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

16 citations · 19 across the 24 of their papers we have counts for

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13 papers · 1 filter

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

Latent Action Reparameterization for Efficient Agent Inference

Wenhao Huang, Qingwen Zeng, Qiyue Chen +11

Large language model (LLM) agents often rely on long sequences of low-level textual actions, resulting in large effective decision horizons and high inference cost. While prior wor…

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

Harnessing Agentic Evolution

Jiayi Zhang, Yongfeng Gu, Jianhao Ruan +10

Agentic evolution has emerged as a powerful paradigm for improving programs, workflows, and scientific solutions by iteratively generating candidates, evaluating them, and using fe…

cs.AI2026

StepOPSD: Step-Aware Online Preference Self-Distillation for Agent Reinforcement Learning

Yanfei Zhang, Xu Lin, Chenglin Wu

Reinforcement learning for multi-turn agents suffers from a credit-assignment mismatch: rewards are sparse and trajectory-level, while success often hinges on a few local decisions…

cs.AI2026

Understanding and Mitigating Premature Confidence for Better LLM Reasoning

Jingchu Gai, Guanning Zeng, Christina Baek +4

Long chains of thought (CoT) from current language models frequently contain logical gaps and unjustified leaps, limiting the gains from additional test-time compute. Improving rea…

cs.AI2026

The Latent Space: Foundation, Evolution, Mechanism, Ability, and Outlook

Xinlei Yu, Zhangquan Chen, Yongbo He +36

Latent space is rapidly emerging as a native substrate for language-based models. While modern systems are still commonly understood through explicit token-level generation, an inc…

cs.AI2026

InfoPO: Information-Driven Policy Optimization for User-Centric Agents

Fanqi Kong, Jiayi Zhang, Mingyi Deng +3

Real-world user requests to LLM agents are often underspecified. Agents must interact to acquire missing information and make correct downstream decisions. However, current multi-t…

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.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.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…