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Tzu-Quan Lin

ACL 2026×2多模态长上下文与架构可解释性强化学习与后训练社会与人本
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1 一作 · 2 篇 · ACL 2026

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2026 顶会论文

2
一作ACL 2026Poster· Natural Language Processing

An Exploration of Mamba for Speech Self-Supervised Models

Tzu-Quan Lin · Heng-Cheng Kuo · Tzu-Chieh Wei · Hsi-Chun Cheng · Chun Wei Chen · Hsien-Fu Hsiao · Yu Tsao · Hung-yi Lee

摘要

While Mamba has demonstrated strong performance in language modeling, its potential as a speech self-supervised learning (SSL) model remains underexplored, with prior studies limited to isolated tasks. To address this, we explore Mamba-based HuBERT models as alternatives to Transformer-based SSL...

长上下文与架构可解释性多模态OpenReview 项目页
作者位次 #4/7ACL 2026Findings· Findings of ACL

P seudo2 R eal: Task Arithmetic for Pseudo-Label Correction in Automatic Speech Recognition

Yi-Cheng Lin · Yu-Hsuan Li Liang · Hsuan Su · Tzu-Quan Lin · Shang-Tse Chen · Yun-Nung Chen · Hung-yi Lee

摘要

Robust ASR under domain shift is crucial because real-world systems encounter unseen accents and domains with limited labeled data. Although pseudo-labeling offers a practical workaround, it often introduces systematic, accent-specific errors that filtering fails to fix. We ask: How can we correc...

多模态强化学习与后训练社会与人本OpenReview 项目页

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