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Xiaoshuai Song

ACL 2026×2强化学习与后训练评测与基准对齐与偏好推理
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一作贡献30
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合作网络9
1 一作 · 2 篇 · ACL 2026

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2026 顶会论文

2
作者位次 #3/16ACL 2026Poster· Natural Language Processing

S hop S imulator: Evaluating and Exploring RL -Driven LLM Agent for Shopping Assistants

Pei Wang · Yanan Wu · Xiaoshuai Song · Weixun Wang · Gengru Chen · Zhongwen Li · Kezhong Yan · Qi Liu · Ken Deng · Shuaibing Zhao · Shaopan Xiong · Xuepeng Liu · Xuefeng Chen · Wanxi Deng · Wenbo Su · Zerui Huang (Taobao &amp

摘要

Large language model (LLM)-based agents are increasingly deployed in e-commerce shopping. To perform thorough, user-tailored product searches, agents should interpret personal preferences, engage in multi-turn dialogues, and ultimately retrieve and discriminate among highly similar products. Howe...

强化学习与后训练对齐与偏好评测与基准OpenReview 项目页
一作ACL 2026Findings· Findings of ACL

E nv S caler: Scaling Tool-Interactive Environments for LLM Agent via Programmatic Synthesis

Xiaoshuai Song · Haofei Chang · Guanting Dong · Yutao Zhu · Ji-Rong Wen · Zhicheng Dou

摘要

Large language models (LLMs) are expected to be trained to act as agents in various real-world environments, but this process relies on rich and varied tool-interaction sandboxes. However, access to real systems is often restricted; LLM-simulated environments are prone to hallucinations and incon...

强化学习与后训练评测与基准推理OpenReview 项目页

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