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Language, Information, and Learning at Yale (LILY)

This is the website for the LILY (Language, Information, and Learning at Yale) Lab at the Department of Computer Science, Yale University.


  • Apr. 2021 Our new dataset FeTaQA: Free-form Table Question Answering is released online now. Check it out!
  • Apr. 2021 We updated aan.how, which now has over 16k manually-curated resources on NLP and related topics!
  • Mar. 2021 Three papers accepted to NAACL! Improving Zero and Few-Shot Abstractive Summarization with Intermediate Fine-tuning and Data Augmentation, DART: Open-Domain Structured Data Record to Text Generation, and QMSum: A New Benchmark for Query-based Multi-domain Meeting Summarization!
  • Mar. 2021 Two papers accepted to ICLR! GraPPa: Grammar-Augmented Pre-Training for Table Semantic Parsing and SCoRe: Pre-Training for Context Representation in Conversational Semantic Parsing!

The LILY Lab started in Spring 2017 with Professor Dragomir Radev joining Yale University. Our interests include:

  • Natural Language Processing
    • Information Retrieval
    • Summarization
    • Multilingual Parsing
    • Dialogue Systems
    • Question Answering
    • Humor Detection
  • Machine Learning
    • Neural Networks
    • Semi-supervised Learning