens in a new tab)
- ACL (T1)Do Large Language Models Discriminate in Hiring Decisions on the Basis of Race, Ethnicity, and Gender? (opens in a new tab)
- TACL (T1)How Often Are Errors in Natural Language Reasoning Due to Paraphrastic Variability? (opens in a new tab)
- KnowLLMIs Your Large Language Model Knowledgeable or a Choices-Only Cheater? (opens in a new tab)
- Findings of ACLIt's Not Easy Being Wrong: Large Language Models Struggle with Process of Elimination Reasoning (opens in a new tab)
- EMNLP (T1)On the Influence of Gender and Race in Romantic Relationship Prediction from Large Language Models (opens in a new tab)
- Findings of the Conference on Empirical Methods in Natural Language ProcessingPlausibly Problematic Questions in Multiple-Choice Benchmarks for Commonsense Reasoning
- Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), NAACL , Mexico City, Mexico, June 16-21Pregnant Questions: The Importance of Pragmatic Awareness in Maternal Health Question Answering (opens in a new tab)
- Proceedings of the Fifth International Workshop on Designing Meaning Representations @ LREC-COLINGPropBank-Powered Data Creation: Utilizing Sense-Role Labelling to Generate Disaster Scenario Data (opens in a new tab)
- EMNLP (T1)Susu Box or Piggy Bank: Assessing Cultural Commonsense Knowledge between Ghana and the US
20235 papers
- Findings of ACLFORK: A Bite-Sized Test Set for Probing Culinary Cultural Biases in Commonsense Reasoning Models (opens in a new tab)
- Proceedings of the Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), ACL , Toronto, Canada, July 9-14Nichelle and Nancy: The Influence of Demographic Attributes and Tokenization Length on First Name Biases (opens in a new tab)
- EACLSODAPOP: Open-Ended Discovery of Social Biases in Social Commonsense Reasoning Models (opens in a new tab)
- Proceedings of the International Conference on Computational SemanticsUse Defines Possibilities: Reasoning about Object Function to Interpret and Execute Robot Instructions (opens in a new tab)
- EMNLP (T1)What to Read in a Contract? Party-Specific Summarization of Legal Obligations, Entitlements, and Prohibitions (opens in a new tab)
Where alumni went3 listed
Apply to UMDFall 2027
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UMD Computer Science PhD
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