Towards Looped Models Done Right, Part II: Rethinking at Fixed Points
Fixed-point behavior connects KV sharing, state reuse, and distilled prefill in looped language models. We review the savings and accuracy trade-offs demonstrated on…
Reinforcement Learning
6 pages
TRACE: Rollout-Guided Quantization-Aware Training for FP4 Reinforcement Learning of MoE Language Models
TRACE: Rollout-Aligned FP4 Quantization-Aware Training — MoE LLM RL at BF16 Quality, up to 5.4x Faster TL;DR In reinforcement learning (RL) for MoE LLMs, quantizing…
On-Policy or Off-Policy Learning? A Systematic Study of Distillation Dynamics
On-Policy Is Not a Panacea: The Real Protagonists of Rollout Policy, KL Direction, and Learning Rate in Distillation Dynamics TL;DR — When we separate on-policy (OnPD)…
StepAudio 3 Gen Technical Report
StepAudio 3 Gen: Unifying Speech, Song, Music, and Sound Effects with a Single Discrete Autoregressive (RVQ) Model TL;DR StepAudio 3 Gen, released by StepFun, is a fully…
Miles v0.1: Production-Level Post-Training
Miles v0.1: A "verified, clean, and scalable" full-stack system for frontier RL post-training TL;DR: Miles is a full-stack RL post-training framework that resolves the…
Online Draft Co-Training for Speculative Decoding in Large-Scale, Long-Context RL Post-Training
Two Designs That Make Speculative Decoding Practical for Large-Scale, Long-Context RL Post-Training TL;DR : Rollout generation dominates the wall-clock time of RL…