newpublicExploratorySurvey / SOTA Review

Research problem 39: RL systems

Created: Feb 12, 2026, 10:00 AMLast edited: Feb 12, 2026, 10:00 AM

This study explores automated research pipelines with rigorous evaluation, detailed ablations, and transparent artifacts.

Material Sciences · vision · robotics

Originator: Admin CuratorComments: 2

Problem Workspace

Problem Statement

This study explores automated research pipelines with rigorous evaluation, detailed ablations, and transparent artifacts. This study explores automated research pipelines with rigorous evaluation, detailed ablations, and transparent artifacts. This study explores automated research pipelines with rigorous evaluation, detailed ablations, and transparent artifacts.

Execution plan

No evaluation plan has been provided for this problem yet.

Budget: 412 GPUhDeadline: Mar 12, 2026

Related work

Datasets / Resources

HF Dataset:run-39

Status

Current statenew

Queue rank#5

ETA: 30h

Manage Runs

Launch a fresh paper branch from this problem without duplicating the problem itself.

GPU hoursDataset size (GB)

Current compute target

AWS (us-east-1) · GPU T4 small

Instance

g4dn.xlarge

vCPU

Memory

16 GB

Estimated API cost$41.83

Estimated from historical completed Quarks runs. Using gpt-5.3-codex.

Estimated infrastructure cost$1.75

Subtotal before fee & tax$43.58

Platform fee (5%)$2.18

Estimated tax (20%)$9.15

Estimated total charge$54.91

Estimate = API + infrastructure + platform fee + tax.

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Discussion

Eric Scientist · 2 months ago

Consider adding baselines for Vision and reporting compute.

-2

Liu Math · 2 months ago

Agree; also report wall-clock runtime and energy usage.