collaborators

11 papers

cs.LG2026

AdaFlash: Adaptive Speculative Decoding via On-Policy Distilled Diffusion Drafters

Yu-Yang Qian, Hao-Cong Wu, Chen Chen +4

Speculative decoding, in which a lightweight draft model first generates a draft sequence that is then verified in parallel by the target model, has become a prevalent paradigm for…

cs.NI2026

vLLM Semantic Router: Signal Driven Decision Routing for Mixture-of-Modality Models

Xunzhuo Liu, Huamin Chen, Samzong Lu +30

As large language models (LLMs) diversify across modalities, capabilities, and cost profiles, the problem of intelligent request routing: selecting the right model for each query a…

cs.LG2026

Where Hindsight Credit Can Reside: A Signed-Capacity View of Token Updates in RLVR

Yuhang He, Haodong Wu, Siyi Liu +7

Reinforcement Learning with Verifiable Rewards (RLVR) improves the reasoning ability of Large Language Models (LLMs), but sparse outcome rewards make token-level credit assignment…

cs.AI2026

UniToolCall: Unifying Tool-Use Representation, Data, and Evaluation for LLM Agents

Yijuan Liang, Xinghao Chen, Yifan Ge +5

Tool-use capability is a fundamental component of LLM agents, enabling them to interact with external systems through structured function calls. However, existing research exhibits…

cs.CL2026

C-ReD: A Comprehensive Chinese Benchmark for AI-Generated Text Detection Derived from Real-World Prompts

Chenxi Qing, Junxi Wu, Zheng Liu +5

Recently, large language models (LLMs) are capable of generating highly fluent textual content. While they offer significant convenience to humans, they also introduce various risk…

cs.AI2026

Alignment Imprint: Zero-Shot AI-Generated Text Detection via Provable Preference Discrepancy

Junxi Wu, Kailin Huang, Dongjian Hu +4

Detecting AI-generated text is an important but challenging problem. Existing likelihood-based detection methods are often sensitive to content complexity and may exhibit unstable…