Papers by Palash Nandi

3 papers
MMAC: A Multilingual, Multimodal Alignment Framework for Cultural Grounding Evaluation (2026.acl-long)

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Challenge: Existing models lack cultural alignment across modalities and languages . a new framework to assess cultural awareness across linguistics and languages is needed .
Approach: They propose a framework that integrates tri-modally aligned cultural benchmarks and a five-dimensional evaluation protocol to assess cross-country awareness disparities.
Outcome: The proposed framework assesses cultural awareness disparities across modalities and languages . it is the first dataset aligned at the input level across text, image, and speech .
SABER: Uncovering Vulnerabilities in Safety Alignment via Cross-Layer Residual Connection (2025.emnlp-main)

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Challenge: Large Language Models (LLMs) with safe-alignment training are vulnerable to jailbreak attacks, causing malicious users to generate harmful outputs.
Approach: They propose a safe-alignment jailbreak method that bypasses the middle-to-late layers of large language models by a residual connection.
Outcome: The proposed method improves by 51% over the best performing baseline GCG on HarmBench test set.
Recent Advances in Online Hate Speech Moderation: Multimodality and the Role of Large Models (2024.findings-emnlp)

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Challenge: HS is any communication demeaning a person or a group based on social or ethnic characteristics that undermines social harmony and individual safety . the recent Israel-Hamas conflict has escalated both anti-Muslim and anti-Semitic sentiments worldwide .
Approach: They examine the role of large language models and large multimodal models in HS moderation . they examine how text, images, and audio interact to spread hate speech .
Outcome: The findings highlight the need for solutions in low-resource settings and highlight the gaps in existing methods.

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