collaborators

28 papers

cs.LG2026

AI4AI at Test-Time: Strong-to-Weak Capability Transfer via Harnesses

Cheng Qian, Wenting Zhao, Liangwei Yang +6

Recent work on distillation transfers the capabilities of large models to smaller ones often by updating the latter's parameters, through teacher forcing, on-policy distillation, a…

cs.CL2026

Webscale-RL: Automated Data Pipeline for Scaling RL Data to Pretraining Levels

Zhepeng Cen, Haolin Chen, Shiyu Wang +8

Large Language Models (LLMs) have achieved remarkable success through imitation learning on vast text corpora, but this paradigm creates a training-generation gap and limits robust…

cs.HC2026

RealUserSim: Bridging the Reality Gap in Agent Benchmarking via Grounded User Simulation

Ming Zhu, Juntao Tan, Rithesh Murthy +6

LLM-based user simulation is the primary mechanism for end-to-end agent evaluation, yet simulated users are poor proxies for real humans: unconstrained LLM defaults produce a Forma…

cs.SD2026

Building Enterprise Realtime Voice Agents from Scratch: A Technical Tutorial

Jielin Qiu, Zixiang Chen, Liangwei Yang +11

We present a technical tutorial for building enterprise-grade realtime voice agents from first principles. While end-to-end speech-to-speech models may ultimately provide the best…

cs.AI2026

LiveAgentBench: Comprehensive Benchmarking of Agentic Systems Across 104 Real-World Challenges

Hao Li, Huan Wang, Jinjie Gu +3

As large language models grow more capable, general AI agents have become increasingly prevalent in practical applications. However, existing benchmarks face significant limitation…

cs.SD2026

VoiceAgentRAG: Solving the RAG Latency Bottleneck in Real-Time Voice Agents Using Dual-Agent Architectures

Jielin Qiu, Jianguo Zhang, Zixiang Chen +12

We present VoiceAgentRAG, an open-source dual-agent memory router that decouples retrieval from response generation. A background Slow Thinker agent continuously monitors the conve…