Gender specific and Age dependent classification model for improved diagnosis in Parkinson's disease. - Ujjwal Gupta; Hritik Bansal; Deepak Joshi (CoRR, 2019)

How much complexity does an RNN architecture need to learn syntax-sensitive dependencies? - Gantavya Bhatt; Hritik Bansal; Rishubh Singh; Sumeet Agarwal (ACL (student), 2020)

An improved sex-specific and age-dependent classification model for Parkinson's diagnosis using handwriting measurement. - Ujjwal Gupta; Hritik Bansal; Deepak Joshi (Comput. Methods Programs Biomed., 2020)

Can RNNs trained on harder subject-verb agreement instances still perform well on easier ones? - Hritik Bansal; Gantavya Bhatt; Sumeet Agarwal (CoRR, 2020)

Systematic Generalization in Neural Networks-based Multivariate Time Series Forecasting Models. - Hritik Bansal; Gantavya Bhatt; Pankaj Malhotra; Prathosh AP (IJCNN, 2021)

Systematic Generalization for Predictive Control in Multivariate Time Series. - Hritik Bansal; Gantavya Bhatt; Pankaj Malhotra; Prathosh A. P. (CoRR, 2021)

How well can Text-to-Image Generative Models understand Ethical Natural Language Interventions? - Hritik Bansal; Da Yin; Masoud Monajatipoor; Kai-Wei Chang (EMNLP, 2022)

GeoMLAMA: Geo-Diverse Commonsense Probing on Multilingual Pre-Trained Language Models. - Da Yin; Hritik Bansal; Masoud Monajatipoor; Liunian Harold Li; Kai-Wei Chang (EMNLP, 2022)

CyCLIP: Cyclic Contrastive Language-Image Pretraining. - Shashank Goel; Hritik Bansal; Sumit Bhatia; Ryan A. Rossi; Vishwa Vinay; Aditya Grover (NeurIPS, 2022)

Rethinking the Role of Scale for In-Context Learning: An Interpretability-based Case Study at 66 Billion Scale. - Hritik Bansal; Karthik Gopalakrishnan 001; Saket Dingliwal; Sravan Bodapati; Katrin Kirchhoff; Dan Roth 001 (ACL (1), 2023)

Dynosaur: A Dynamic Growth Paradigm for Instruction-Tuning Data Curation. - Da Yin; Xiao Liu; Fan Yin; Ming Zhong 005; Hritik Bansal; Jiawei Han 001; Kai-Wei Chang (EMNLP, 2023)

CleanCLIP: Mitigating Data Poisoning Attacks in Multimodal Contrastive Learning. - Hritik Bansal; Fan Yin; Nishad Singhi; Aditya Grover; Yu Yang; Kai-Wei Chang (ICCV, 2023)

VisIT-Bench: A Dynamic Benchmark for Evaluating Instruction-Following Vision-and-Language Models. - Yonatan Bitton; Hritik Bansal; Jack Hessel; Rulin Shao; Wanrong Zhu; Anas Awadalla; Josh Gardner 001; Rohan Taori; Ludwig Schmidt (NeurIPS, 2023)

ClimateLearn: Benchmarking Machine Learning for Weather and Climate Modeling. - Tung Nguyen; Jason Jewik; Hritik Bansal; Prakhar Sharma; Aditya Grover (NeurIPS, 2023)

Leaving Reality to Imagination: Robust Classification via Generated Datasets. - Hritik Bansal; Aditya Grover (CoRR, 2023)

VisIT-Bench: A Benchmark for Vision-Language Instruction Following Inspired by Real-World Use. - Yonatan Bitton; Hritik Bansal; Jack Hessel; Rulin Shao; Wanrong Zhu; Anas Awadalla; Josh Gardner 001; Rohan Taori; Ludwig Schmidt (CoRR, 2023)

MathVista: Evaluating Math Reasoning in Visual Contexts with GPT-4V, Bard, and Other Large Multimodal Models. - Pan Lu; Hritik Bansal; Tony Xia; Jiacheng Liu 010; Chunyuan Li; Hannaneh Hajishirzi; Hao Cheng 002; Kai-Wei Chang; Michel Galley; Jianfeng Gao 001 (CoRR, 2023)

Scaling transformer neural networks for skillful and reliable medium-range weather forecasting. - Tung Nguyen; Rohan Shah; Hritik Bansal; Troy Arcomano; Sandeep Madireddy; Romit Maulik; Veerabhadra Kotamarthi; Ian T. Foster; Aditya Grover (CoRR, 2023)

Improving Event Definition Following For Zero-Shot Event Detection. - Zefan Cai; Po-Nien Kung; Ashima Suvarna; Mingyu Derek Ma; Hritik Bansal; Baobao Chang; P. Jeffrey Brantingham; Wei Wang 010; Nanyun Peng 001 (ACL (1), 2024)

VideoCon: Robust Video-Language Alignment via Contrast Captions. - Hritik Bansal; Yonatan Bitton; Idan Szpektor; Kai-Wei Chang; Aditya Grover (CVPR, 2024)

Peering Through Preferences: Unraveling Feedback Acquisition for Aligning Large Language Models. - Hritik Bansal; John Dang; Aditya Grover (ICLR, 2024)

MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts. - Pan Lu; Hritik Bansal; Tony Xia; Jiacheng Liu 010; Chunyuan Li; Hannaneh Hajishirzi; Hao Cheng 002; Kai-Wei Chang; Michel Galley; Jianfeng Gao 001 (ICLR, 2024)

ConTextual: Evaluating Context-Sensitive Text-Rich Visual Reasoning in Large Multimodal Models. - Rohan Wadhawan; Hritik Bansal; Kai-Wei Chang; Nanyun Peng 001 (ICML, 2024)

DataComp-LM: In search of the next generation of training sets for language models. - Jeffrey Li; Alex Fang; Georgios Smyrnis; Maor Ivgi; Matt Jordan; Samir Yitzhak Gadre; Hritik Bansal; Etash Kumar Guha; Sedrick Scott Keh; Kushal Arora; Saurabh Garg; Rui Xin; et al. (NeurIPS, 2024)

Scaling transformer neural networks for skillful and reliable medium-range weather forecasting. - Tung Nguyen; Rohan Shah; Hritik Bansal; Troy Arcomano; Romit Maulik; Rao Kotamarthi; Ian T. Foster; Sandeep Madireddy; Aditya Grover (NeurIPS, 2024)

Survey of Bias In Text-to-Image Generation: Definition, Evaluation, and Mitigation. - Yixin Wan; Arjun Subramonian; Anaelia Ovalle; Zongyu Lin; Ashima Suvarna; Christina Chance; Hritik Bansal; Rebecca Pattichis; Kai-Wei Chang (CoRR, 2024)

GenEARL: A Training-Free Generative Framework for Multimodal Event Argument Role Labeling. - Hritik Bansal; Po-Nien Kung; P. Jeffrey Brantingham; Kai-Wei Chang; Nanyun Peng 001 (CoRR, 2024)

TALC: Time-Aligned Captions for Multi-Scene Text-to-Video Generation. - Hritik Bansal; Yonatan Bitton; Michal Yarom; Idan Szpektor; Aditya Grover; Kai-Wei Chang (CoRR, 2024)

Towards a Holistic Framework for Multimodal Large Language Models in Three-dimensional Brain CT Report Generation. - Cheng-Yi Li; Kao-Jung Chang; Cheng-Fu Yang; Hsin-Yu Wu; Wenting Chen; Hritik Bansal; Ling Chen; Yi-Ping Yang; Yu-Chun Chen; Shih-Pin Chen; Jiing-Feng Lirng; Kai-Wei Chang; et al. (CoRR, 2024)

MedMax: Mixed-Modal Instruction Tuning for Training Biomedical Assistants. - Hritik Bansal; Daniel Israel; Siyan Zhao; Shufan Li; Tung Nguyen; Aditya Grover (CoRR, 2024)

Comparing Bad Apples to Good Oranges Aligning Large Language Models via Joint Preference Optimization. - Hritik Bansal; Ashima Suvarna; Gantavya Bhatt; Nanyun Peng 001; Kai-Wei Chang; Aditya Grover (ACL (Findings), 2025)

BIG-Bench Extra Hard. - Mehran Kazemi; Bahare Fatemi; Hritik Bansal; John Palowitch; Chrysovalantis Anastasiou; Sanket Vaibhav Mehta; Lalit K. Jain; Virginia Aglietti; Disha Jindal; Peter Chen; Nishanth Dikkala; Gladys Tyen; et al. (ACL (1), 2025)

Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal Sampling. - Hritik Bansal; Arian Hosseini; Rishabh Agarwal; Vinh Q. Tran 002; Mehran Kazemi (ICLR, 2025)

VideoPhy: Evaluating Physical Commonsense for Video Generation. - Hritik Bansal; Zongyu Lin; Tianyi Xie; Zeshun Zong; Michal Yarom; Yonatan Bitton; Chenfanfu Jiang; Yizhou Sun; Kai-Wei Chang; Aditya Grover (ICLR, 2025)

Generative Verifiers: Reward Modeling as Next-Token Prediction. - Lunjun Zhang; Arian Hosseini; Hritik Bansal; Mehran Kazemi; Aviral Kumar; Rishabh Agarwal (ICLR, 2025)

BIG-Bench Extra Hard. - Mehran Kazemi; Bahare Fatemi; Hritik Bansal; John Palowitch; Chrysovalantis Anastasiou; Sanket Vaibhav Mehta; Kshitij Jain 001; Virginia Aglietti; Disha Jindal; Peter Chen; Nishanth Dikkala; Gladys Tyen; et al. (CoRR, 2025)

Peeking Behind Closed Doors: Risks of LLM Evaluation by Private Data Curators. - Hritik Bansal; Pratyush Maini (CoRR, 2025)

VideoPhy-2: A Challenging Action-Centric Physical Commonsense Evaluation in Video Generation. - Hritik Bansal; Clark Peng; Yonatan Bitton; Roman Goldenberg; Aditya Grover; Kai-Wei Chang (CoRR, 2025)

OpenVLThinker: An Early Exploration to Complex Vision-Language Reasoning via Iterative Self-Improvement. - Yihe Deng; Hritik Bansal; Fan Yin; Nanyun Peng 001; Wei Wang 010; Kai-Wei Chang (CoRR, 2025)

When To Solve, When To Verify: Compute-Optimal Problem Solving and Generative Verification for LLM Reasoning. - Nishad Singhi; Hritik Bansal; Arian Hosseini; Aditya Grover; Kai-Wei Chang; Marcus Rohrbach; Anna Rohrbach (CoRR, 2025)

LaViDa: A Large Diffusion Language Model for Multimodal Understanding. - Shufan Li; Konstantinos Kallidromitis; Hritik Bansal; Akash Gokul; Yusuke Kato; Kazuki Kozuka; Jason Kuen; Zhe Lin; Kai-Wei Chang; Aditya Grover (CoRR, 2025)

OpenThoughts: Data Recipes for Reasoning Models. - Etash Kumar Guha; Ryan Marten; Sedrick Keh; Negin Raoof; Georgios Smyrnis; Hritik Bansal; Marianna Nezhurina; Jean Mercat; Trung Vu 002; Zayne Sprague; Ashima Suvarna; Benjamin Feuer; et al. (CoRR, 2025)