3 citations · 3 across the 3 of their papers we have counts for
3 papers
Enhancing Self-Correction in Large Language Models through Multi-Perspective Reflection
Mariana Costa, Alberlucia Rafael Soarez, Daniel Kim +1
While Chain-of-Thought (CoT) prompting advances LLM reasoning, challenges persist in consistency, accuracy, and self-correction, especially for complex or ethically sensitive tasks…
CLEAR: Contrasting Textual Feedback with Experts and Amateurs for Reasoning
Andrew Rufail, Daniel Kim, Sean O'Brien +1
We introduce CLEAR (Contrasting Textual Feedback with Experts and Amateurs for Reasoning), a novel approach to language model reasoning that leverages the strengths of a larger (ex…
Chain-of-Thought Augmentation with Logit Contrast for Enhanced Reasoning in Language Models
Jay Shim, Grant Kruttschnitt, Alyssa Ma +5
Rapidly increasing model scales coupled with steering methods such as chain-of-thought prompting have led to drastic improvements in language model reasoning. At the same time, mod…