- LOB-Bench: Orderbook Generative Model Evaluation Benchmark
A review of LOB-Bench, focusing on why generated order book models need rollout-level evaluation beyond one-step loss and stylized facts.
6 min - SFT Memorizes, RL Generalizes
A review of SFT Memorizes, RL Generalizes, focusing on how supervised finetuning and verifier-based reinforcement learning behave under shifted rules and visual inputs.
5 min - Beyond Defaults: Is Noise Conditioning Necessary for Diffusion Models?
A review of recent research that challenges the necessity of noise level conditioning in generative models, exploring alternative approaches to denoising and flow matching.
1 min - PinT algorithms for Diffusion Models
A review of researches that accelerate diffusion models in wall clock time by parallelization.
1 min - Test-time scaling in Diffusion Models
A review of researches that explore test-time scaling for diffusion models.
1 min - Video Diffusion Models as World Simulators
A review of Oasis: A Universe in a transformer, and Diffusion Forcing: Next-token Prediction Meets Full-Sequence Diffusion
4 min - Controllabilities in Video Diffusion Models
A review of papers that add controllabilities to video generation (DragNUWA and Boximator)
1 min - Designing Diffusion Models in Real World
Elucidating the Design Space of Diffusion-Based Generative Models, focusing on the rationale behind its engineering details.
8 min
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