Ruoyu Wang

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upvoted a paper 4 days ago

LEGO-RL: Harness-Native Reinforcement Learning for Coding Agents

Paper • 2608.17393 • Published 6 days ago • 24

authored a paper about 2 months ago

What Makes Interaction Trajectories Effective for Training Terminal Agents?

Paper • 2606.03461 • Published Jun 2 • 3

updated 2 models about 2 months ago

Lego-X/SWE-Review-30B-A3B

Text Generation • 211k • Updated Jul 9 • 98

Lego-X/SWE-Review-8B

Text Generation • 308k • Updated Jul 9 • 350 • 2

updated 2 datasets about 2 months ago

Lego-X/SWE-Review-Traj

Viewer • Updated Jul 9 • 8.91k • 320 • 2

Lego-X/SWE-Review-Bench

Viewer • Updated Jul 9 • 1.38k • 337

upvoted a paper about 2 months ago

What Makes Interaction Trajectories Effective for Training Terminal Agents?

Paper • 2606.03461 • Published Jun 2 • 3

authored a paper about 2 months ago

SWE-Review: Closing the Loop on Issue Resolution with Agentic Code Review

Paper • 2607.06065 • Published Jul 7 • 10

upvoted a paper about 2 months ago

SWE-Review: Closing the Loop on Issue Resolution with Agentic Code Review

Paper • 2607.06065 • Published Jul 7 • 10

submitted a paper to Daily Papers about 2 months ago

SWE-Review: Closing the Loop on Issue Resolution with Agentic Code Review

Paper • 2607.06065 • Published Jul 7 • 10

updated 2 models 3 months ago

Lego-X/SWE-Review-30B-A3B

Text Generation • 211k • Updated Jul 9 • 98

Lego-X/SWE-Review-8B

Text Generation • 308k • Updated Jul 9 • 350 • 2

updated 2 datasets 3 months ago

Lego-X/SWE-Review-Traj

Viewer • Updated Jul 9 • 8.91k • 320 • 2

Lego-X/SWE-Review-Bench

Viewer • Updated Jul 9 • 1.38k • 337

updated a collection 3 months ago

SWE-Review

Collection

SWE-Review: Closing the Loop on Issue Resolution with Agentic Code Review. Benchmark, trajectories, training data, and models for agentic code review. • 4 items • Updated May 13

updated a model 3 months ago

Lego-X/SWE-Review-30B-A3B

Text Generation • 211k • Updated Jul 9 • 98