I am a third-year Ph.D. candidate in the Department of Computer Science at UCLA (2021-Present), co-advised by Prof. Kai-Wei Chang and Prof. Aditya Grover. 

In my research, I have worked on vision-language alignment, reasoning, and generation. In addition, I am interested in understanding the feedback data that is used to improve large language models as assistants. Further, I have also contributed to climate and weather modeling.

I will join Google DeepMind in Montreal as Student Researcher in Summer 2024. Outside UCLA, I actively collaborate with Google Research (manager: Idan Szpektor, mentor: Yonatan Bitton) and Prof. Ludwig Schimdt at UW. I spent my Summer of 2022 at Amazon AWS AI (manager: Sravan Bodapati, mentor: Karthik Gopalakrishnan) . Before UCLA, I completed my B.Tech at IIT Delhi 2020 (advisor: Sumeet Agarwal). I have also worked at Goldman Sachs as an Analyst for a year (2021). 

Hritik Bansal*, Zongyu Lin*, Tianyi Xie, Zeshun Zong, Michal Yarom, Yonatan Bitton, Chenfanfu Jiang, Yizhou Sun, Kai-Wei Chang, Aditya Grover. VideoPhy: Evaluating Physical Commonsense for Video Generation. [Website][Summary][Code]

DataComp-LM: In search of the next generation of training sets for language models. [Summary]

Hritik Bansal, Yonatan Bitton, Michal Yarom, Idan Szpektor, Aditya Grover, Kai-Wei Chang. TALC: Time-Aligned Captions for Multi-Scene Text-to-Video Generation. [Website][Summary][Code]

Hritik Bansal*, Ashima Suvarna*, Gantavya Bhatt*, Nanyun Peng, Kai-Wei Chang, Aditya Grover. Comparing Bad Apples to Good Oranges: Aligning Large Language Models via Joint Preference Optimization. [Website][Summary][Code]

Rohan Wadhawan, Hritik Bansal*, Kai-Wei Chang, Nanyun Peng. ConTextual: Evaluating Context-Sensitive Text-Rich Visual Reasoning in Large Language Models [Project Page][Summary][Code]

Accepted at ICML 2024

Oral Presentation at Vision Datasets Understanding CVPR 2024. Accepted at Evaluation of Generative Foundation Models CVPR 2024

Tung Nguyen, Rohan Shah, Hritik Bansal, Troy Arcomano, Sandeep Madireddy, Romit Maulik, Veerabhadra Kotamarthi, Ian Foster, Aditya Grover. Scaling transformer neural networks for skillful and reliable medium-range weather forecasting.

Climate Change and AI ICLR 2024 [BEST PAPER AWARD🏆]

Hritik Bansal, Yonatan Bitton, Idan Szpektor*, Kai-Wei Chang*, Aditya Grover*. VideoCon: Robust Video-Language Alignment via Contrast Captions [Project Page][Summary][Code]

Accepted at CVPR 2024

Oral Presentation at Data Problems for Foundation Models ICLR 2024 [BEST PAPER AWARD🏆]

Pan Lu, Hritik Bansal, Tony Xia, Jiacheng Liu, Chunyuan Li, Hannaneh Hajishirzi, Hao Cheng, Kai-Wei Chang, Michel Galley, Jianfeng Gao, 2023. MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts [Project Page][Summary][Code]

Oral Presentation at ICLR 2024 (Top 1.2%)

Hritik Bansal, John Dang, Aditya Grover, 2023. Peering Through Preferences: Unraveling the Feedback Acquisition for Aligning LLMs. [Summary][Code]

Accepted at ICLR 2024

Accepted at Data Problems for Foundation Models ICLR 2024

Yonatan Bitton*, Hritik Bansal*, Jack Hessel*, Rulin Shao, Wanrong Zhu, Anas Awadalla, Josh Gardner, Rohan Taori, Ludwig Schmidt, 2023. VisIT-Bench: A Benchmark for Vision-Language Instruction Following Inspired by Real-World Use. [Summary][LAION Blog][Website][Code][Video]

Accepted at NeurIPS 2023

Tung Nguyen*, Jason Jewik*, Hritik Bansal, Prakhar Sharma, Aditya Grover, 2023. ClimateLearn: Benchmarking Machine Learning for Weather and Climate Modeling [Code][Summary]

Accepted at NeurIPS 2023

Da Yin*, Xiao Liu*, Fan Yin*, Ming Zhong*, Hritik Bansal, Jiawen Han, Kai-Wei Chang, 2023. Dynosaur: A Dynamic Growth Paradigm for Instruction-Tuning Data Curation [Project Page][Summary]

Accepted at EMNLP 2023

Hritik Bansal, Aditya Grover, 2023. Leaving Reality to Imagination: Robust Classification via Generated Datasets. [Summary][Code][Dataset]

Oral Presentation at Trustworthy and Reliable Large-Scale Machine Learning Models ICLR 2023 (Top 8%)

Deployable Generative AI Workshop at ICML 2023

Hritik Bansal*, Nishad Singhi*, Yu Yang, Fan Yin, Aditya Grover, Kai-Wei Chang, 2023. CleanCLIP: Mitigating Data Poisoning Attacks in Multimodal Contrastive Learning. [Code][Summary]

Oral Presentation at ICCV 2023 (Top 1.8%)
Oral Presentation at Trustworthy and Reliable Large-Scale Machine Learning Models ICLR 2023 [Website] [BEST PAPER AWARD🏆]

Hritik Bansal, Karthik Gopalakrishnan, Saket Dingliwal, Sravan Bodapati, Katrin Kirchhoff, Dan Roth, 2022. Rethinking the Role of Scale for In-Context Learning: An Interpretability-based Case Study at 66 Billion Scale. [Summary][Code]

Poster Presentation at Main ACL 2023

Shashank Goel*, Hritik Bansal*, Sumit Bhatia, Ryan A. Rossi, Vishwa Vinay, Aditya Grover, 2022. CyCLIP: Cyclic Contrastive Language-Image Pre-training [Code][Summary]

Oral Presentation at NeurIPS 2022 (Top 1.76%)

Hritik Bansal*, Da Yin*, Masoud Monajatipoor, Kai-Wei Chang, 2022. How well can Text-to-Image Generative Models understand Ethical Natural Language Interventions? [Summary][Code][Dataset]

Oral Presentation at EMNLP 2022 (Top 4%)

Da Yin, Hritik Bansal, Masoud Monajatipoor, Liunian Harold Li, Kai-Wei Chang, 2022. GEOMLAMA: Geo-Diverse Commonsense Probing on Multilingual Pre-Trained Language Models  [Summary][Code]

Oral Presentation at EMNLP 2022 (Top 4%)

Hritik Bansal*, Gantavya Bhatt*, Pankaj Malhotra, Prathosh A.P., 2021. Systematic Generalization for Predictive Control in Multivariate Time Series. [Code]

Oral Presentation at IJCNN 2021

Hritik Bansal*, Gantavya Bhatt*, Sumeet Agarwal, 2020. Can RNNs trained on harder subject-verb agreement instances still perform well on easier ones?  [Code] [Summary]

Poster Presentation at SCiL 2021

Gantavya Bhatt*, Hritik Bansal*, Rishubh Singh*, Sumeet Agarwal. How much complexity does an RNN architecture need to learn syntax-sensitive dependencies? [Code][Video with Slides]

Poster Presentation at ACL SRW 2020

Ujjwal Gupta*, Hritik  Bansal* and Deepak Joshi, 2020. An improved sex-specific and age-dependent classification model for Parkinson's diagnosis using handwriting measurement. 

Computer Methods and Programs in Biomedicine 2020

Hritik Bansal*, Shashank Goel*, Tung Nguyen*, Aditya Grover, 2022. ClimateLearn: Machine Learning for Climate and Weather. [Tutorial][Slides][Code][Twitter Summary]

Spotlight Presentation at Climate Change AI Workshop at NeurIPS 2022