most citedExternalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering

6 citations · 7 across the 12 of their papers we have counts for

collaborators

13 papers

cs.AI2026

AMBER: Multi-View Adaptive Budget Allocation for Listwise Vision-Language Reranking

Wenteng Chen, Jiachen Zhu, Rong Shan +10

Vision-language models (VLMs) are powerful listwise rerankers for multimodal retrieval, but high inference costs restrict them to evaluating small local candidate views. Existing m…

cs.CV2026

Weaving Visual Narratives: Agentic Image Bundle Composition Beyond Atomic Visual Matching

Rong Shan, Tianyi Xu, Congmin Zheng +9

Image retrieval has traditionally been formulated as a point-wise matching problem, where each candidate image is scored in isolation. However, this atomic paradigm fails to captur…

cs.CL2026

Retrospective Progress-Aware Self-Refinement for LLM Agent Training

Xinbei Ma, Congmin Zheng, Jiyang Qiu +11

Long-horizon LLM-based agents receive rich environmental observations during interaction, yet outcome rewards provide limited explicit supervision about how individual actions adva…

cs.CL2026

Contexting as Recommendation: Evolutionary Collaborative Filtering for Context Engineering

Jiachen Zhu, Zhuoying Ou, Congmin Zheng +9

Large Language Models (LLMs) are highly sensitive to their input contexts, motivating the development of automated context engineering. However, existing methods predominantly trea…

cs.SE2026★ 6 cited

Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering

Chenyu Zhou, Huacan Chai, Wenteng Chen +18

Large language model (LLM) agents are increasingly built less by changing model weights than by reorganizing the runtime around them. Capabilities that earlier systems expected the…

cs.AI2026

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…

cs.AI2026

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,…

cs.LG2026

Adaptive Milestone Reward for GUI Agents

Congmin Zheng, Xiaoyun Mo, Xinbei Ma +10

Reinforcement Learning (RL) has emerged as a mainstream paradigm for training Mobile GUI Agents, yet it struggles with the temporal credit assignment problem inherent in long-horiz…

cs.MA2025

ColorAgent: Building A Robust, Personalized, and Interactive OS Agent

Ning Li, Qiqiang Lin, Zheng Wu +19

With the advancements in hardware, software, and large language model technologies, the interaction between humans and operating systems has evolved from the command-line interface…

cs.CL2025★ 1 cited

A Survey of Process Reward Models: From Outcome Signals to Process Supervisions for Large Language Models

Congmin Zheng, Jiachen Zhu, Zhuoying Ou +8

Although Large Language Models (LLMs) exhibit advanced reasoning ability, conventional alignment remains largely dominated by outcome reward models (ORMs) that judge only final ans…

cs.CL2025

CoLD: Counterfactually-Guided Length Debiasing for Process Reward Models in Mathematical Reasoning

Congmin Zheng, Jiachen Zhu, Jianghao Lin +6

Process Reward Models (PRMs) play a central role in evaluating and guiding multi-step reasoning in large language models (LLMs), especially for mathematical problem solving. Howeve…

cs.CL2025

Evolutionary Perspectives on the Evaluation of LLM-Based AI Agents: A Comprehensive Survey

Jiachen Zhu, Menghui Zhu, Renting Rui +9

The advent of large language models (LLMs), such as GPT, Gemini, and DeepSeek, has significantly advanced natural language processing, giving rise to sophisticated chatbots capable…

cs.AI2025

Retrieval-Augmented Process Reward Model for Generalizable Mathematical Reasoning

Jiachen Zhu, Congmin Zheng, Jianghao Lin +5

While large language models (LLMs) have significantly advanced mathematical reasoning, Process Reward Models (PRMs) have been developed to evaluate the logical validity of reasonin…