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cs.CL2026
LMs as Task-Specific Knowledge Bases: An Interpretability Analysis
Amit Elhelo, Amir Globerson, Mor Geva
Language models (LMs) capture large amounts of factual knowledge applicable to a wide range of tasks, motivating the view of their parameters as a knowledge base. An important prop…
cs.CL2026
Latent Reasoning with Supervised Thinking States
Ido Amos, Avi Caciularu, Mor Geva +4
Reasoning with a chain-of-thought (CoT) enables Large Language Models (LLMs) to solve complex tasks but incurs significant inference costs due to the generation of long rationales.…