Hritik Bansal
Hritik Bansal
University of California Los Angeles | Indian Institute of Technology Delhi
Verified email at - Homepage
Cited by
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An improved sex-specific and age-dependent classification model for Parkinson's diagnosis using handwriting measurement
U Gupta, H Bansal, D Joshi
Computer methods and programs in biomedicine 189, 105305, 2020
Cyclip: Cyclic contrastive language-image pretraining
S Goel, H Bansal, S Bhatia, R Rossi, V Vinay, A Grover
Advances in Neural Information Processing Systems 35, 6704-6719, 2022
How well can Text-to-Image Generative Models understand Ethical Natural Language Interventions?
H Bansal, D Yin, M Monajatipoor, KW Chang
arXiv preprint arXiv:2210.15230, 2022
Geomlama: Geo-diverse commonsense probing on multilingual pre-trained language models
D Yin, H Bansal, M Monajatipoor, LH Li, KW Chang
arXiv preprint arXiv:2205.12247, 2022
How much complexity does an RNN architecture need to learn syntax-sensitive dependencies?
G Bhatt, H Bansal, R Singh, S Agarwal
Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020
Leaving reality to imagination: Robust classification via generated datasets
H Bansal, A Grover
arXiv preprint arXiv:2302.02503, 2023
Rethinking the Role of Scale for In-Context Learning: An Interpretability-based Case Study at 66 Billion Scale
H Bansal, K Gopalakrishnan, S Dingliwal, S Bodapati, K Kirchhoff, D Roth
arXiv preprint arXiv:2212.09095, 2022
Systematic Generalization in Neural Networks-based Multivariate Time Series Forecasting Models
H Bansal, G Bhatt, P Malhotra, AP Prathosh
2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021
Computational prediction of replication sites in DNA sequences using complex number representation
S Kundal, R Lohiya, H Bansal, S Johri, V Sarwal, K Shah
arXiv preprint arXiv:1909.13751, 2019
CleanCLIP: Mitigating Data Poisoning Attacks in Multimodal Contrastive Learning
H Bansal, N Singhi, Y Yang, F Yin, A Grover, KW Chang
arXiv preprint arXiv:2303.03323, 2023
Can RNNs trained on harder subject-verb agreement instances still perform well on easier ones?
H Bansal, G Bhatt, S Agarwal
arXiv preprint arXiv:2010.04976, 2020
Dynosaur: A Dynamic Growth Paradigm for Instruction-Tuning Data Curation
D Yin, X Liu, F Yin, M Zhong, H Bansal, J Han, KW Chang
arXiv preprint arXiv:2305.14327, 2023
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