Papers by Anirban Majumder

2 papers
PROTEGE: Prompt-based Diverse Question Generation from Web Articles (2023.findings-emnlp)

Copied to clipboard

Challenge: a popular format for knowledge bases is question-answer pairs (Q&As) specialized knowledge bases that extract and store question-annwer pairs are prevalent .
Approach: They propose a framework for question generation that generates diverse questions from text . they propose 'protege' framework that can generate diverse questions using a variety of prompts .
Outcome: The proposed framework improves diversity and fidelity over diverse beam search and prompt-based baselines on three public Q&A datasets.
PEARL: Preference Extraction with Exemplar Augmentation and Retrieval with LLM Agents (2024.emnlp-industry)

Copied to clipboard

Challenge: Existing systems specialize in extracting customer preferences from standalone queries . absence of a conversational interface often leaves customers feeling the need for humanlike assistance .
Approach: They propose a shopping assistant chatbot that extracts customer preferences as key-value filters from a multi-turn conversation on an e-commerce website.
Outcome: The proposed solution improves performance on exact match by 10% compared to baselines and improves inference latency by 1%.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations