1 citations · 1 across the 3 of their papers we have counts for
4 papers
Hierarchical Orthogonal Residual Spread for Precise Massive Editing in Large Language Models
Xiaojie Gu, Guangxu Chen, Yuheng Yang +2
Large language models (LLMs) exhibit exceptional performance across various domains, yet they face critical safety concerns. Model editing has emerged as an effective approach to m…
DRIVE: Data Curation Best Practices for Reinforcement Learning with Verifiable Reward in Competitive Code Generation
Speed Zhu, Jianwei Cai, Guang Chen +3
Recent reasoning-first models (e.g., OpenAI o1, DeepSeek R1) have spurred a resurgence of interest in RLVR. Nevertheless, advances are dominated by mathematics (e.g., AIME), with c…
Think in Blocks: Adaptive Reasoning from Direct Response to Deep Reasoning
Yekun Zhu, Guang Chen, Chengjun Mao
Large Language Models (LLMs) with chains-of-thought have demonstrated strong performance on an increasing range of tasks, particularly those involving complex logical reasoning. Ho…
LL3M: Large Language 3D Modelers
Sining Lu, Guan Chen, Nam Anh Dinh +3
We present LL3M, a multi-agent system that leverages pretrained large language models (LLMs) to generate 3D assets by writing interpretable Python code in Blender. We break away fr…