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Abid Ali

ACL 2026×2多模态对齐与偏好评测与基准可解释性
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2 一作 · 2 篇 · ACL 2026

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2026 顶会论文

2
一作ACL 2026Findings· Findings of ACL

Measuring What Matters Beyond Text: Evaluating Multimodal Summaries by Quality, Alignment, and Diversity

Abid Ali · Diego Molla · Usman Naseem

摘要

Multimodal Large Language Models (MLLMs) have facilitated Multimodal Summarization with Multimodal Output (MSMO), wherein systems generate concise textual summaries accompanied by salient visuals from multimodal sources. However, current MSMO evaluation remains fragmented: text quality, image-tex...

评测与基准多模态对齐与偏好OpenReview 项目页
一作ACL 2026Findings· Findings of ACL

Towards Visually Grounded Multimodal Summarization via Cross-Modal Transformer and Gated Attention

Abid Ali · Diego Molla · Usman Naseem

摘要

Multimodal summarization requires models to jointly understand textual and visual inputs to generate concise, semantically coherent summaries. Existing methods often inject shallow visual features into deep language models, leading to representational mismatches and weak cross-modal grounding. We...

多模态对齐与偏好可解释性OpenReview 项目页

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