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AI Agent Papers·2026
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AREX-2: Advancing Self-Improving Agents through Long-Horizon Reflective Tasks

Hongjin Qian, Chaofan Li +12·Beijing Academy of Artificial Intelligence (BAAI)

Defines and evaluates AREX-2, an LLM agent that iteratively self-improves at test time via reflection and long-horizon execution. Trained on long-horizon improvement trajectories from ML engineering and algorithmic programming (built on Qwen3.8-27B), it scales with more rounds and achieves strong benchmark scores.

#agent-skills#long-horizon#qwen#LLM#benchmarks+3
AI Video Papers·2026
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Beyond the Timeline: Augmenting Long-Video Memory with Grounded Entity Biographies

Hui Ren, Lei Fan +6·University of Illinois Urbana-Champaign, Amazon.com, Inc.

Groups visually grounded appearances of the same physical instance into persistent, retrievable “biographies” so agents can follow objects across hours or days for long-video question answering. Links identity-aware observations to episodic context and visual evidence; improves EgoLifeQA to 72.0% and increases evidence-window reach from 37.6% to 58.9%.

#video#vision#multimodal#long-horizon#retrieval+2
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