1 citations · 2 across the 11 of their papers we have counts for
5 papers · 1 filter
Libra: Efficient Resource Management for Agentic RL Post-Training
Kaiwen Chen, Xin Tan, Jingzong Li +6
Reinforcement learning (RL) has emerged as a standard post-training paradigm for shaping large language models (LLMs) into capable agents. In agentic RL, the rollout stage generate…
GameGen-Verifier: Parallel Keypoint-Based Verification for LLM-Generated Games via Runtime State Injection
Chaobo Jia, Ruipeng Wan, Ting Sun +5
LLM-based game generation promises to turn natural-language specifications into executable games, but progress is limited by the lack of reliable automated verification. Unlike con…
Frontier: Simulating the Next Generation of LLM Inference Systems
Yicheng Feng, Xin Tan, Kin Hang Sew +3
Large Language Model (LLM) inference is growing increasingly complex with the rise of Mixture-of-Experts (MoE) models and disaggregated architectures that decouple components like…
ReasonCache: Accelerating Large Reasoning Model Serving through KV Cache Sharing
Kaiwen Chen, Xin Tan, Minchen Yu +2
Large Reasoning Models (LRMs) are becoming integral to many AI inference systems, enhancing their capabilities with advanced reasoning. However, deploying these models in productio…
Echo: Simulating Distributed Training At Scale
Yicheng Feng, Yuetao Chen, Kaiwen Chen +7
Simulation offers unique values for both enumeration and extrapolation purposes, and is becoming increasingly important for managing the massive machine learning (ML) clusters and…