The Language Understanding and Knowledge Acquisition (LUKA) Lab is directed by Dr. Muhao Chen. Our research focuses on robust and accountable machine learning methods for natural language understanding, structured data processing, and knowledge acquisition from unstructured data. We are also interested in knowledge-driven intelligent systems that handle interdisciplinary tasks (for example, biology, medicine, software engineering, and geoinformatics). Our long-term goal is to develop robust, generalizable and minimally supervised knowledge-aware learning systems that help machines understand nature.
We are looking for several new Ph.D. students to join the lab. Prospective students please read this.
We have 7 papers accepted to ACL 2023. Congratulations to all the authors, especially to Tanay and Shudi who are undergraduate lead-authors to two of those.
Congratulations to our first two PhD graduates, Ehsan and Wenxuan, for passing their dissertation defense.
We will give a tutorial about "Indirectly Supervised Natural Language Processing" at ACL 2023.
We are delighted to receive the Amazon Research Award for our research on faithful information extraction.
We have 6 long papers accepted to EMNLP 2022. (Also check out our recent AACL papers)
We have received a Cisco Faculty Award to support our research on robust knowledge extraction.)
We will present 7 long papers at NAACL 2022 (incl. 4 main, 2 findings and 1 TACL). See you in Seattle. (Also check out our recent ACL and ICLR papers)
We have a new paper on indirect supervision accepted to TACL. Congratulations to the great work by our undergraduate scholar Bangzheng.
We will give a tutorial about "New Frontiers in Information Extraction" at NAACL 2022.
We have 6 long papers accepted to EMNLP 2021. Also check out our new ACL papers.
We have received the NSF CRII Award that will support our research on transferable representation learning.
We have two upcoming tutorials at ACL 2021 and KDD 2021.
Our group website is online.