collaborators

16 papers

cs.LG2026

MERA: Model Evolution and Routing with Skill Adaptation for Agentic Systems at Scale

Yuhang Yao, Zeyu Wang, Wanyi Chen +8

LLM agents execute heterogeneous sequences of model calls within a single task: some invocations require careful reasoning, while others are structured steps such as formatting or…

cs.MA2026

Symphony-Coord: Adaptive Routing for Multi-Agent LLM Systems

Zhaoyang Guan, Huixi Cao, Ming Zhong +6

Multi-agent large language model systems can tackle complex multi-step tasks by decomposing work and coordinating specialized behaviors. However, current coordination mechanisms ty…

cs.LG2026

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning

Jingwei Song, Meng Chen, Jie Xiao +15

Reinforcement learning (RL) is a critical stage in post-training large language models (LLMs), involving repeated interaction between rollout generation, reward evaluation, and cen…

cs.LG2026

TwinRouterBench: Fast Static and Live Dynamic Evaluation for Realistic Agentic LLM Routing

Pei Yang, Wanyi Chen, Tongyun Yang +14

LLM routing matters most in long-horizon applications such as coding agents, deep research systems, and computer-use agents, where a single user request triggers many model calls.…

cs.LG2026

MARS: Unleashing the Power of Speculative Decoding via Margin-Aware Verification

Jingwei Song, Xinyu Wang, Hanbin Wang +6

Speculative Decoding (SD) accelerates autoregressive large language model (LLM) inference by decoupling generation and verification. While recent methods improve draft quality by t…

cs.CL2026

EVM-QuestBench: An Execution-Grounded Benchmark for Natural-Language Transaction Code Generation

Pei Yang, Wanyi Chen, Ke Wang +3

Large language models are increasingly applied to various development scenarios. However, in on-chain transaction scenarios, even a minor error can cause irreversible loss for user…