Papers by Krishna Patel

2 papers
Bias after Prompting: Persistent Discrimination in Large Language Models (2025.findings-emnlp)

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Challenge: a dangerous assumption is that biases do not transfer from pre-trained large language models to adapted models.
Approach: They validate the bias transfer hypothesis by using prompt adaptations to study biases in causal models . they find that popular prompt-based mitigation methods do not consistently prevent biase transferring .
Outcome: The results invalidate the assumption that biases do not transfer from pre-trained models to adapted models.
Scaling Text-Rich Image Understanding via Code-Guided Synthetic Multimodal Data Generation (2025.acl-long)

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Challenge: Vision-language models struggle to understand text-rich images due to the scarcity of diverse text-only large language data.
Approach: They propose a framework that leverages the coding capabilities of text-only large language models to create synthetic text-rich multimodal data.
Outcome: The proposed framework can generate high-quality instruction-tuning data using Python, HTML, LaTeX and other languages.

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