Mohit Bansal

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Hao TanAdobe ResearchVerified email at adobe.com
Jie Lei 雷杰Research Scientist, Meta AIVerified email at fb.com
Jaemin ChoPhD Student at UNC Chapel HillVerified email at cs.unc.edu
Peter HaseResident, AnthropicVerified email at anthropic.com
Tamara L BergAssociate Professor, Computer Science, UNC Chapel HillVerified email at cs.unc.edu
Yixin NieMeta, UNC Chapel HillVerified email at meta.com
Licheng Yu 虞立成Research Scientist and Manager, Facebook AIVerified email at fb.com
Kevin GimpelQuillBotVerified email at ttic.edu
Colin RaffelUniversity of Toronto, Vector Institute and Hugging FaceVerified email at cs.toronto.edu
Shiyue ZhangBloombergVerified email at cs.unc.edu
Swarnadeep SahaResearch Scientist, FAIR at MetaVerified email at meta.com
Karen LivescuTTI-ChicagoVerified email at ttic.edu
Xiang ZhouGoogleVerified email at cs.unc.edu
Matthew R. WalterToyota Technological Institute at ChicagoVerified email at ttic.edu
Adyasha MaharanaUniversity of North Carolina, Chapel HillVerified email at cs.unc.edu
Jialu LiUNC Chapel HillVerified email at cs.unc.edu
Zineng TangUC BerkeleyVerified email at cs.unc.edu
Heng JiProfessor, Siebel School of Computing and Data Science, AICE Director, UIUC, Amazon ScholarVerified email at illinois.edu
Han GuoMITVerified email at mit.edu
Douwe KielaContextual AI, Stanford UniversityVerified email at stanford.edu

Mohit Bansal

Parker Distinguished Professor, Computer Science, UNC Chapel Hill

Verified email at cs.unc.edu - Homepage

Natural Language Processing Computer Vision Machine Learning Multimodal AI


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
LXMERT: Learning Cross-Modality Encoder Representations from Transformers H Tan, M Bansal EMNLP 2019, 2019	2871	2019
End-to-end Relation Extraction using LSTMs on Sequences and Tree Structures M Miwa, M Bansal ACL 2016, 2016	1611	2016
Beyond the imitation game: Quantifying and extrapolating the capabilities of language models A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ... arXiv preprint arXiv:2206.04615, 2022	1300	2022
Adversarial NLI: A New Benchmark for Natural Language Understanding Y Nie, A Williams, E Dinan, M Bansal, J Weston, D Kiela ACL 2020, 2019	1011	2019
MAttNet: Modular Attention Network for Referring Expression Comprehension L Yu, Z Lin, X Shen, J Yang, X Lu, M Bansal, TL Berg CVPR 2018, 2018	926	2018
Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning H Liu, D Tam, M Muqeeth, J Mohta, T Huang, M Bansal, C Raffel NeurIPS 2022, 2022	855	2022
Towards Universal Paraphrastic Sentence Embeddings J Wieting, M Bansal, K Gimpel, K Livescu ICLR 2016, 2015	750	2015
Less is More: ClipBERT for Video-and-Language Learning via Sparse Sampling J Lei, L Li, L Zhou, Z Gan, TL Berg, M Bansal, J Liu CVPR 2021, 2021	747	2021
Fast Abstractive Summarization with Reinforce-Selected Sentence Rewriting YC Chen, M Bansal ACL 2018, 2018	747	2018
TVQA: Localized, Compositional Video Question Answering J Lei, L Yu, M Bansal, TL Berg EMNLP 2018, 2018	718	2018
Unifying Vision-and-Language Tasks via Text Generation J Cho, J Lei, H Tan, M Bansal ICML 2021, 2021	574	2021
How Much Can CLIP Benefit Vision-and-Language Tasks? S Shen, LH Li, H Tan, M Bansal, A Rohrbach, KW Chang, Z Yao, ... ICLR 2022, 2021	460	2021
Dynabench: Rethinking Benchmarking in NLP D Kiela, M Bartolo, Y Nie, D Kaushik, A Geiger, Z Wu, B Vidgen, G Prasad, ... NAACL 2021, 2021	426	2021
Tailoring Continuous Word Representations for Dependency Parsing M Bansal, K Gimpel, K Livescu ACL 2014, 2014	388	2014
VL-Adapter: Parameter-Efficient Transfer Learning for Vision-and-Language Tasks YL Sung, J Cho, M Bansal CVPR 2022, 2022	377	2022
Learning to Navigate Unseen Environments: Back Translation with Environmental Dropout H Tan, L Yu, M Bansal NAACL 2019, 2019	360	2019
Combining fact extraction and verification with neural semantic matching networks Y Nie, H Chen, M Bansal Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 6859-6866, 2019	343	2019
Evaluating Explainable AI: Which Algorithmic Explanations Help Users Predict Model Behavior? P Hase, M Bansal ACL 2020, 2020	341	2020
What to talk about and how? Selective Generation using LSTMs with Coarse-to-Fine Alignment H Mei, M Bansal, MR Walter NAACL 2016, 2016	335	2016
From Paraphrase Database to Compositional Paraphrase Model and Back J Wieting, M Bansal, K Gimpel, K Livescu TACL 2015, 2015	327	2015

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