LAUNCH = LAnguage Understanding and generatioN researCH
The LAUNCH lab aims to build efficient and robust Natural Language Processing (NLP) models to extract knowledge from large-scale texts as well as teach machines to talk and write like humans do. Our goal is to make machines more intelligent through creating natural language understanding and generation tools.
Our lab has active projects in summarizing documents of various domains and genres, generating text with complex narratives, characterizing human arguments and reasoning process, extracting fine-grained opinions from user-generated content, and solving interdisciplinary challenges in computational social science and AI for education.
We can be found on Twitter as @launchnlp.
📋 If you're interested in joining the LAUNCH lab for research projects, please check out this page.
[November 2023] Received grants from LG AI and Cisco to work on "Effective and Fine-grained Feedback for Enhanced Language Model Reasoning and Alignment" and "Multi-Document Reasoning with Large Language Models".
[July 2023] Received a grant from NSF to work on "Argument Graph Supported Multi-Level Approach for Argumentative Writing Assistance".
[Feb 2023] Check out our new preprint on multi-hop question answering using large language models (LLMs).
[Nov 2022] Check out our recent work on entity-to-entity stance detection, multimodal ideological content analysis, media bias study, time-aware prompting for generation, and generative models for aspect-based sentiment analysis.
[Aug 2022] Received a grant from LG AI Research to work on "Knowledge-grounded Scientific Reasoning".
[May 2022] Received a grant from AFOSR to work on "Computational Modeling of Narrative Representation, Shaping, and Influence". CSE news
[Mar 2022] Check out our recent work on long document summarization with hierarchical question-summary pairs and efficient structure extraction methods for argument mining.
[Feb 2022] Welcome Winston Wu to join the lab as Postdoc researcher. He will work on cross culture narrative understanding (together with Rada Mihalcea) and media content analysis.