10 papers · 1 filter
Reinforcement Learning with Metacognitive Feedback Elicits Faithful Uncertainty Expression in LLMs
Gabrielle Kaili-May Liu, Avi Caciularu, Gal Yona +2
Metacognition is a critical component of intelligence that describes the ability to monitor and regulate one's own cognitive processes. Yet LLMs exhibit systemic deficiencies in ke…
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.…
MetaFaith: Faithful Natural Language Uncertainty Expression in LLMs
Gabrielle Kaili-May Liu, Gal Yona, Avi Caciularu +3
A critical component in the trustworthiness of LLMs is reliable uncertainty communication, yet LLMs often use assertive language when conveying false claims, leading to over-relian…
ReliableEval: A Recipe for Stochastic LLM Evaluation via Method of Moments
Gili Lior, Eliya Habba, Shahar Levy +2
LLMs are highly sensitive to prompt phrasing, yet standard benchmarks typically report performance using a single prompt, raising concerns about the reliability of such evaluations…
DoubleDipper: Improving Long-Context LLMs via Context Recycling
Arie Cattan, Alon Jacovi, Alex Fabrikant +8
Despite recent advancements in Large Language Models (LLMs), their performance on tasks involving long contexts remains sub-optimal. In this work, we propose DoubleDipper, a novel…
DRAGged into Conflicts: Detecting and Addressing Conflicting Sources in Search-Augmented LLMs
Arie Cattan, Alon Jacovi, Ori Ram +6
Retrieval Augmented Generation (RAG) is a commonly used approach for enhancing large language models (LLMs) with relevant and up-to-date information. However, the retrieved sources…