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20242026
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cs.CL2026

The Surprising Effectiveness of Membership Inference with Simple N-Gram Coverage

Skyler Hallinan, Jaehun Jung, Melanie Sclar +7

Membership inference attacks serves as useful tool for fair use of language models, such as detecting potential copyright infringement and auditing data leakage. However, many curr…

cs.CL20251 cited

Finding Flawed Fictions: Evaluating Complex Reasoning in Language Models via Plot Hole Detection

Kabir Ahuja, Melanie Sclar, Yulia Tsvetkov

Stories are a fundamental aspect of human experience. Engaging deeply with stories and spotting plot holes -- inconsistencies in a storyline that break the internal logic or rules…

cs.CL2025

AI as Humanity's Salieri: Quantifying Linguistic Creativity of Language Models via Systematic Attribution of Machine Text against Web Text

Ximing Lu, Melanie Sclar, Skyler Hallinan +8

Creativity has long been considered one of the most difficult aspect of human intelligence for AI to mimic. However, the rise of Large Language Models (LLMs), like ChatGPT, has rai…

cs.CL2024

Quantifying Language Models' Sensitivity to Spurious Features in Prompt Design or: How I learned to start worrying about prompt formatting

Melanie Sclar, Yejin Choi, Yulia Tsvetkov +1

As large language models (LLMs) are adopted as a fundamental component of language technologies, it is crucial to accurately characterize their performance. Because choices in prom…

cs.CL2024

Phenomenal Yet Puzzling: Testing Inductive Reasoning Capabilities of Language Models with Hypothesis Refinement

Linlu Qiu, Liwei Jiang, Ximing Lu +8

The ability to derive underlying principles from a handful of observations and then generalize to novel situations -- known as inductive reasoning -- is central to human intelligen…