collaborators

5 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.AI2026

Perceive Before Reasoning: A Pre-Reasoning Perception Framework for Efficient and Reliable Proactive Mobile Agents

Zhijie Ding, Weinan Hong, Zicheng Zhu +6

Multimodal large language models (MLLMs) have substantially advanced mobile agents, yet proactive mobile assistance remains challenging because agents must decide \emph{when} to in…

cs.AI2026

ProactiveMobile: A Comprehensive Benchmark for Boosting Proactive Intelligence on Mobile Devices

Dezhi Kong, Zhengzhao Feng, Qiliang Liang +12

Multimodal large language models (MLLMs) have made significant progress in mobile agent development, yet their capabilities are predominantly confined to a reactive paradigm, where…

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…