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20242026
most citedConfusionPrompt: Practical Private Inference for Online Large Language Models

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cs.AI2026

EvoMaster: A Foundational Evolving Agent Framework for Agentic Science at Scale

Xinyu Zhu, Yuzhu Cai, Zexi Liu +20

The convergence of large language models and agents is catalyzing a new era of scientific discovery: Agentic Science. While the scientific method is inherently iterative, existing…

cs.AI2026

LongSeeker: Elastic Context Orchestration for Long-Horizon Search Agents

Yijun Lu, Rui Ye, Yuwen Du +3

Long-horizon search agents must manage a rapidly growing working context as they reason, call tools, and observe information. Naively accumulating all intermediate content can over…

cs.AI2026

OpenSeeker-v2: Pushing the Limits of Search Agents with Informative and High-Difficulty Trajectories

Yuwen Du, Rui Ye, Shuo Tang +4

Deep search capabilities have become an indispensable competency for frontier Large Language Model (LLM) agents, yet their development remains dominated by industrial giants. The t…

cs.AI2025

BrowseMaster: Towards Scalable Web Browsing via Tool-Augmented Programmatic Agent Pair

Xianghe Pang, Shuo Tang, Rui Ye +3

Effective information seeking in the vast and ever-growing digital landscape requires balancing expansive search with strategic reasoning. Current large language model (LLM)-based…

cs.AI2025

SciMaster: Towards General-Purpose Scientific AI Agents, Part I. X-Master as Foundation: Can We Lead on Humanity's Last Exam?

Jingyi Chai, Shuo Tang, Rui Ye +8

The rapid advancements of AI agents have ignited the long-held ambition of leveraging them to accelerate scientific discovery. Achieving this goal requires a deep understanding of…

cs.AI2025

MobileA3gent: Training Mobile GUI Agents Using Decentralized Self-Sourced Data from Diverse Users

Wenhao Wang, Mengying Yuan, Zijie Yu +5

The advancement of mobile GUI agents has opened new opportunities for automating tasks on mobile devices. Training these agents requires large-scale high-quality data, which is pro…