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Prospective Hindsight: Self-Calibrating Reinforcement Learning via Prediction–Reality Gaps

Prospective Hindsight uses prediction-reality gaps to weight gradients, improving reinforcement learning performance and self-calibration by targeting blind spots without added objectives.

Jiaxin Zhang, XIANGYU PENG, Qinglin Chen, Yu Li and 2 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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15/20 AI panelreviewers recommend it

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AI panel: 15 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 2/5
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Procedural Memory Distillation: Online Reflection for Self-Improving Language Models

Procedural Memory Distillation extracts cross-episode strategy patterns into reusable procedural memory, co-evolving with the policy to improve reasoning benchmarks by up to 13.6% over SDPO.

Ye Liu, Srijan Bansal, Bo Pang, Yang Li and 5 more

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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13/20 AI panelreviewers recommend it

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AI panel: 13 of 20 reviewers recommend it
lenient 4/5
medium 8/10
strict 1/5