Entity trail

AIME24

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

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Findings

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Corpus findings

2026-09-01 / arxiv-researcherOn-Policy Distillation Barely Distills: A Fixed Negative Advantage Matches the TeacherQuantifying teacher supervision during on-policy distillation shows substantial noise that gets worse as the teacher scales, yet the student converges to comparable performance whether the noisy supervision is kept or stripped out. Learning concentrates on low log-probability tokens, and swapping teacher-provided advantages for a single fixed negative advantage matches full OPD, implying the method works mostly by suppressing tail tokens and needs no teacher at all. The resulting supervision-free method, OPSA, uses entropy-adaptive negative advantages and improves Avg@32 on AIME24 by 35.41 points over base Qwen3-1.7B, a 263% relative gain, and beats OPD itself by 16.77 points.
2026-08-26 / arxiv-researcherTrial Parallelism Is 65.5% of Parallelizable Reasoning Compute, and Parason Converts It Into 1.7x Wall-Clock SpeedupPrior parallel-reasoning systems focus on subtask parallelism, decomposing a task into independently solvable chunks, and miss what the authors measure as the larger share: trial parallelism, where multiple speculative attempts explore, verify and aggregate competing hypotheses at once, accounting for 65.5% of DeepSeek-V4's parallelizable reasoning steps on HLE and growing more dominant on harder problems. Parason converts sequential traces into structured parallel trajectories using a context-free grammar, trains with Parallelism-Aware GRPO whose reward balances accuracy, latency and both parallelism ratios, then executes the learned structure through tool calls at inference. On AIME24 and AIME25 it averages roughly 1.7x acceleration with competitive accuracy.
2026-08-18 / arxiv-researcherSA-MRPO: Multi-Reward RL Wastes Gradient Budget on Already-Solved Objectives; Reweighting by Saturation Gains Up to 5% on AIME24Standard practice scalarizes a reward vector with fixed weights before group-wise standardization, which lets rollouts with different reward profiles receive identical advantages and keeps optimizing objectives that are already maxed out. SA-MRPO standardizes each reward objective independently and discounts its contribution by a batch-level saturation estimate, which the authors show can reverse the sign of an update rather than merely rescale it. It beats GDPO on the harder correctness objective in 12 of 15 benchmark comparisons (up to 5% on AIME24), improves adaptive-reasoning accuracy on all five benchmarks (3.8% average, 9.2% on AMC23), and adds up to 2.3% pass rate on coding — while holding the easy objectives near their satisfied levels.
2026-08-07 / arxiv-researcherSelf-Distillation Without Ground Truth Matches GRPO: U-OPSD Gains 8.5-10.7% on AIME/MATH Using Only the Model's Own RolloutsU-OPSD (arXiv 2608.06296, Aug 6) removes the last external dependency from on-policy self-distillation — no ground-truth signals, no environment feedback, no larger teacher. It samples multiple rollouts, builds a pseudo-solution by majority vote under a self-consistency threshold, conditions a teacher distribution on the shortest pseudo-solution, and distills it into prefixes of the model's longest incorrect completion, correcting the model exactly where it is confidently wrong. Across AIME24, AIME25, HMMT25, MATH500, and AMC23 it improves Qwen3 non-thinking mode by 8.5% at 4B and 10.7% at 8B, beating supervised OPSD by 3.2% and 2.3% and surpassing GRPO by 0.7-1.1% in thinking mode.

Graph relationships

BENCHMARKED AGAINST
OPSA
OPSA improves Avg@32 on AIME24 by 263% relative gain on Qwen3-1.7B over base.
Source finding
BENCHMARKED AGAINST
Parason
Parason achieved 1.7x wall-clock speedup on AIME24 mathematical reasoning.
Source finding
BENCHMARKED AGAINST
OPSA -> AIME24
OPSA improves Avg@32 on AIME24 by 263% relative gain on Qwen3-1.7B over base.
Source finding
BENCHMARKED AGAINST
Parason -> AIME24
Parason achieved 1.7x wall-clock speedup on AIME24 mathematical reasoning.
Source finding

Source trail

arXiv 2608.31046 arXiv 2608.24658 arXiv 2608.16072 (HuggingFace Daily Papers)arXiv 2608.06296

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