works on

From the 1 of 30 linked papers with an AI index.

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

1 citations · 1 across the 21 of their papers we have counts for

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12 papers · 1 filter

cs.AI2026

ABSeeker: Training Long-Horizon Search Agents via Answer-Backtracked Credit Assignment

Yijun Lu, Rui Ye, Jiajun Wang +4

Long-horizon search agents must make multiple sequential actions (steps) to search, retrieve, verify, and integrate evidence to reach a final answer. However, existing methods for…

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

Agentic Time Machine as an Infrastructure for Future-Event Forecasting

Jingyi Chai, Bingyang Zheng, Xiangrui Liu +5

Forecasting future events is a critical challenge for large language model (LLM) agents, spanning domains from elections and monetary policy to financial markets. However, evaluati…

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

MCP-Persona: Benchmarking LLM Agents on Real-World Personal Applications via Environment Simulation

Wenhao Wang, Peizhi Niu, Gongyi Zou +9

The Model Context Protocol (MCP) has emerged as a transformative standard for connecting large language models (LLMs) with external data sources and tools, and has been rapidly ado…

cs.AI2026

MIRA: Mid-training Rubric Anchoring for Source-Aware Data Selection

Haowen Wang, Yaxin Du, Jian Yang +9

Mid-training has become an important stage in modern LLM development, using large-scale curated mixtures to strengthen capabilities before final post-training. Its data selection p…