4 citations · 5 across the 17 of their papers we have counts for
5 papers · 2 filters
ReflectRL: Learning from Golden Negative Trajectories via Reflective-to-Direct Reasoning
Jinhe Bi, Chennan Zhou, Zengjie Jin +10
On-policy training has emerged as a powerful post-training paradigm for improving the reasoning capabilities of large language models, and is often enhanced by golden trajectories…
HarnessX: A Composable, Adaptive, and Evolvable Agent Harness Foundry
Tingyang Chen, Shuo Lu, Kang Zhao +11
AI agent performance depends critically on the runtime harness, comprising the prompts, tools, memory, and control flow that mediate how a model observes, reasons, and acts. Yet to…
Mi-Memory: A Lifecycle Memory Framework for Personal AI
Xule Liu, Hanlin Teng, Chao Li +15
Personal AI is moving beyond chat-only interaction toward continuous services that span phones, cars, homes, wearables, cameras, and tools. In this setting, memory cannot remain a…
WorldCoder-Bench: Benchmarking Physically Grounded 3D World Synthesis
Shuo Lu, Yinuo Xu, Kecheng Yu +8
Large language models (LLMs) are increasingly asked not only to write static interfaces, but to construct executable interactive worlds from natural language. Browser-native 3D, co…
Do MLLMs Really Understand Space? A Mathematical Reasoning Evaluation
Shuo Lu, Jianjie Cheng, Yinuo Xu +16
Multimodal large language models (MLLMs) have achieved strong performance on perception-oriented tasks, yet their ability to perform mathematical spatial reasoning, defined as the…