1 citations · 1 across the 2 of their papers we have counts for
5 papers
RedCoder: Automated Multi-Turn Red Teaming for Code LLMs
Wenjie Jacky Mo, Qin Liu, Xiaofei Wen +5
Large Language Models (LLMs) for code generation (i.e., Code LLMs) have demonstrated impressive capabilities in AI-assisted software development and testing. However, recent studie…
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…
FRIEDA: Benchmarking Multi-Step Cartographic Reasoning in Vision-Language Models
Jiyoon Pyo, Yuankun Jiao, Dongwon Jung +11
Cartographic reasoning is the skill of interpreting geographic relationships by aligning legends, map scales, compass directions, map texts, and geometries across one or more map i…
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…