3 papers
cs.AI2026
Nanbeige4.2-3B: Unlocking Agentic Capabilities in a Compact Model
Nanbeige Lab, :, Chen Yang +23
We present Nanbeige4.2-3B, a compact general agentic model with 3B non-embedding parameters. It delivers strong performance across code-agent, office-agent, and complex tool-use ta…
cs.CL2026
From Skill Text to Skill Structure: The Scheduling-Structural-Logical Representation for Agent Skills
Qiliang Liang, Hansi Wang, Zhong Liang +1
Large language model (LLM) agents increasingly rely on reusable skills: capability packages that combine instructions, control flow, constraints, and tool calls. In current agent s…
cs.CL2025
From Imitation to Discrimination: Toward A Generalized Curriculum Advantage Mechanism Enhancing Cross-Domain Reasoning Tasks
Changpeng Yang, Jinyang Wu, Yuchen Liu +9
Reinforcement learning has emerged as a paradigm for post-training large language models, boosting their reasoning capabilities. Such approaches compute an advantage value for each…