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Xiaoting Wu

ACL 2026×3ICLR 2026对齐与偏好评测与基准多模态社会与人本推理
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一作贡献30
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合作网络3
1 一作 · 4 篇 · ACL 2026 / ICLR 2026

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2026 顶会论文

4
一作ACL 2026Poster· Natural Language Processing

Thinking Alignment of Scenario-Oriented User Simulation

Xiaoting Wu · Yi Huang · Chunyang Gao · Mengfei Guo · Jingyu Yao · Junlan Feng

摘要

Existing user simulators based on prompting to role-play or SFT are generally confined to imitating users’ textual utterances, without adequately considering the multi-faceted cognitive processes that underlie human decision-making during interactions. To facilitate better alignment with real hum...

社会与人本推理对齐与偏好OpenReview 项目页
作者位次 #4/5ACL 2026Findings· Findings of ACL

Beyond Static Profiles: Capturing the Fluidity of User Preferences in Diverse Scenarios

Chunyang Gao · Yi Huang · Jingyu Yao · Xiaoting Wu · Junlan Feng

摘要

Despite the remarkable evolution of Large Language Models (LLMs) from simple assistants to versatile agents, effective personalization remains a significant challenge. Existing approaches often treat user preferences as static or merely time-varying traits, overlooking the dynamic nature of human...

对齐与偏好评测与基准智能体与工具OpenReview 项目页
作者位次 #5/6ACL 2026Findings· Findings of ACL

A Learnable Skill Combination Strategy for Multi-task Learning in Natural Language Understanding

ZHE YANG · Yi Huang · Yaqin Chen · Mengfei Guo · Xiaoting Wu · Junlan Feng

摘要

In the realm of domain-specific natural language understanding (NLU) tasks, acquiring high-quality labeled data is often arduous, thereby posing significant challenges for effective model training. Multi-task learning (MTL) addresses these limitations by jointly optimizing multiple tasks within a...

可解释性评测与基准数据与预训练OpenReview 项目页

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