3 papers
cs.CL2026
Large Language Models Decide Early and Explain Later
Ayan Datta, Zhixue Zhao, Bhuvanesh Verma +3
Large Language Models often achieve strong performance by generating long intermediate chain-of-thought reasoning. However, it remains unclear when a model's final answer is actual…
cs.CL2026
From Early Encoding to Late Suppression: Interpreting LLMs on Character Counting Tasks
Ayan Datta, Mounika Marreddy, Alexander Mehler +2
Large language models (LLMs) exhibit failures on elementary symbolic tasks such as character counting in a word, despite excelling on complex benchmarks. Although this limitation h…
cs.CL2025
Confabulations from ACL Publications (CAP): A Dataset for Scientific Hallucination Detection
Federica Gamba, Aman Sinha, Timothee Mickus +12
We introduce the CAP (Confabulations from ACL Publications) dataset, a multilingual resource for studying hallucinations in large language models (LLMs) within scientific text gene…