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20232026
most citedBlack-box Model Merging for Language-Model-as-a-Service with Massive Model Repositories

2 citations · 4 across the 10 of their papers we have counts for

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5 papers · 1 filter

cs.AI2026

WEFT: Scaling Tool-Use Post-Training for General-Purpose Agents

Bo Mao, Hang He, Linting Wang +17

Recent efforts to scale tool-use post-training have largely centered on the synthesis of executable environments, which constitute only one component of a broader agentic interacti…

cs.AI2026

ContextWeave: A Real-World Workflow Benchmark

Bo Wang, Yuqian Yao, Enxi Wang +25

Memory is essential as language agents move from isolated tasks to long-horizon, stateful workflows, yet existing evaluations often reduce it to retrieval or question answering. We…

cs.AI2026

AgentHPOBench: A Benchmark For Evaluating LLM Agents as Sequential Hyperparameter Optimizers

Tianyu Huai, Tingshuo Fan, Xinchi Chen +5

As LLMs evolve from code completion systems into autonomous scientific agents, evaluating their ability to conduct experiments has become increasingly important. Existing benchmark…

cs.AI2025★ 2 cited

Black-box Model Merging for Language-Model-as-a-Service with Massive Model Repositories

Shilian Chen, Jie Zhou, Tianyu Huai +9

Model merging refers to the process of integrating multiple distinct models into a unified model that preserves and combines the strengths and capabilities of the individual models…

cs.AI2025★ 1 cited

Building Self-Evolving Agents via Experience-Driven Lifelong Learning: A Framework and Benchmark

Yuxuan Cai, Yipeng Hao, Jie Zhou +14

As AI advances toward general intelligence, the focus is shifting from systems optimized for static tasks to creating open-ended agents that learn continuously. In this paper, we i…