From the 1 of 9 linked papers with an AI index.
9 papers
ComplexityWorld: Benchmarking Vision-Language Models on Verifiable Visual Decision Making
Ningxin Pan, Hanyu Li, Yehui Tang
Vision-language models (VLMs) have made rapid progress in visual perception and increasingly support real-world tasks that depend on images. Many such tasks, however, require more…
FaithEyes: Towards Faithful Tool Use via Multi-Agent Process-Image Verification
Haoqing Wang, Xingrun Xing, Wei Xia +2
FaithEyes proposes a multi‑agent framework where a vision‑language model judges its own tool calls to ensure they are useful, improving both accuracy and tool faithfulness on visua…
LiveClawBench: Benchmarking LLM Agents on Complex, Real-World Assistant Tasks
Xiang Long, Li Du, Yilong Xu +11
OpenClaw-style personal assistants extend LLM agents from isolated tool use to open-ended, stateful, and personalized software environments. Evaluating these assistants is fundamen…
Trust Region On-Policy Distillation
Xingrun Xing, Haoqing Wang, Boyan Gao +2
On-Policy Distillation (OPD) is a fundamental technique for efficient post-training of large language models (LLMs), with broad applications in agent learning, multi-task enhanceme…
When Do LLMs Reason? A Dynamical Systems View via Entropy Phase Transitions
Wei Xia, Haoqing Wang, Zhi-Hong Deng +1
Chain-of-thought (CoT) reasoning has become the default strategy for enhancing LLM capabilities, yet its application raises a fundamental question: when is explicit reasoning actua…
MemTrain: Self-Supervised Context Memory Training
Ziheng Li, Xingrun Xing, Haoqing Wang +2
Memory is an indispensable capability for long-horizon LLM agents, enabling them to preserve and utilize information accumulated across extended interactions. Existing memory-agent…