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Shu-Qi Gu

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#artificial intelligence Preprint Sep 2026

ARISE: Adapting to Evolving Capability Gaps in Agentic Reinforcement Learning

Adaptive Rubric-Skill Co-Evolution (ARISE), a reinforcement learning framework that uses rollout evidence to continually adapt evaluation criteria, exploration guidance, and training priorities, and demonstrates that ARISE successfully enhances both overall task performance and training efficiency.

Kun Feng, Yu-Chen Fang, Yih-Yang Tan et al. · 0 citations

KairosAgent: Agentic Time Series Forecasting with Fused Semantic Reasoning

KairosAgent, a novel agentic framework for multimodal time series forecasting, including an LLM-based reasoner and a TSFM-based forecaster, unifies textual reasoning and numerical forecasting by dynamically invoking analytical tools to enhance the numerical understanding and semantic reasoning capabilities of LLMs.

Kun Feng, Ziwei Shan, Yu-Chen Fang et al. · 5 citations · ⚡1
#computer vision Preprint Aug 2026

AVA-Encoder: Towards Agent-Native Video Representation Learning

The Agentic Video Auto-Encoder (AVA-Encoder), a novel auto-encoding framework driven by agentic self-evolution to learn agent-native video representations that outperforms a carefully human-tuned policy while using 74.3% fewer shot-level and keyframe-level system-prompt tokens.

Chuyue Li, Jinpeng Yu, Hao-Zhe Wang et al. · 1 citation

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