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Topic · 28 recaps
Reasoning
Methods that improve how language models think through problems — chain-of-thought, search, verification, and the reasoning-trained model families that have emerged since o1-style training.
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Sliding-window beats linear attention
Inference Optimization · Aug 28
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Fast Weight Attention for Continual Learning
LLM Training · Aug 27
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Graph Engineering in the Era of LLM Agents: From Individual Intelligence to System Intelligence
Agents · Aug 21
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Learn What's Left, Not What's Mastered: Saturation Aware Advantage Reweighting for Multi-Reward Policy Optimization
Reasoning · Aug 17
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BDH-CQ: In-Context Learning with Recurrent Latent Reasoning
Inference Optimization · Aug 10
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On-Policy Self-Distillation without Any Supervision
LLM Training · Aug 9
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ABSeeker: Training Long-Horizon Search Agents via Answer-Backtracked Credit Assignment
Agents · Aug 5
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Deferred Exposure of Future Trajectories for Verifiable Reasoning in Autonomous Driving VLMs
Agents · Aug 3
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DAPD: Dual-Anchored Policy Distillation
LLM Training · Aug 3
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PhiZero: A World Model Built Around Physical Language
Diffusion · Jul 30
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