Tianxiao Li
Orcid: 0000-0002-9147-7511Affiliations:
- NEC Laboratories America, Machine Learning Department, Irving, TX, USA
- Yale University, Department of Molecular Biophysics & Biochemistry, New Haven, CT, USA
According to our database1,
Tianxiao Li
authored at least 15 papers
between 2020 and 2025.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
-
on linkedin.com
-
on orcid.org
On csauthors.net:
Bibliography
2025
MKG-Rank: Enhancing Large Language Models with Knowledge Graph for Multilingual Medical Question Answering.
CoRR, March, 2025
Exploring the Role of Knowledge Graph-Based RAG in Japanese Medical Question Answering with Small-Scale LLMs.
Proceedings of the First International Workshop on Improving Healthcare with Small Language Models co-located with 23rd International Conference on Artificial Intelligence in Medicine, 2025
Learning Disentangled Equivariant Representation for Explicitly Controllable 3D Molecule Generation.
Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025
2024
A Survey of Generative AI for De Novo Drug Design: New Frontiers in Molecule and Protein Generation.
CoRR, 2024
A survey of generative AI for <i>de novo</i> drug design: new frontiers in molecule and protein generation.
Briefings Bioinform., 2024
2023
Constructing a full, multiple-layer interactome for SARS-CoV-2 in the context of lung disease: Linking the virus with human genes and microbes.
PLoS Comput. Biol., 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
2021
Gene Tracer: a smart, interactive, voice-controlled Alexa skill For gene information retrieval and browsing, mutation annotation and network visualization.
Bioinform., 2021
Unsupervised Cross-Domain Prerequisite Chain Learning using Variational Graph Autoencoders.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021
2020
What are We Depressed about When We Talk about COVID19: Mental Health Analysis on Tweets Using Natural Language Processing.
CoRR, 2020
Latent-space embedding of expression data identifies gene signatures from sputum samples of asthmatic patients.
BMC Bioinform., 2020
Bioinform., 2020
What Are We Depressed About When We Talk About COVID-19: Mental Health Analysis on Tweets Using Natural Language Processing.
Proceedings of the Artificial Intelligence XXXVII, 2020