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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.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.LG2026

AOI: Turning Failed Trajectories into Training Signals for Autonomous Cloud Diagnosis

Pei Yang, Wanyi Chen, Asuka Yuxi Zheng +11

Large language model (LLM) agents offer a promising data-driven approach to automating Site Reliability Engineering (SRE), yet their enterprise deployment is constrained by three c…

cs.LG2026

Implicit Strategic Optimization: Rethinking Long-Horizon Decision-Making in Adversarial Poker Environments

Boyang Xia, Weiyou Tian, Qingnan Ren +7

Training large language model (LLM) agents for adversarial games is often driven by episodic objectives such as win rate. In long-horizon settings, however, payoffs are shaped by l…