2 citations · 5 across the 6 of their papers we have counts for
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cs.AI2026
Self-Evolving Agent Harness
Chuyang Wei, Haoxiang Guan, Minghang Zhu +5
Harness self-evolution revises an agent's software scaffolding, including prompts, memory, workflows, and executable components, while keeping model weights fixed. We formalize a f…
cs.AI2026
ZGCM-1: A Fully Open and Extremely Efficient Foundation Model for Math and Agentic Search
Jiyan He, Guang Liang, Hao Liu +19
In this work, we present ZGCM-1, a fully open 7B dense foundation model trained from scratch with extreme data, system, and algorithmic efficiency. ZGCM-1 is founded on a core prem…
cs.AI2023★ 2 cited
Confucius: Iterative Tool Learning from Introspection Feedback by Easy-to-Difficult Curriculum
Shen Gao, Zhengliang Shi, Minghang Zhu +6
Augmenting large language models (LLMs) with external tools has emerged as a promising approach to extending the capability of LLMs. Although some works employ open-source LLMs for…