9 papers
ClawEnvKit: Automatic Environment Generation for Claw-Like Agents
Xirui Li, Ming Li, Ion Stoica +2
Constructing environments for training and evaluating claw-like agents remains a manual, human-intensive process that does not scale. We argue that what is needed is not just a dat…
Sparse MeZO: Less Parameters for Better Performance in Zeroth-Order LLM Fine-Tuning
Yong Liu, Zirui Zhu, Chaoyu Gong +3
While fine-tuning large language models (LLMs) for specific tasks often yields impressive results, it comes at the cost of memory inefficiency due to back-propagation in gradient-b…
QG-CoC: Question-Guided Chain-of-Captions for Large Multimodal Models
Kuei-Chun Kao, Hsu Tzu-Yin, Yunqi Hong +2
Recently, Multimodal Large Language Models (MLLMs) encounter two key issues in multi-image contexts: (1) a lack of fine-grained perception across disparate images, and (2) a dimini…
POME: Post Optimization Model Edit via Muon-style Projection
Yong Liu, Di Fu, Yang Luo +4
We introduce Post-Optimization Model Edit (POME), a new algorithm that enhances the performance of fine-tuned large language models using only their pretrained and fine-tuned check…
OR-Bench: An Over-Refusal Benchmark for Large Language Models
Justin Cui, Wei-Lin Chiang, Ion Stoica +1
Large Language Models (LLMs) require careful safety alignment to prevent malicious outputs. While significant research focuses on mitigating harmful content generation, the enhance…
Don't Think Longer, Think Wisely: Optimizing Thinking Dynamics for Large Reasoning Models
Sohyun An, Ruochen Wang, Tianyi Zhou +1
While recent success of large reasoning models (LRMs) significantly advanced LLMs' reasoning capability by optimizing the final answer accuracy using reinforcement learning, they m…