6 citations · 7 across the 48 of their papers we have counts for
19 papers · 1 filter
Model What Matters: Decision-Guided Selective World Modeling for Language Agents
Maolin Ran, Minda Chen, Di Huang +3
Reinforcement learning provides a direct mechanism for optimizing task objectives in large language model-driven agents, but task rewards are typically sparse trajectory-level sign…
Evaluating Agentic Capabilities Before Post-Training: An End-to-End Approach
Jiarui Qin, Junjie Huang, Yunjia Xi +5
Agentic capabilities are increasingly important for modern LLMs, yet remain difficult to evaluate during pretraining. Existing approaches typically rely on static trajectory-derive…
PhysCodeGym: Benchmarking Coding Agents for Physically Verifiable 4D Reconstruction
Shuai Shao, Jinchen He, Cunxin Fan +10
Building physical simulations from video requires coding agents to translate observations into executable models and refine them through tool use. We introduce PhysCodeGym, a bench…
FleetPilot: Fine-Grained Steering Empowers Real-World LLM Personalization
Kounianhua Du, Jianxing Liu, Kangning Zhang +7
With the rapid evolution of large language models (LLMs), there is an increasing demand for effective personalization techniques that can adapt model behavior to individual user pr…
SEAM: Shot Entity-Attribute Memory for Consistent Short-Drama Generation at Scale
Jiaqi Liu, Maolin Ran, Xiaoyang Lu +5
Short-drama generation has grown into a large, industrialized pipeline, and as it scales from isolated shots to the episode level, visual continuity has become a critical bottlenec…
SkillGate: Training In-Policy Skill Selection in Long-Horizon Agents
Qingyao Li, Wenxiang Jiao, Shuai Shao +6
Agent frameworks increasingly package procedural knowledge as skills: instruction files an agent reads on demand, while public libraries now hold thousands of them. Which skill to…
SAGE: Self-Evolving Storyboard Skills via Attribution-Guided Rule Evolution
Maolin Ran, Xiaoyang Lu, Jiaqi Liu +5
Storyboards turn screenplays into visual shot plans for automated short drama production. Professional storyboarding relies on tacit directorial expertise and remains an industrial…
EnvACE: Internalizing Environment Dynamics via World Rehearsal for Agentic Reinforcement Learning
Zishan Xu, Zhiyuan Yao, Yuxin Chen +9
Training large language model agents for long-horizon tool use typically relies on interactions with real or synthesized executable environments, whose construction and verificatio…
Harness-R1: Learning to Edit Executable Runtime Harnesses from Agent Failure Trajectories
Shuai Shao, Kangning Zhang, Qingyao Li +7
Agents built around large language models continually accumulate interaction trajectories during deployment, yet their behavior typically remains fixed. Beyond updating model weigh…
Communication Policy Evolution for Proactive LLM Agents
Xinbei Ma, Jiyang Qiu, Yao Yao +10
LLM agents have rapidly evolved into autonomous systems, yet a persistent information gap remains between users and agents: communication is costly, while users' identical preferen…
MMSkills: Towards Multimodal Skills for General Visual Agents
Kangning Zhang, Shuai Shao, Qingyao Li +8
Reusable skills have become a core substrate for improving agent capabilities, yet most existing skill packages encode reusable behavior primarily as textual prompts, executable co…
Turing Test on Screen: A Benchmark for Mobile GUI Agent Humanization
Jiachen Zhu, Lingyu Yang, Rong Shan +6
The rise of autonomous GUI agents has triggered adversarial countermeasures from digital platforms, yet existing research prioritizes utility and robustness over the critical dimen…
Holos: A Web-Scale LLM-Based Multi-Agent System for the Agentic Web
Xiaohang Nie, Zihan Guo, Zicai Cui +20
As large language models (LLM)-driven agents transition from isolated task solvers to persistent digital entities, the emergence of the Agentic Web, an ecosystem where heterogeneou…
Plan-MCTS: Plan Exploration for Action Exploitation in Web Navigation
Weiming Zhang, Jihong Wang, Jiamu Zhou +9
Large Language Models (LLMs) have empowered autonomous agents to handle complex web navigation tasks. While recent studies integrate tree search to enhance long-horizon reasoning,…
ACE-Router: Generalizing History-Aware Routing from MCP Tools to the Agent Web
Zhiyuan Yao, Zishan Xu, Yifu Guo +6
With the rise of the Agent Web and Model Context Protocol (MCP), the agent ecosystem is evolving into an open collaborative network, exponentially increasing accessible tools. Howe…
Fints: Efficient Inference-Time Personalization for LLMs with Fine-Grained Instance-Tailored Steering
Kounianhua Du, Jianxing Liu, Kangning Zhang +6
The rapid evolution of large language models (LLMs) has intensified the demand for effective personalization techniques that can adapt model behavior to individual user preferences…
APTBench: Benchmarking Agentic Potential of Base LLMs During Pre-Training
Jiarui Qin, Yunjia Xi, Junjie Huang +6
With the rapid development of LLM-based agents, there is a growing trend to incorporate agent-specific data into the pre-training stage of LLMs, aiming to better align LLMs with re…
ColorBench: Benchmarking Mobile Agents with Graph-Structured Framework for Complex Long-Horizon Tasks
Yuanyi Song, Heyuan Huang, Qiqiang Lin +9
The rapid advancement of multimodal large language models has enabled agents to operate mobile devices by directly interacting with graphical user interfaces, opening new possibili…
CATArena: Evaluating Evolutionary Capabilities of Code Agents via Iterative Tournaments
Lingyue Fu, Xin Ding, Linyue Pan +9
Current evaluation for Large Language Model (LLM) code agents predominantly focus on generating functional code in single-turn scenarios, which fails to evaluate the agent's capabi…