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Yang Zhao

ACL 2026×2ICLR 2026推理强化学习与后训练多模态理论与学习动力学可解释性
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0 一作 · 3 篇 · ACL 2026 / ICLR 2026

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2026 顶会论文

3
作者位次 #3/4ACL 2026Poster· Natural Language Processing

DART : Disambiguation-Aware Reasoning for Video-guided Machine Translation

Boyu Guan · Chuang Han · Yang Zhao · Chengqing Zong

摘要

Video-guided Machine Translation (VMT) seeks to enhance translation quality by incorporating contextual information derived from paired short video clips. However, many VMT samples are text-sufficient; even when visual information is needed, only minimal cues are required. Aiming to tackle these...

多模态推理强化学习与后训练OpenReview 项目页
作者位次 #5/6ACL 2026Findings· Findings of ACL

Decoding the Multimodal Mind: Generalizable Brain-to-Text Translation via Multimodal Alignment and Adaptive Routing

Chunyu Ye · Yunhao Zhang · Jingyuan Sun · Chong Li · Yang Zhao · Shaonan Wang

摘要

Decoding language from the human brain remains a grand challenge for Brain-Computer Interfaces (BCIs). Current approaches typically rely on unimodal brain representations, neglecting the brain’s inherently multimodal processing. Inspired by the brain’s associative mechanisms, where viewing an ima...

多模态可解释性多语言与语言学OpenReview 项目页

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