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AI Video Papers·2026
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The Past Frames the Future: Memory for Autoregressive Video Generation

Harold Haodong Chen, Rongjin Guo +23·HKUST, CityUHK +14

Surveys memory mechanisms for autoregressive video generation, framing memory as persistent historical information that influences future generation. Organizes work by Forms, Functions, Operations, Learning, and Evaluation, and synthesizes challenges for long-horizon consistency and memory-aware learning.

#video#ai-video#long-horizon#retrieval#evaluation+3
AI Agent Papers·2026
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Qwen-Planner-Agent: A Closed-Loop AI-for-AI Framework for Real-World Mobile Planner Agents

Tingyu Qu, Weigao Sun +24·Alibaba Group, Alibaba Token Hub +1

A mobile-planning agent paper that develops a closed-loop AI-for-AI lifecycle to generate data, train a planner model, and co-evolve a runtime Harness for multi-app task execution. Demonstrates top performance on MobilePA-Bench with improved tool use, memory, skill coordination and low estimated per-task output cost.

#qwen#ai-agent#agent-skills#mobile#benchmarks+3
AI Agent Papers·2026
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IterSynth: Rethinking Deep Search Agents via Role-Decoupled Iterative Synthesis

Xingyu Wu, Yuchen Yan +10·Zhejiang University, Tencent

Alternates a Planner (issues sub-queries) and a Synthesizer (integrates retrieved evidence into a persistent summary) to tackle long-horizon deep-search; introduces Role‑Decoupled Policy Optimization (RDPO) for role-specific RL credit assignment and shows strong results (IterSynth-8B reaches 50.7% on five benchmarks).

#ai-agent#long-horizon#RL#benchmarks#llm+4
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