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20242026
most citedAdvances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems

16 citations · 25 across the 14 of their papers we have counts for

collaborators

15 papers

cs.CL2026

SMTrap: Cost-Effective DoS Attacks Against Large Reasoning Models via SMT Conflict Guidance

Jian Yang, Zhenqi Feng, Zhaoyang Yu +7

Existing LRM-DoS methods rely heavily on model feedback to synthesize attack queries, requiring either repeated queries to the target model or training a dedicated attack model. Th…

cs.AI2026

Foundation Protocol: A Coordination Layer for Agentic Society

Bang Liu, Yongfeng Gu, Jiayi Zhang +26

Autonomous agents are moving from tools into a layer of social infrastructure: they browse, purchase, deploy software, manage systems, and increasingly interact with one another. A…

cs.AI2026

Scalable Environments Drive Generalizable Agents

Jiayi Zhang, Fanqi Kong, Guibin Zhang +7

Generalizable agents should adapt to diverse tasks and unseen environments beyond their training distribution. This position paper argues that such generalization requires environm…

cs.AI2026

AutoWebWorld: Synthesizing Infinite Verifiable Web Environments via Finite State Machines

Yifan Wu, Yiran Peng, Yiyu Chen +12

The performance of autonomous Web GUI agents heavily relies on the quality and quantity of their training data. However, a fundamental bottleneck persists: collecting interaction t…

cs.AI2026

AOrchestra: Automating Sub-Agent Creation for Agentic Orchestration

Jianhao Ruan, Zhihao Xu, Yiran Peng +9

Language agents have shown strong promise for task automation. Realizing this promise for increasingly complex, long-horizon tasks has driven the rise of a sub-agent-as-tools parad…

cs.AI2025

AutoEnv: Automated Environments for Measuring Cross-Environment Agent Learning

Jiayi Zhang, Yiran Peng, Fanqi Kong +12

Humans naturally adapt to diverse environments by learning underlying rules across worlds with different dynamics, observations, and reward structures. In contrast, existing agents…

cs.CV2025

Reasoning via Video: The First Evaluation of Video Models' Reasoning Abilities through Maze-Solving Tasks

Cheng Yang, Haiyuan Wan, Yiran Peng +8

Video Models have achieved remarkable success in high-fidelity video generation with coherent motion dynamics. Analogous to the development from text generation to text-based reaso…

cs.CL2025

InteractComp: Evaluating Search Agents With Ambiguous Queries

Mingyi Deng, Lijun Huang, Yani Fan +23

Language agents have demonstrated remarkable potential in web search and information retrieval. However, many search-agent benchmarks assume that user queries are complete and unam…

cs.AI2025

ReCode: Unify Plan and Action for Universal Granularity Control

Zhaoyang Yu, Jiayi Zhang, Huixue Su +9

Real-world tasks require decisions at varying granularities, and humans excel at this by leveraging a unified cognitive representation where planning is fundamentally understood as…

cs.CL2025

VisJudge-Bench: Aesthetics and Quality Assessment of Visualizations

Yupeng Xie, Zhiyang Zhang, Yifan Wu +8

Visualization, a domain-specific yet widely used form of imagery, is an effective way to turn complex datasets into intuitive insights, and its value depends on whether data are fa…

cs.AI2025★ 16 cited

Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems

Bang Liu, Xinfeng Li, Jiayi Zhang +45

The advent of large language models (LLMs) has catalyzed a transformative shift in artificial intelligence, paving the way for advanced intelligent agents capable of sophisticated…

cs.CL2025

Atom of Thoughts for Markov LLM Test-Time Scaling

Fengwei Teng, Quan Shi, Zhaoyang Yu +4

Large Language Models (LLMs) have achieved significant performance gains through test-time scaling methods. However, existing approaches often incur redundant computations due to t…

cs.CL2025★ 2 cited

Self-Supervised Prompt Optimization

Jinyu Xiang, Jiayi Zhang, Zhaoyang Yu +8

Well-designed prompts are crucial for enhancing Large language models' (LLMs) reasoning capabilities while aligning their outputs with task requirements across diverse domains. How…

cs.AI2024★ 7 cited

AFlow: Automating Agentic Workflow Generation

Jiayi Zhang, Jinyu Xiang, Zhaoyang Yu +11

Large language models (LLMs) have demonstrated remarkable potential in solving complex tasks across diverse domains, typically by employing agentic workflows that follow detailed i…

cs.AI2024

MobileExperts: A Dynamic Tool-Enabled Agent Team in Mobile Devices

Jiayi Zhang, Chuang Zhao, Yihan Zhao +3

The attainment of autonomous operations in mobile computing devices has consistently been a goal of human pursuit. With the development of Large Language Models (LLMs) and Visual L…