1 citations · 2 across the 6 of their papers we have counts for
5 papers · 1 filter
Targeting Pivotal Decisions for Credit Assignment in Agentic Reinforcement Learning
Dongwon Jung, Hemanth Neelgund Ramesh, Yifan Wang +7
Group Relative Policy Optimization (GRPO) has become a promising approach for training large language model agents. However, its uniform assignment of trajectory-level advantages t…
Adaptive Latent Agentic Reasoning
Dongwon Jung, Peng Shi, Yi Zhang +2
Large reasoning models improve performance by generating extended chain-of-thought (CoT) reasoning, but this behavior becomes inefficient when applied to LLM agents. Current LLM ag…
Code Execution as Grounded Supervision for LLM Reasoning
Dongwon Jung, Wenxuan Zhou, Muhao Chen
Training large language models (LLMs) with chain-of-thought (CoT) supervision has proven effective for enhancing their reasoning abilities. However, obtaining reliable and accurate…
Familiarity-Aware Evidence Compression for Retrieval-Augmented Generation
Dongwon Jung, Qin Liu, Tenghao Huang +2
Retrieval-augmented generation (RAG) improves large language models (LMs) by incorporating non-parametric knowledge through evidence retrieved from external sources. However, it of…
Planning and Editing What You Retrieve for Enhanced Tool Learning
Tenghao Huang, Dongwon Jung, Muhao Chen
Recent advancements in integrating external tools with Large Language Models (LLMs) have opened new frontiers, with applications in mathematical reasoning, code generators, and sma…