3 papers
cs.CL2026
When Do LLMs Admit Their Mistakes? Understanding The Role Of Model Belief In Retraction
Yuqing Yang, Robin Jia
We study the internal mechanisms that govern when LLMs choose to retract wrong answers, i.e., spontaneously and immediately acknowledge errors in their previously generated false a…
cs.CL2025
Promote, Suppress, Iterate: How Language Models Answer One-to-Many Factual Queries
Tianyi Lorena Yan, Robin Jia
To answer one-to-many factual queries (e.g., listing cities of a country), a language model (LM) must simultaneously recall knowledge and avoid repeating previous answers. How are…
cs.CL2025
Mechanistic Interpretability of Emotion Inference in Large Language Models
Ala N. Tak, Amin Banayeeanzade, Anahita Bolourani +3
Large language models (LLMs) show promising capabilities in predicting human emotions from text. However, the mechanisms through which these models process emotional stimuli remain…