Papers by Debdeep Sanyal

2 papers
Nine Ways to Break Copyright Law and Why Our LLM Won’t: A Fair Use Aligned Generation Framework (2025.findings-emnlp)

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Challenge: Large language models (LLMs) often risk copyright infringement by reproducing protected content verbatim or with insufficient transformative modifications.
Approach: They propose a legally-grounded framework to align LLM outputs with fair-use doctrine . LAW-LM uses a dataset containing 18,000 expert-validated examples .
Outcome: The proposed framework aligns outputs with fair-use doctrine and is validated by 18,000 experts.
Investigating Pedagogical Teacher and Student LLM Agents: Genetic Adaptation Meets Retrieval-Augmented Generation Across Learning Styles (2025.emnlp-main)

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Challenge: Existing models for large language models neglect comprehensive student modeling beyond basic knowledge states and lack mechanisms for teachers to dynamically adapt their approach based on student feedback and collective performance.
Approach: They propose a framework that integrates LLM-based diverse student agents with a self-evolving teacher agent to optimize teacher's pedagogical parameters based on simulated student performance.
Outcome: The proposed framework integrates diverse student agents with a self-evolving teacher agent to optimize teacher pedagogical parameters based on simulated student performance.

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