Papers by Anurag Gupta
Model Editing at Scale leads to Gradual and Catastrophic Forgetting (2024.findings-acl)
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| Challenge: | Existing model editing methods are evaluated using metrics for reliability, specificity and generalization over one or few edits. |
| Approach: | They evaluate model editing methods for three crucial properties - editing proficiency, fact forgetting and downstream performance. |
| Outcome: | The proposed methods are based on two state-of-the-art models - ROME and MEMIT. |
Information Extraction from Visually Rich Documents using LLM-based Organization of Documents into Independent Textual Segments (2025.acl-long)
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| Challenge: | Specialized non-LLM NLP-based solutions lack reasoning and are not able to infer values not explicitly present in documents. |
| Approach: | They propose a novel LLM-based approach that organizes VRDs into localized semantic textual segments called semantic blocks. |
| Outcome: | The proposed approach outperforms the state-of-the-art on public VRD benchmarks by 1-3% in F1 scores and is resilient to document formats previously not encountered. |
MedTutor: A Retrieval-Augmented LLM System for Case-Based Medical Education (2025.emnlp-demos)
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Dongsuk Jang, Ziyao Shangguan, Kyle Tegtmeyer, Anurag Gupta, Jan T Czerminski, Sophie Chheang, Arman Cohan
| Challenge: | Existing educational tools for medical residents are time-consuming and inconsistent. |
| Approach: | They propose a system that generates educational content and multiple-choice questions from clinical case reports and a pipeline that takes clinical case report input and produces targeted educational materials. |
| Outcome: | The system generates educational content and multiple-choice questions from clinical case reports and synergizes with local knowledge base to ensure it is foundationally sound and current. |