Michael Tang @_michaeltang_
post-training / prev @princeton michaeltang.xyz san francisco Joined March 2013-
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Excited to share what friends and I have been working on at @Standard_Kernel We've raised from General Catalyst (@generalcatalyst), Felicis (@felicis), and a group of exceptional angels. We have some great H100 BF16 kernels in pure CUDA+PTX, featuring: - Matmul 102%-105% perf…
VideoGameBench full release! now has metrics 👀
VideoGameBench full release! now has metrics 👀
I love this project
If you're at NeurIPS, stop by our workshop oral! @GraceLiu78 will be presenting on single-goal contrastive RL at 2:45-3pm on Sun 12/15, don't miss it :) imol-workshop.github.io/pages/program/
👀
Presenting USACO at @COLM_conf, reach out to chat about anything coding, agents, test-time methods, or other nlp / rl topics :)
"Next frame prediction achieves a PSNR of 29.4, comparable to lossy JPEG compression." 😮
"Next frame prediction achieves a PSNR of 29.4, comparable to lossy JPEG compression." 😮
Next-gen evals should be interactive 👀 • Long-horizon env interaction tests realistic planning (SWEBench, WebShop) • Human interaction draws out hidden capabilities (USACO human-in-loop) • Multi-turn interaction with a bad actor better captures the surface area for attacks
Next-gen evals should be interactive 👀 • Long-horizon env interaction tests realistic planning (SWEBench, WebShop) • Human interaction draws out hidden capabilities (USACO human-in-loop) • Multi-turn interaction with a bad actor better captures the surface area for attacks
fast edit 👀
Excited about more robust repository-level code evals!
Excited about more robust repository-level code evals!
I'm excited to share recent work with @GraceLiu78 and @_michaeltang_ on exploration in RL! A Single Goal is All You Need: Skills and Exploration Emerge from Contrastive RL without Rewards, Demonstrations, or Subgoals Paper, code, and videos: graliuce.github.io/sgcrl/ A thread.
ben wrote up extended thoughts on gpt4 attempting usaco with human-in-the-loop! trajectories contain lots of insights, incl. a recurring issue where the model identifies a bug while reflecting but its code revision then fails to fix it 👀
ben wrote up extended thoughts on gpt4 attempting usaco with human-in-the-loop! trajectories contain lots of insights, incl. a recurring issue where the model identifies a bug while reflecting but its code revision then fails to fix it 👀
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