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Unsupervised approach for inducing dialogue schemas from domain-specific conversations. This repository houses the source code and research findings from the application of cutting-edge NLP and ML techniques to dialogue systems.

  • Updated May 27, 2023
  • Python

This repository explores the use of advanced sequence-to-sequence networks and transformer models, such as BERT, BART, PEGASUS, and T5, for summarizing multi-text documents in the medical domain. It leverages extensive datasets like CORD-19 and a Biomedical Abstracts dataset from Hugging Face to fine-tune these models.

  • Updated May 17, 2024
  • Jupyter Notebook

An end-to-end pipeline for adapting FLAN-T5 for dialogue summarization, exploring the full spectrum of modern LLM tuning. Implements and compares Full Fine-Tuning, PEFT (LoRA), and Reinforcement Learning (RLHF) for performance and alignment. Features a PPO-tuned model to reduce toxicity, in-depth analysis notebooks, and interactive Streamlit demo.

  • Updated Aug 4, 2025
  • Jupyter Notebook

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