3 papers
cs.CL2026
Performance Gap in Entity Knowledge Extraction Across Modalities in Vision Language Models
Ido Cohen, Daniela Gottesman, Mor Geva +1
Vision-language models (VLMs) excel at extracting and reasoning about information from images. Yet, their capacity to leverage internal knowledge about specific entities remains un…
cs.CL2025
How Well Can Reasoning Models Identify and Recover from Unhelpful Thoughts?
Sohee Yang, Sang-Woo Lee, Nora Kassner +3
Recent reasoning models show the ability to reflect, backtrack, and self-validate their reasoning, which is crucial in spotting mistakes and arriving at accurate solutions. A natur…
cs.CL2025
LMEnt: A Suite for Analyzing Knowledge in Language Models from Pretraining Data to Representations
Daniela Gottesman, Alon Gilae-Dotan, Ido Cohen +4
Language models (LMs) increasingly drive real-world applications that require world knowledge. However, the internal processes through which models turn data into representations o…