Zhichao Yang
Orcid: 0000-0002-2797-4257Affiliations:
- University of Massachusetts Amherst, MA, USA
According to our database1,
Zhichao Yang
authored at least 30 papers
between 2018 and 2024.
Collaborative distances:
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Bibliography
2024
BioInstruct: instruction tuning of large language models for biomedical natural language processing.
J. Am. Medical Informatics Assoc., 2024
RiTeK: A Dataset for Large Language Models Complex Reasoning over Textual Knowledge Graphs.
CoRR, 2024
MCQG-SRefine: Multiple Choice Question Generation and Evaluation with Iterative Self-Critique, Correction, and Comparison Feedback.
CoRR, 2024
MedQA-CS: Benchmarking Large Language Models Clinical Skills Using an AI-SCE Framework.
CoRR, 2024
JMLR: Joint Medical LLM and Retrieval Training for Enhancing Reasoning and Professional Question Answering Capability.
CoRR, 2024
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024
README: Bridging Medical Jargon and Lay Understanding for Patient Education through Data-Centric NLP.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024
Do Clinicians Know How to Prompt? The Need for Automatic Prompt Optimization Help in Clinical Note Generation.
Proceedings of the 23rd Workshop on Biomedical Natural Language Processing, 2024
NoteChat: A Dataset of Synthetic Patient-Physician Conversations Conditioned on Clinical Notes.
Proceedings of the Findings of the Association for Computational Linguistics, 2024
Proceedings of the 6th Clinical Natural Language Processing Workshop, 2024
UMass-BioNLP at MEDIQA-M3G 2024: DermPrompt - A Systematic Exploration of Prompt Engineering with GPT-4V for Dermatological Diagnosis.
Proceedings of the 6th Clinical Natural Language Processing Workshop, 2024
2023
README: Bridging Medical Jargon and Lay Understanding for Patient Education through Data-Centric NLP.
CoRR, 2023
Do Physicians Know How to Prompt? The Need for Automatic Prompt Optimization Help in Clinical Note Generation.
CoRR, 2023
SELF-EXPLAIN: Teaching Large Language Models to Reason Complex Questions by Themselves.
CoRR, 2023
NoteChat: A Dataset of Synthetic Doctor-Patient Conversations Conditioned on Clinical Notes.
CoRR, 2023
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023
Vision Meets Definitions: Unsupervised Visual Word Sense Disambiguation Incorporating Gloss Information.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023
UMASS_BioNLP at MEDIQA-Chat 2023: Can LLMs generate high-quality synthetic note-oriented doctor-patient conversations?
Proceedings of the 5th Clinical Natural Language Processing Workshop, 2023
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
Enhancing the prediction of disease outcomes using electronic health records and pretrained deep learning models.
CoRR, 2022
Associations Between Natural Language Processing (NLP) Enriched Social Determinants of Health and Suicide Death among US Veterans.
CoRR, 2022
An Automatic SOAP Classification System Using Weakly Supervision And Transfer Learning.
CoRR, 2022
Context Variance Evaluation of Pretrained Language Models for Prompt-based Biomedical Knowledge Probing.
CoRR, 2022
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022
Extracting Biomedical Factual Knowledge Using Pretrained Language Model and Electronic Health Record Context.
Proceedings of the AMIA 2022, 2022
2020
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020
2019
Computer-aided industrial development path optimization: a case from "Optics Valley of China".
Clust. Comput., 2019
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019
2018