| 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 | 47 | 2022 |
| Weakly-Supervised Visual-Retriever-Reader for Knowledge-based Question Answering M Luo, Y Zeng, P Banerjee, C Baral EMNLP 517, 6417–6431, 2021 | 47 | 2021 |
| 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 | 25 | 2022 |
| Improving Biomedical Information Retrieval with Neural Retrievers M Luo, A Mitra, T Gokhale, C Baral AAAI 2022, 2022 | 25 | 2022 |
| Dr. ICL: Demonstration-Retrieved In-context Learning M Luo, X Xu, Z Dai, P Pasupat, M Kazemi, C Baral, V Imbrasaite, VY Zhao R0-FoMo: Robustness of Few-shot and Zero-shot Learning in Large Foundation …, 2023 | 18 | 2023 |
| 'Just because you are right, doesn't mean I am wrong': Overcoming a Bottleneck in the Development and Evaluation of Open-Ended Visual Question Answering (VQA) Tasks M Luo, SK Sampat, R Tallman, Y Zeng, M Vancha, A Sajja, C Baral EACL 240, 2766–2771, 2021 | 17 | 2021 |
| BioTABQA: Instruction Learning for Biomedical Table Question Answering M Luo, S Saxena, S Mishra, M Parmar, C Baral CEUR Workshop 2022, 2022 | 14 | 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 | 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 | 8 | 2022 |
| Improving Contrastive Learning with Model Augmentation Z Liu, Y Chen, J Li, M Luo, PS Yu, C Xiong arXiv preprint arXiv:2203.15508, 2022 | 8 | 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 | 7 | 2020 |
| End-to-end Knowledge Retrieval with Multi-modal Queries M Luo, Z Fang, T Gokhale, Y Yang, C Baral ACL 2023, 2023 | 6 | 2023 |
| In-context Learning with Retrieved Demonstrations for Language Models: A Survey M Luo, X Xu, Y Liu, P Pasupat, M Kazemi arXiv preprint arXiv:2401.11624, 2024 | 4 | 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 | 4 | 2021 |
| Strong equivalence for LPMLN programs J Lee, M Luo ICLP 2019, 2019 | 4 | 2019 |
| 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, 2023 | 3 | 2023 |
| Can NLP Models Correctly Reason Over Contexts that Break the Common Assumptions? N Varshney, M Parmar, N Patel, D Handa, S Sarkar, M Luo, C Baral arXiv preprint arXiv:2305.12096, 2023 | 3 | 2023 |
| 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 | 3 | 2022 |
| Self-supervised Learning for Sequential Recommendation with Model Augmentation Z Liu, Y Chen, J Li, M Luo, SY Philip, C Xiong | 3 | 2021 |
| Neural Retriever and Go Beyond: A Thesis Proposal M Luo Proceedings of the 2022 Conference of the North American Chapter of the …, 2022 | 2 | 2022 |
Chitta BaralProfessor of Computer Science, Arizona State UniversityVerified email at asu.edu
