activity
20242026
most citedOpenSeeker: Democratizing Frontier Search Agents by Fully Open-Sourcing Training Data

1 citations · 3 across the 14 of their papers we have counts for

collaborators

14 papers

cs.LG2026

DataMaster: Data-Centric Autonomous AI Research

Yaxin Du, Xiyuan Yang, Zhifan Zhou +12

As model families, training recipes, and compute budgets become increasingly standardized, further gains in machine learning systems depend increasingly on data. Yet data engineeri…

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.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. However, common agent infrastructure is repeatedly rebuilt acr…

cs.AI2026★ 1 cited

OpenSeeker: Democratizing Frontier Search Agents by Fully Open-Sourcing Training Data

Yuwen Du, Rui Ye, Shuo Tang +4

Deep search capabilities have become an indispensable competency for frontier Large Language Model (LLM) agents, yet the development of high-performance search agents remains domin…

cs.CL2026

Projection-Free Evolution Strategies for Continuous Prompt Search

Yu Cai, Canxi Huang, Xiaoyu He

Continuous prompt search offers a computationally efficient alternative to conventional parameter tuning in natural language processing tasks. Nevertheless, its practical effective…

cs.LG2026

AceGRPO: Adaptive Curriculum Enhanced Group Relative Policy Optimization for Autonomous Machine Learning Engineering

Yuzhu Cai, Zexi Liu, Xinyu Zhu +3

Autonomous Machine Learning Engineering (MLE) requires agents to perform sustained, iterative optimization over long horizons. While recent LLM-based agents show promise, current p…

cs.AI2026

From Digital to Physical: Digital Agents as Autonomous Coaches for Physical Intelligence

Zixing Lei, Genjia Liu, Yuanshuo Zhang +11

The field of Embodied AI is witnessing a rapid evolution toward general-purpose robotic systems, fueled by high-fidelity simulation and large-scale data collection. However, this s…

cs.AI2026

Toward Ultra-Long-Horizon Agentic Science: Cognitive Accumulation for Machine Learning Engineering

Xinyu Zhu, Yuzhu Cai, Zexi Liu +8

The advancement of artificial intelligence toward agentic science is currently bottlenecked by the challenge of ultra-long-horizon autonomy, the ability to sustain strategic cohere…

cs.AI2025

Bohrium + SciMaster: Building the Infrastructure and Ecosystem for Agentic Science at Scale

Linfeng Zhang, Siheng Chen, Yuzhu Cai +46

AI agents are emerging as a practical way to run multi-step scientific workflows that interleave reasoning with tool use and verification, pointing to a shift from isolated AI-assi…

cs.AI2025★ 1 cited

ML-Master: Towards AI-for-AI via Integration of Exploration and Reasoning

Zexi Liu, Yuzhu Cai, Xinyu Zhu +6

As AI capabilities advance toward and potentially beyond human-level performance, a natural transition emerges where AI-driven development becomes more efficient than human-centric…

cs.CL2025

MASLab: A Unified and Comprehensive Codebase for LLM-based Multi-Agent Systems

Rui Ye, Keduan Huang, Qimin Wu +17

LLM-based multi-agent systems (MAS) have demonstrated significant potential in enhancing single LLMs to address complex and diverse tasks in practical applications. Despite conside…

cs.SE2025

SWE-Dev: Evaluating and Training Autonomous Feature-Driven Software Development

Yaxin Du, Yuzhu Cai, Yifan Zhou +6

Large Language Models (LLMs) have shown strong capability in diverse software engineering tasks. However, feature-driven development, a highly prevalent real-world task that involv…

cs.SE2024★ 1 cited

Self-Evolving Multi-Agent Collaboration Networks for Software Development

Yue Hu, Yuzhu Cai, Yaxin Du +6

LLM-driven multi-agent collaboration (MAC) systems have demonstrated impressive capabilities in automatic software development at the function level. However, their heavy reliance…

cs.CV2024

Ethical-Lens: Curbing Malicious Usages of Open-Source Text-to-Image Models

Yuzhu Cai, Sheng Yin, Yuxi Wei +5

The burgeoning landscape of text-to-image models, exemplified by innovations such as Midjourney and DALLE 3, has revolutionized content creation across diverse sectors. However, th…