Welcome 👏🏻

Welcome to the official website of LiLab, founded and directed by Dr. Irene Li at the University of Tokyo. 

LiLab is an independent research group, established on February 14, 2023. LiLab specializes in research in Artificial Intelligence (AI), Machine Learning (ML), and Natural Language Processing (NLP). 

Our current projects include medical text processing, LLM text generation, medical question answering, LLMs for education, explainable AI, and NLP applications, such as recommendation systems. Please check our publications.

💡We welcome collaborators from diverse backgrounds and areas. 

⭐️We are actively looking for research assistants and potential collaborators to join our lab for collaboration. If you are interested in working as a postdoc, please contact us. 

📪 Please contact Irene via ireneli[at]ds.itc.u-tokyo.ac.jp. 

News 📣🥳 🤗🙌

[2024-11-9] We received 5k USD credits from Google - [Gemma Academic Program for JP/KR 2024] Program!

[2024-11-5] Our special issue, Advances in Large Language Models for Biological and Medical Applications received the first submission! 

[2024-10-26] Our special issue, Advances in Large Language Models for Biological and Medical Applications with Big Data and Cognitive Computing, is open for submission! 

[2024-11-9] We received 5k USD credits from Google - [Gemma Academic Program for JP/KR 2024] Program!

[2024-10-10]  EARL workshop schedule is out! Looking forward to seeing you at RecSys 2024!

[2024-9-20] We received the ActX grant from JST!

[2024-9-13] Our paper, Enhancing Diagnostic Accuracy through Multi-Agent Conversations: Using Large Language Models to Mitigate Cognitive Bias, is accepted by JMIR!

[2024-9-9] Dr. Li is invited as a guest editor on Big Data and Cognitive Computing.

[2024-7-22] We received sponsorship from Baidu, Inc., and Smartor, Inc. for the EARL workshop at RecSys 2024! The submission link is open! 

[2024-7-21] We received an additional 10k USD credits from the Academic Program GCP Credit Award from Google!

[2024-7-16]  Our paper, RecPrompt: A Prompt Tuning Framework for News Recommendation Using Large Language Models, is accepted by CIKM 2024! 

[2024-7-16]  Our paper, Ascle: A Python Natural Language Processing Toolkit for Medical Text Generation, is accepted by JMIR!

[2024-7-5]  Our paper, Topic-Centric Explanations for News Recommendation, is accepted by ACM Transactions on Recommender Systems 2024!

[2024-5-16] 3 papers, including workshops, are accepted by ACL 2024, check our publication page!

[2024-4-12] We received 10k USD credits from the Academic Program GCP Credit Award from Google!

[2024-3-30] We received the KAKEN grant from JSPS! 

[2024-3-25] Our workshop proposal, EARL, was accepted by RecSys 2024! 

[2024-1-18] Our paper, Better Explain Transformers by Illuminating Important Information, is accepted by EACL 2024!

[2023-10-10] Dr. Li was interviewed by Nature - Featured News!