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Add autoresearch run ledger: EXPERIMENTS/FINDINGS/leaderboard + raw train-eval logs
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| # research-github report (2026-07-12) | |
| ## TIER 1 — canonical drop-in reward functions | |
| 1. **Cosine length-scaled reward** (Yeo 2502.03373, open-r1 `get_cosine_scaled_reward`, also in trl.rewards): | |
| progress=len/max_len; reward=min_v+0.5(max_v−min_v)(1+cos(progress·π)). Correct: 0.5..1.0 (shorter→1.0); | |
| wrong: SWAPPED −1.0..−0.5 (longer wrong penalized LESS → preserves exploration). One-diff. | |
| 2. **Kimi-1.5 min-max linear len_reward** (open-r1 rewards.py; GSM8K fork kithib/ReDit/grpo_gsm8k.py): | |
| λ=0.5−(len−min)/(max−min) per batch; correct→λ, wrong→min(0,λ). No hyperparams. | |
| 3. **DAPO soft overlong punishment** (2503.14476, trl `get_soft_overlong_punishment`): zero until | |
| max−cache, linear to −1 at cap. + `GRPOConfig(mask_truncated_completions=True, loss_type="dapo", | |
| epsilon_high=0.28, beta=0.0)`. GSM8K scale: max=1024, cache=256. | |
| ## TRL native: no built-in length penalty; knobs = mask_truncated_completions, scale_rewards, max_completion_length. | |
| ## TIER 2 — hard numbers | |
| - **Fast-Math-R1** (analokmaus/kaggle-aimo2-fast-math-r1, 2507.08267): SFT→GRPO, cosine+len+format | |
| reward forcing boxed answer BEFORE </think> + stop at </think>. AIME24: +1.1pt @ −25% tokens (32k budget), | |
| +5.7pt @ −17% tokens (16k). Trick: regex `^.*?\boxed{...}.*?</think>` + early stop kills post-answer rambling. | |
| - **ReBalance** (yu-lin-li/ReBalance, ICLR26): naive length penalties cause "underthinking"; | |
| measure length reduction SEPARATELY for correct vs incorrect. | |
| ## TIER 3 — awesome lists: hemingkx/Awesome-Efficient-Reasoning, Eclipsess/Awesome-Efficient-Reasoning-LLMs, | |
| DevoAllen/Awesome-Reasoning-Economy-Papers. Families: long2short distillation (Kimi), difficulty→budget | |
| scheduler, staged ctx curriculum 8K→16K→32K. | |
| ## Recommended single diff | |
| correctness + cosine_scaled(max_len≈256-512) + mask_truncated_completions=True; add repetition_penalty_reward | |
| guard (n-gram repetition is the known hack response to length shaping). | |