MaxProof: How MiniMax M3 Reaches Gold-Level Proof Scores
MaxProof turns MiniMax-M3 into a generator, verifier, fixer, and ranker; with population-level test-time scaling it reports 35/42 on IMO 2025 and 36/42 on USAMO 2026.
Institution
Tsinghua University
Leading Chinese research university; its AI groups drive work in deep generative models, diffusion, and machine learning.
Long Context · Tsinghua University
LongTraceRL: Harder Distractors and Rubric Rewards for Long-Context RL
Tsinghua's LongTraceRL mines distractors from real search-agent trajectories and adds entity-level rubric rewards, lifting a Qwen3-4B reasoner from 53.3 to 59.0 average across five long-context benchmarks (+5.7).
Reinforcement Learning · Tsinghua University
CHERRL: A Controlled Sandbox for Reward Hacking in Rubric RL
CHERRL injects four known judge biases to reliably reproduce reward hacking in rubric RL; an agent reading only training logs pinned the onset with 11-step total interval error and missed none of six runs.
Echo-Infinity: Learnable Evolving Memory for 24-Hour Real-Time Video
Echo-Infinity is an autoregressive video model with a learnable evolving memory that compresses any-length history at constant cost, hitting 24-hour rollouts (over 1.3M frames) in real time at 18.5 FPS on an H100.
Robotics · Tsinghua University
Humanoid-GPT: A GPT-Style Transformer for Humanoid Motion Tracking
Humanoid-GPT treats humanoid control like language modeling: a causal Transformer distilled from ~384 PPO experts on a 2-billion-frame corpus, 200x prior data. It hits 92.58 percent sim success, under 1.5ms.
Diffusion Models · Tsinghua University
Causal Forcing++: Few-Step Autoregressive Diffusion for Real-Time Video
Causal Forcing++ distills bidirectional video diffusion into a 1-2 step frame-wise autoregressive generator at 14.1 FPS, halves first-frame latency, and cuts few-step training cost ~4x (11,600 to 2,900 A800 GPU hours).