8 papers
Echo: Learning from Experience Data via User-Driven Refinement
Hande Dong, Xiaoyun Liang, Jiarui Yu +15
Static "human data" faces inherent limitations: it is expensive to scale and bounded by the knowledge of its creators. Continuous learning from "experience data" - interactions bet…
Evaluating the Search Agent in a Parallel World
Jiawei Chen, Xintian Shen, Lihao Zheng +7
Integrating web search tools has significantly extended the capability of LLMs to address open-world, real-time, and long-tail problems. However, evaluating these Search Agents pre…
CGC: Compositional Grounded Contrast for Fine-Grained Multi-Image Understanding
Lihao Zheng, Zhenwei Shao, Yu Zhou +5
Although Multimodal Large Language Models (MLLMs) have advanced rapidly, they still face notable challenges in fine-grained multi-image understanding, often exhibiting spatial hall…
StreamingClaw Technical Report
Jiawei Chen, Zhe Chen, Chaoqun Du +21
Emerging applications such as embodied intelligence, AI hardware, autonomous driving, and intelligent cockpits rely on a real-time perception-decision-action closed loop, posing st…
Evolving from Tool User to Creator via Training-Free Experience Reuse in Multimodal Reasoning
Xintian Shen, Jiawei Chen, Lihao Zheng +3
Existing Tool-Integrated Reasoning (TIR) models have effectively extended the question-answering capabilities of LLMs by incorporating external tools. However, real-world scenarios…
MindWatcher: Toward Smarter Multimodal Tool-Integrated Reasoning
Jiawei Chen, Xintian Shen, Lihao Zheng +43
Traditional workflow-based agents exhibit limited intelligence when addressing real-world problems requiring tool invocation. Tool-integrated reasoning (TIR) agents capable of auto…