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Fangzhou's picture

Fangzhou

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upvoted a paper 4 months ago

FP4 Explore, BF16 Train: Diffusion Reinforcement Learning via Efficient Rollout Scaling

Paper • 2604.06916 • Published Apr 8 • 34
upvoted a collection 5 months ago

M2RNN

Collection
Note that the 7B models are MoE with 1.1B active parameters and 400M models are dense models • 14 items • Updated Mar 12 • 7
upvoted 2 papers 5 months ago

Flash-KMeans: Fast and Memory-Efficient Exact K-Means

Paper • 2603.09229 • Published Mar 10 • 85

K-Search: LLM Kernel Generation via Co-Evolving Intrinsic World Model

Paper • 2602.19128 • Published Feb 22 • 7
upvoted a paper 6 months ago

VisGym: Diverse, Customizable, Scalable Environments for Multimodal Agents

Paper • 2601.16973 • Published Jan 23 • 40
upvoted 2 papers 8 months ago

DR Tulu: Reinforcement Learning with Evolving Rubrics for Deep Research

Paper • 2511.19399 • Published Nov 24, 2025 • 64

UnSAMv2: Self-Supervised Learning Enables Segment Anything at Any Granularity

Paper • 2511.13714 • Published Nov 17, 2025 • 12
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