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20242026
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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.AI2026

FutureWorld: A Live Reinforcement Learning Environment for Predictive Agents with Real-World Outcome Rewards

Zhixin Han, Yanzhi Zhang, Chuyang Wei +11

Live future prediction refers to the task of making predictions about real-world events before they unfold. This task is increasingly studied using large language model-based agent…

cs.AI2026

Harnessing Pre-Resolution Signals for Future Prediction Agents

Chuyang Wei, Maohang Gao, Zhixin Han +12

Many high-stakes decisions depend on forecasts made before outcomes are known. In this future prediction setting, the central challenge is that public evidence evolves over time, w…

cs.AI2026

Can a Lightweight Automated AI Pipeline Solve Research-Level Mathematical Problems?

Lve Meng, Weilong Zhao, Yanzhi Zhang +2

Large language models (LLMs) have recently achieved remarkable success in generating rigorous mathematical proofs, with "AI for Math" emerging as a vibrant field of research (Ju et…