Man Luo (罗满)

Ph.D.


About

I am currently an AI Research Scientist at Intel Lab, multimodal cognitive AI team. My research includes Multimodal and language models post-training, Multimodal Retrieval and Generation, Synthetic Data Pipelines, Computer Use Agents, and Multimodal Applications in Healthcare. More details:

  • Knowledge Retrieval: How can we effectively retrieve and utilize external knowledge to not only enhance comprehension but also mitigate hallucination?
  • Generalization: Designing models that can seamlessly adapt and perform across various tasks and domains without explicit training.
  • Multimodal Understanding: Delving into the integration of textual, visual, and other modalities to bolster machine comprehension and response capabilities.
  • Biomedical/healthcare application and innovation: Evaluate and innovate the LLMs to solve biomedical and healthcare challenges, such as long sequence processing, noisy data mitigation, data imbalance rectification, and enhancing interpretability.

Previously, I was a research fellow at Mayo Clinic, AZ, working closely with Dr. Imon Banerjee and Dr. Bhavik Patel. I earned my doctoral degree in 2023 from Arizona State University under the esteemed supervision of Dr. Chitta Baral. I am also privileged to collaborate with amazing industry researchers from Salesforce, Meta and Google during my internship.


News

2025
  • [2025.06]: New paper DPO Learning with LLMs-Judge Signal for Computer Use Agents.
  • [2025.05]: Our paper SK-VQA has been accepted to ICML 2025 Oral Presentation (less than 1%).
  • [2025.05]: Our paper Revolve has been accepted to ICML 2025.
  • [2025.03]: New paper FiVL A Framework for Improved Vision-Language Alignment is out.
2024
  • [2022.12]: 2th O-DRUM Workshop will be back at CVPR 2023 with a new rhythm: Open-Domain *Reasoning* under Multimodal settings.
  • [2022.08]: Start internship at Google Research.
  • [2022.08]: Completed thesis proposal and became Ph.D. candidate.
  • [2022.05]: Start internship at Meta Reality Lab working on efficient retrieval task.
  • [2022.05]: 2 papers accpeted to NAACL 2022 SRW .
  • [2022.04]: 1 paper accpeted to NAACL 2022 Finging.
  • [2022.04]: 1 paper accpeted to ACL 2022 Spa-NLP workshop.
  • [2022.02]: 1 paper accpeted to ACL 2022 Finding.
  • [2022.01]: O-Drum Workshop will be held in CVPR 2022
  • [2021.12]: 1 paper accepted to AAAI 2021. Acceptant rate 15%.
  • [2021.08]: 1 paper accepted to EMNLP 2021.
  • [2021.06]: Yankai Zeng (mentor by me) passed his master thesis and now be a Ph.D. student in UTD.
  • [2021.05]: Research intern at Salesforce and worked with Kazuma Hashimoto and Yingbo Zhou.
  • [2021.04]: Finalist of 2021 Knowledge Mobilization Awards.
  • [2021.03]:Invited talk at exploreCSR workshop (ASU).
  • [2021.02]: 1 paper accepted to EACL 2021.
  • [2019.09]: 1 paper accpeted to ICLP 2019.
  • [2019.09]: Presented at ICLP 2019 Doctoral Consortium
  • [2019.06]: 1 workshop paper accepted to ASPOCP 2019

Professional Activities and Experience

  • Super Volunteer for WiML @NeurIPS 2024.
  • Editor of PLOS Digital Medicine
  • Guest Editor of PLOS Digital Medicine
  • Workshop orginzer for Multimodal4Health 2024
  • Workshop orginzer for O-DRUM 2023, 2022
  • Reviewer for AAAI, NIPS, EMNLP, ACL, EACL

Publications


In-BoXBART: Get Instructions into Biomedical Multi-Task Learning
Mihir Parmar, Swaroop Mishra, Mirali Purohit, Man Luo, M. Hassan Murad, Chitta Baral
NAACL 2022 Finding
[Paper] [Model in Huggingface]

In-context Learning with Retrieved Demonstrations for Language Models: A Survey
Man Luo, Xin Xu, Yue Liu, Panupong Pasupat, Mehran Kazemi
TACL 2024
[Paper]

Improving Biomedical Information Retrieval with Neural Retrievers
Man Luo, Arindam Mitra, Tejas Gokhale, Chitta Baral
AAAI 2022
[Paper]

‘Just because you are right, doesn’t mean I am wrong’: Overcoming a bottleneck in development and evaluation of Open-Ended VQA tasks
Man Luo, Shailaja Keyur Sampat, Riley Tallman, Yankai Zeng, Manuha Vancha, Akarshan Sajja, Chitta Baral
EACL 2021
[Paper] [Code]

Dr. ICL: Demonstration-Retrieved In-context Learning
Man Luo, Xin Xu, Zhuyun Dai, Panupong Pasupat, Mehran Kazemi, Chitta Baral, Vaiva Imbrasaite, Vincent Y Zhao
Data Intelligence Journal 2024
[Paper]

Weakly-Supervised Visual-Retriever-Reader for Knowledge-based Question Answering
Man Luo*, Yankai Zeng*, Pratyay Banerjee, Chitta Baral
EMNLP 2021
[Paper] [Code]