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Pushpak Bhattacharyya

ACL 2026×3社会与人本对齐与偏好效率与系统推理安全
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0 一作 · 3 篇 · ACL 2026

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2026 顶会论文

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

Looking at Radiology Report Generation through a Causal Lens: A Survey

Satyam Kumar · Kaustubh Shivshankar Shejole · Pushpak Bhattacharyya

摘要

Automatic radiology report generation (RRG) has emerged as a promising approach to reduce clinicians’ workload, yet existing systems are vulnerable to biases induced by spurious correlations across data, models, and evaluation pipelines. Such biases raise serious fairness concerns and may adverse...

社会与人本对齐与偏好效率与系统OpenReview 项目页
作者位次 #2/2ACL 2026Findings· Findings of ACL

Rethinking Research on Stereotypes: An Analysis through Social Psychological and Computational Perspectives

Kaustubh Shivshankar Shejole · Pushpak Bhattacharyya

摘要

Stereotypes are social constructs shaping human perception and behavior that can produce harmful outcomes under specific conditions. Recent work shows that large language models (LLMs) may inherit and amplify such social harms. However, most existing research often focuses only upon stereotypical...

社会与人本推理安全OpenReview 项目页
作者位次 #5/5ACL 2026Findings· Findings of ACL

C a RVE : Critiquing and Refining Visual Elaborations for Figurative Language Illustrations

Manishit Kundu · Tejomay Kishor Padole · Sumit Shekhar · Biplab Banerjee · Pushpak Bhattacharyya

摘要

Illustrating figurative language remains challenging due to its non-literal semantics, and existing text-to-image frameworks rely heavily on proprietary models or human supervision to achieve adequate alignment. We introduce CaRVE, a lightweight and fully open-source critique-driven framework tha...

多模态对齐与偏好评测与基准OpenReview 项目页

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