We started with a surrogate discovery env and foudn that it is excellent and beats pytorch.compile (36x) and trioton.autotune (3x) using a gaussian process optimized by out oracle. Since the oracle was so powerful we used it for generative CUDA kernel optimization wth a online self-improvement loop using unsloth lora and DPO.
Team
Placement
ParticipantKube SRE Gym is a self-improving RL environment where a small language model (Qwen3-1.7B) learns to diagnose and fix real Kubernetes production incidents…
RL environment for autonomous biologist agents. Simulate an entire biological worldstate based on scientifically-accurate single-cell standards. Naive agents…
ShopRLVE-GYM HF Blog https://huggingface.co/blog/thebajajra/shop-rlve-gym
Our agent uses OpenEnv to build a curriculum of video game environments that train a TinyLlama 1.1B agent via GRPO reinforcement learning. We implement three…
GAIA is an OpenEnv-compatible geospatial reasoning environment where an AI agent infers hidden real-world locations using multi-step tool calls (terrain…
Voyager-VRAM is a long-horizon workplace simulator where LLM agents must navigate a realistic office environment ( emails, Slack, shared drive, spreadsheets…
