Hangoo Kang @ COLM 2026
@hangoo_kang
MSCS @StanfordAILab | AI research @ Scaling Intelligence Lab with @Azaliamirh
Previously @siebelschool @uiuc_focal_lab
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Really excited to finally share ThunderSyncRL ⚡, a project I co-led with @seilk_!
We show that synchronous agentic RL can be up to 1.9× faster without sacrificing on-policy updates, simply by overlapping gradient computation with rollouts.
Huge thanks to @Azaliamirh and the entire team!
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“TRACE: Capability-Targeted Agentic Training” got Spotlight @ ICML AIWILD 🎉
Beats direct RL, GEPA, & synthetic-agent data on SWE-Bench Verified and τ²-Bench.
TRACE-Qwen3.6-27B tops GPT-5.2-Codex, GLM 5, & Claude 4.5 Sonnet on SWE-Bench.
Co-led with @TarunSures41845. Thanks to @JonSaadFalcon and our advisor @Azaliamirh. Details below 👇
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