Papers by Debanjana Kar

2 papers
ArgGen: Prompting Text Generation Models for Document-Level Event-Argument Aggregation (2022.findings-aacl)

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Challenge: Existing discourse-level information extraction tasks are extractive in nature, but extracting information from larger bodies of discourse-like documents requires more natural language understanding and reasoning capabilities.
Approach: They propose a conditional text generation approach which generates consolidated event-arguments at a document-level with minimal loss of information.
Outcome: The proposed approach generates document-level argument spans in a low-resource and zero-shot setting and can be leveraged in other related multilingual text generation tasks.
MathBuddy: A Multimodal System for Affective Math Tutoring (2025.emnlp-demos)

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Challenge: Existing LLM-based conversational systems do not take into account the student’s affective states.
Approach: They propose an emotionally aware LLM-powered math tutor that models student emotions and maps them to relevant pedagogical strategies.
Outcome: The proposed model improves student engagement and learning effectiveness by 23 points using win rate and 3 points at an overall level using DAMR scores.

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