215 citations · 893 across the 32 of their papers we have counts for
33 papers
Latent Collaboration in Multi-Agent Systems
Jiaru Zou, Ruizhong Qiu, Gaotang Li +10
Multi-agent systems (MAS) extend large language models (LLMs) from independent single-model reasoning to coordinative system-level intelligence. While existing LLM agents depend on…
In-the-Flow Agentic System Optimization for Effective Planning and Tool Use
Zhuofeng Li, Haoxiang Zhang, Seungju Han +6
Outcome-driven reinforcement learning has advanced reasoning in large language models (LLMs), but prevailing tool-augmented approaches train a single, monolithic policy that interl…
OctoTools: An Agentic Framework with Extensible Tools for Complex Reasoning
Pan Lu, Bowen Chen, Sheng Liu +3
Solving complex reasoning tasks may involve visual understanding, domain knowledge retrieval, numerical calculation, and multi-step reasoning. Existing methods augment large langua…
MuirBench: A Comprehensive Benchmark for Robust Multi-image Understanding
Fei Wang, Xingyu Fu, James Y. Huang +18
We introduce MuirBench, a comprehensive benchmark that focuses on robust multi-image understanding capabilities of multimodal LLMs. MuirBench consists of 12 diverse multi-image tas…
VDebugger: Harnessing Execution Feedback for Debugging Visual Programs
Xueqing Wu, Zongyu Lin, Songyan Zhao +4
Visual programs are executable code generated by large language models to address visual reasoning problems. They decompose complex questions into multiple reasoning steps and invo…
Enhancing Large Vision Language Models with Self-Training on Image Comprehension
Yihe Deng, Pan Lu, Fan Yin +6
Large vision language models (LVLMs) integrate large language models (LLMs) with pre-trained vision encoders, thereby activating the perception capability of the model to understan…