activity
20212026
most citedClip-Low Increases Entropy and Clip-High Decreases Entropy in Reinforcement Learning of Large Language Models

1 citations · 2 across the 10 of their papers we have counts for

collaborators
Showing 2024Show all

2 papers · 1 filter

cs.CL2024

Divide and Translate: Compositional First-Order Logic Translation and Verification for Complex Logical Reasoning

Hyun Ryu, Gyeongman Kim, Hyemin S. Lee +1

Complex logical reasoning tasks require a long sequence of reasoning, which a large language model (LLM) with chain-of-thought prompting still falls short. To alleviate this issue,…

cs.CL2024

PromptKD: Distilling Student-Friendly Knowledge for Generative Language Models via Prompt Tuning

Gyeongman Kim, Doohyuk Jang, Eunho Yang

Recent advancements in large language models (LLMs) have raised concerns about inference costs, increasing the need for research into model compression. While knowledge distillatio…