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Junchao Wu

ACL 2026×2ICLR 2026可解释性对齐与偏好多模态强化学习与后训练数据与预训练
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一作贡献30
核心/参与17
方向广度13
合作网络12
1 一作 · 3 篇 · ACL 2026 / ICLR 2026

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2026 顶会论文

3
作者位次 #3/5ACL 2026Poster· Natural Language Processing

Understanding and Mitigating Political Stance Cross-topic Generalization in Large Language Models

Jiayi Zhang · Shu Yang · Junchao Wu · Derek F. Wong · Di Wang

摘要

Fine-tuning Large Language Models on a political topic will significantly manipulate their political stance on various issues and unintentionally affect their stance on broad topics. While previous studies have proposed this issue, there is still a lack of understanding regarding the internal rep...

可解释性强化学习与后训练数据与预训练OpenReview 项目页
一作ACL 2026Poster· Natural Language Processing

D etect RL - X : Towards Reliable Multilingual and Real-World LLM -Generated Text Detection

Junchao Wu · Yefeng Liu · Chenyu Zhu · Hao Zhang · Zeyu Wu · Tianqi Shi · Yichao Du · Longyue Wang · Weihua Luo · Jinsong Su · Derek F. Wong

摘要

The effective detection and governance of Large Language Model (LLM) generated content has become increasingly critical due to the growing risk of misuse. Despite the impressive performance of existing detectors, their reliability and potential in multilingual, real-world scenarios remain largely...

评测与基准多语言与语言学社会与人本OpenReview 项目页

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