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20242026
most citedMeasuring and Enhancing Trustworthiness of LLMs in RAG through Grounded Attributions and Learning to Refuse

2 citations · 2 across the 18 of their papers we have counts for

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6 papers · 1 filter

cs.AI2026

Agents' Last Exam

Yiyou Sun, Xinyang Han, Weichen Zhang +378

Recent AI systems have achieved strong results on a wide range of benchmarks, yet these gains have not translated into economically meaningful deployment across many professional d…

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

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

Epistemic Context Learning: Building Trust the Right Way in LLM-Based Multi-Agent Systems

Ruiwen Zhou, Maojia Song, Xiaobao Wu +8

Individual agents in multi-agent (MA) systems often lack robustness, tending to blindly conform to misleading peers. We show this weakness stems from both sycophancy and inadequate…

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…