Papers by Avijit Mitra

3 papers
Synth-SBDH: A Synthetic Dataset of Social and Behavioral Determinants of Health for Clinical Text (2025.emnlp-main)

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Challenge: Existing SBDH datasets lack detailed annotations and are limited in their availability and coverage.
Approach: They propose a synthetic SBDH annotation dataset with detailed SBDH status, temporal information, and rationale across 15 categories.
Outcome: The proposed dataset outperforms models with no Synth-SBDH training on three tasks using real-world clinical datasets from two distinct hospital settings.
Generating Contextual Images for Long-Form Text (2024.lrec-main)

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Challenge: Recent advances in Text-to-Image models require short prompts that describe both the content and style of the target image.
Approach: They propose to use Large Language Models (LLMs) and Text-to-Image Models to synthesize relevant visual imagery from generic long-form text.
Outcome: The proposed models can generate high-quality images from short prompts that describe both the content and style of the target image.
Knowledge Injected Prompt Based Fine-tuning for Multi-label Few-shot ICD Coding (2022.findings-emnlp)

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Challenge: Existing methods for ICD coding are limited due to the high-dimensional space of multi-label assignment and the long-tail challenge.
Approach: They propose a prompt-based fine-tuning technique with label semantics to solve this challenge.
Outcome: The proposed method outperforms state-of-the-art methods on a benchmark dataset of code assignment in 14.5% of cases.

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