| Weakly-Supervised Visual-Retriever-Reader for Knowledge-based Question Answering M Luo, Y Zeng, P Banerjee, C Baral EMNLP 517, 6417–6431, 2021 | 72 | 2021 |
| In-BoXBART: Get Instructions into Biomedical Multi-Task Learning M Parmar, S Mishra, M Purohit, M Luo, MH Murad, C Baral NAACL 2022 Finding, 2022 | 66 | 2022 |
| In-context Learning with Retrieved Demonstrations for Language Models: A Survey M Luo, X Xu, Y Liu, P Pasupat, M Kazemi TMLR, 2024 | 40 | 2024 |
| Improving Biomedical Information Retrieval with Neural Retrievers M Luo, A Mitra, T Gokhale, C Baral AAAI 2022, 2022 | 39 | 2022 |
| Dr. ICL: Demonstration-Retrieved In-context Learning M Luo, X Xu, Z Dai, P Pasupat, M Kazemi, C Baral, V Imbrasaite, VY Zhao Data Intelligence, 2024, 2024 | 38 | 2024 |
| Generalized but not Robust? Comparing the Effects of Data Modification Methods on Out-of-Domain Generalization and Adversarial Robustness T Gokhale, S Mishra, M Luo, BS Sachdeva, C Baral ACL 2022 Finding, 2022 | 31 | 2022 |
| Choose Your QA Model Wisely: A Systematic Study of Generative and Extractive Readers for Question Answering M Luo, K Hashimoto, S Yavuz, Z Liu, C Baral, Y Zhou SpaNLP ACL 2022 Workshop, 2022 | 27 | 2022 |
| A large language model–based generative natural language processing framework fine‐tuned on clinical notes accurately extracts headache frequency from electronic health records CC Chiang, M Luo, G Dumkrieger, S Trivedi, YC Chen, CJ Chao, ... Headache: The Journal of Head and Face Pain 64 (4), 400-409, 2024 | 25 | 2024 |
| LogicBench: Towards systematic evaluation of logical reasoning ability of large language models M Parmar, N Patel, N Varshney, M Nakamura, M Luo, S Mashetty, A Mitra, ... Proceedings of the 62nd Annual Meeting of the Association for Computational …, 2024 | 19 | 2024 |
| Towards LogiGLUE: A Brief Survey and A Benchmark for Analyzing Logical Reasoning Capabilities of Language Models M Luo, S Kumbhar, M Shen, M Parmar, N Varshney, P Banerjee, S Aditya, ... arXiv preprint arXiv:2310.00836, 2024 | 19 | 2024 |
| End-to-end Knowledge Retrieval with Multi-modal Queries M Luo, Z Fang, T Gokhale, Y Yang, C Baral ACL 2023, 2023 | 19 | 2023 |
| ‘Just because you are right, doesn’t mean I am wrong’: Overcoming a bottleneck in development and evaluation of Open-Ended VQA tasks M Luo, SK Sampat, R Tallman, Y Zeng, M Vancha, A Sajja, C Baral Proceedings of the 16th Conference of the European Chapter of the …, 2021 | 19* | 2021 |
| Improving Contrastive Learning with Model Augmentation Z Liu, Y Chen, J Li, M Luo, PS Yu, C Xiong arXiv preprint arXiv:2203.15508, 2022 | 17 | 2022 |
| BioTABQA: Instruction Learning for Biomedical Table Question Answering M Luo, S Saxena, S Mishra, M Parmar, C Baral CEUR Workshop 2022, 2022 | 14 | 2022 |
| Can Open-Domain QA Reader Utilize External Knowledge Efficiently like Humans? N Varshney, M Luo, C Baral arXiv preprint arXiv:2211.12707, 2022 | 10 | 2022 |
| Can Transformers Reason About Effects of Actions? P Banerjee, C Baral, M Luo, A Mitra, K Pal, TC Son, N Varshney arXiv preprint arXiv:2012.09938, 2020 | 9 | 2020 |
| A Study on the Efficiency and Generalization of Light Hybrid Retrievers M Luo, S Jain, A Gupta, A Einolghozati, B Oguz, D Chatterjee, X Chen, ... ACL 2023, 2022 | 7 | 2022 |
| Assessing Empathy in Large Language Models with Real-World Physician-Patient Interactions M Luo, CJ Warren, L Cheng, HM Abdul-Muhsin, I Banerjee IEEE Big Data Conference 2025, 2024 | 5 | 2024 |
| Refining Text-to-Image Generation: Towards Accurate Training-Free Glyph-Enhanced Image Generation S Lakhanpal, S Chopra, V Jain, A Chadha, M Luo WACV 2025 conference, 2024 | 5 | 2024 |
| A Simple Approach to Jointly Rank Passages and Select Relevant Sentences in the OBQA Context M Luo, S Chen, C Baral Proceedings of the 2022 Conference of the North American Chapter of the …, 2021 | 5 | 2021 |
Chitta BaralProfessor of Computer Science, Arizona State UniversityEmail verificata su asu.edu