OpenRSI Index

Task

Synthesize RL tasks to further optimize a 122B post-trained model

Generate and select 2,560 verifiable RL tasks in 24 hours to improve Qwen3.5-122B-A10B (already post-trained): 512 each for math, multiple-choice reasoning, instruction following, long context, and coding. Each task needs a prompt and an automatically checkable answer, constraint set, or test suite. The agent may change only the RL task data; the model, GRPO training recipe, and reward rules are fixed.

Result. The Research Agent's data reached 71.51 on the geometric mean of five benchmarks, versus 71.37 for the baseline. Compared with the baseline, coding improved most (+2.45 points); math, instruction following, and long context scored lower.

Evaluation. LiveCodeBench V6 averages 10 generated solutions per problem across 175 problems (1,750 responses) to reduce sampling variance. PolyMath (9,000 items), MMLU-Pro (12,032), IFBench (294), and LongBench V2 (503) use one response per item.

Behaviour. The Research Agent generated arithmetic questions with deliberately similar answer choices, layered writing constraints, long logs, and coding problems, with answers checked by calculations, rules, or tests. It repeatedly sampled the starting model and selected questions that produced both correct and incorrect answers, aiming to provide useful reward contrast. It adjusted noisy small-sample estimates and compared filters for empty or overly long responses. The strategy connects data selection to the training rule.

Kev Decision Architecture

Kev is a Jev-inspired small neural model that makes decisions directly, without generating text. Improve its decision quality and confidence estimates on fixed training data.

Judged on the probabilities assigned to correct decisions, scored absolutely.

Molmo2 Video-Pointing Inference Strategy

Improve how a frozen Molmo2 model points to anomalies in video by tuning which frames it sees, how it is prompted, and how long it can answer.

Judged on mean spatiotemporal pointing soft-F1, scored absolutely.

ACE Playbook Inspection and Repair

Inspect and repair the reusable advice in an ACE playbook so a frozen Qwen model answers Formula reasoning problems more accurately.

Judged on held-out Formula exact-answer accuracy, scored absolutely.

MolmoWeb Interaction Context Allocation

Choose which interaction history, page details, and screenshots a frozen MolmoWeb model sees to improve its next browser-action prediction.

Judged on macro-averaged browser-action prediction quality, scored absolutely.

ReasonIR Difficulty Curriculum

Choose how a fixed pool of easy and hard retrieval examples is weighted and ordered to improve ReasonIR-8B, without weakening its general retrieval ability.

Judged on reasoning-retrieval quality, with a penalty if general retrieval regresses, scored absolutely.

Learnability-Aware Long/Short CoT Adaptation

Adapt the supplied long and short mathematical reasoning examples so the same small language model learns more effectively under a fixed training recipe.

Judged on five-benchmark mathematical-reasoning accuracy, scored absolutely.

MInference 32-Head Sparse Prefill Kernel

Speed up a fixed sparse-attention prefill operator without changing which tokens it attends to or weakening its numerical result.

Judged on paired sparse-prefill speedup, measured against the reference in the same Judge run.