2 citations · 3 across the 15 of their papers we have counts for
8 papers · 1 filter
Sibyl: An Efficient Small-large Model Collaboration Framework for Long-horizon Tasks
Zhewei Fang, Yuxin Zhang, Zhenwei Shao +8
Small language models (SLMs) offer a promising foundation for on-device agents through low-latency, resource-efficient inference, yet limited reasoning and planning capabilities co…
SCOUT: Synergizing Reasoning and Tool-Use for Computer-Use Safety
Jianxing Chen, Xiao Yu, Shipra Agrawal +1
Computer-use agents (CUAs), while capable of completing computer tasks in everyday and professional workflows, can cause unintended harm even under benign instructions and environm…
Co-Evolving Harnesses and Models: On-Policy Correction Helps Weaker Models Catch Up Where Imitation Fails
Zhou Yu, Bin Bi, Shiva Kumar Pentyala +8
Agent harnesses (the system prompt, tool set, execution hooks, and context-management scaffolding around a model) are a critical determinant of agentic task success. Automated harn…
OpenForgeRL: Train Harness-native Agents in Any Environment
Xiao Yu, Baolin Peng, Ruize Xu +7
Modern AI agents rely on elaborate inference harnesses such as Claude Code, Codex, and OpenClaw to drive multi-turn reasoning, tool use, and access to external systems. While power…
Factorization-Error-Free Discrete Diffusion Language Model via Speculative Decoding
Xun Fang, Yunchen Li, Hang Yuan +1
Discrete diffusion language models improve generation efficiency through parallel token prediction, but standard prediction methods introduce factorization errors by approxim…
ConFit v3: Improving Resume-Job Matching with LLM-based Re-Ranking
Xiao Yu, Ruize Xu, Chengyuan Xue +6
A reliable resume-job matching system helps a company find suitable candidates from a pool of resumes and helps a job seeker find relevant jobs from a list of job posts. While rece…
Orchard: An Open-Source Agentic Modeling Framework
Baolin Peng, Wenlin Yao, Qianhui Wu +11
Agentic modeling aims to transform LLMs into autonomous agents capable of solving complex tasks through planning, reasoning, tool use, and multi-turn interaction with external envi…
Reinforcement World Model Learning for LLM-based Agents
Xiao Yu, Baolin Peng, Ruize Xu +6
Large language models (LLMs) have achieved strong performance in language-centric tasks. However, in agentic settings, LLMs often struggle to anticipate action consequences and ada…