Hritik Bansal - RankMe

60 papers A* 16B 1Journal 38Unranked 5

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	BIG-Bench Extra Hard. ACL (1) 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, Xin Liu, Uri Shalit, Silvia Chiappa, Kate Olszewska, Yi Tay, Vinh Q. Tran, Quoc V. Le, Orhan Firat
2025	J	`jnl`	BIG-Bench Extra Hard. CoRR Mehran Kazemi, Bahare Fatemi, Hritik Bansal, John Palowitch, Chrysovalantis Anastasiou, Sanket Vaibhav Mehta, Kshitij Jain, Virginia Aglietti, Disha Jindal, Peter Chen, Nishanth Dikkala, Gladys Tyen, Xin Liu, Uri Shalit, Silvia Chiappa, Kate Olszewska, Yi Tay, Vinh Q. Tran, Quoc V. Le, Orhan Firat
2025	—	`conf`	Comparing Bad Apples to Good Oranges Aligning Large Language Models via Joint Preference Optimization. ACL (Findings) Hritik Bansal, Ashima Suvarna, Gantavya Bhatt, Nanyun Peng, Kai-Wei Chang, Aditya Grover
2025	A*	`conf`	Generative Verifiers: Reward Modeling as Next-Token Prediction. ICLR Lunjun Zhang, Arian Hosseini, Hritik Bansal, Mehran Kazemi, Aviral Kumar, Rishabh Agarwal
2025	J	`jnl`	HoneyBee: Data Recipes for Vision-Language Reasoners. CoRR Hritik Bansal, Devandra Singh Sachan, Kai-Wei Chang, Aditya Grover, Gargi Ghosh, Wen-tau Yih, Ramakanth Pasunuru
2025	J	`jnl`	LaViDa: A Large Diffusion Language Model for Multimodal Understanding. CoRR Shufan Li, Konstantinos Kallidromitis, Hritik Bansal, Akash Gokul, Yusuke Kato, Kazuki Kozuka, Jason Kuen, Zhe Lin, Kai-Wei Chang, Aditya Grover
2025	J	`jnl`	OpenThoughts: Data Recipes for Reasoning Models. CoRR Etash Kumar Guha, Ryan Marten, Sedrick Keh, Negin Raoof, Georgios Smyrnis, Hritik Bansal, Marianna Nezhurina, Jean Mercat, Trung Vu, Zayne Sprague, Ashima Suvarna, Benjamin Feuer, Liangyu Chen, Zaid Khan, Eric Frankel, Sachin Grover, Caroline Choi, Niklas Muennighoff, Shiye Su, Wanjia Zhao, John Yang, Shreyas Pimpalgaonkar, Kartik Sharma, Charlie Cheng-Jie Ji, Yichuan Deng, Sarah M. Pratt, Vivek Ramanujan, Jon Saad-Falcon, Jeffrey Li, Achal Dave, Alon Albalak, Kushal Arora, Blake Wulfe, Chinmay Hegde, Greg Durrett, Sewoong Oh, Mohit Bansal, Saadia Gabriel, Aditya Grover, Kai-Wei Chang, Vaishaal Shankar, Aaron Gokaslan, Mike A. Merrill, Tatsunori Hashimoto, Yejin Choi, Jenia Jitsev, Reinhard Heckel, Maheswaran Sathiamoorthy, Alexandros G. Dimakis, Ludwig Schmidt
2025	J	`jnl`	OpenVLThinker: An Early Exploration to Complex Vision-Language Reasoning via Iterative Self-Improvement. CoRR Yihe Deng, Hritik Bansal, Fan Yin, Nanyun Peng, Wei Wang, Kai-Wei Chang
2025	J	`jnl`	Peeking Behind Closed Doors: Risks of LLM Evaluation by Private Data Curators. CoRR Hritik Bansal, Pratyush Maini
2025	A*	`conf`	Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal Sampling. ICLR Hritik Bansal, Arian Hosseini, Rishabh Agarwal, Vinh Q. Tran, Mehran Kazemi
2025	J	`jnl`	VideoPhy-2: A Challenging Action-Centric Physical Commonsense Evaluation in Video Generation. CoRR Hritik Bansal, Clark Peng, Yonatan Bitton, Roman Goldenberg, Aditya Grover, Kai-Wei Chang
2025	A*	`conf`	VideoPhy: Evaluating Physical Commonsense for Video Generation. ICLR Hritik Bansal, Zongyu Lin, Tianyi Xie, Zeshun Zong, Michal Yarom, Yonatan Bitton, Chenfanfu Jiang, Yizhou Sun, Kai-Wei Chang, Aditya Grover
2025	J	`jnl`	When To Solve, When To Verify: Compute-Optimal Problem Solving and Generative Verification for LLM Reasoning. CoRR Nishad Singhi, Hritik Bansal, Arian Hosseini, Aditya Grover, Kai-Wei Chang, Marcus Rohrbach, Anna Rohrbach
2024	J	`jnl`	Comparing Bad Apples to Good Oranges: Aligning Large Language Models via Joint Preference Optimization. CoRR Hritik Bansal, Ashima Suvarna, Gantavya Bhatt, Nanyun Peng, Kai-Wei Chang, Aditya Grover
2024	A*	`conf`	ConTextual: Evaluating Context-Sensitive Text-Rich Visual Reasoning in Large Multimodal Models. ICML Rohan Wadhawan, Hritik Bansal, Kai-Wei Chang, Nanyun Peng
2024	J	`jnl`	ConTextual: Evaluating Context-Sensitive Text-Rich Visual Reasoning in Large Multimodal Models. CoRR Rohan Wadhawan, Hritik Bansal, Kai-Wei Chang, Nanyun Peng
2024	A*	`conf`	DataComp-LM: In search of the next generation of training sets for language models. NeurIPS 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, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee F. Chen, Suchin Gururangan, Mitchell Wortsman, Alon Albalak, Yonatan Bitton, Marianna Nezhurina, Amro Abbas, Cheng-Yu Hsieh, Dhruba Ghosh, Josh Gardner, Maciej Kilian, Hanlin Zhang, Rulin Shao, Sarah M. Pratt, Sunny Sanyal, Gabriel Ilharco, Giannis Daras, Kalyani Marathe, Aaron Gokaslan, Jieyu Zhang, Khyathi Raghavi Chandu, Thao Nguyen, Igor Vasiljevic, Sham M. Kakade, Shuran Song, Sujay Sanghavi, Fartash Faghri, Sewoong Oh, Luke Zettlemoyer, Kyle Lo, Alaaeldin El-Nouby, Hadi Pouransari, Alexander Toshev, Stephanie Wang, Dirk Groeneveld, Luca Soldaini, Pang Wei Koh, Jenia Jitsev, Thomas Kollar, Alex Dimakis, Yair Carmon, Achal Dave, Ludwig Schmidt, Vaishaal Shankar
2024	J	`jnl`	DataComp-LM: In search of the next generation of training sets for language models. CoRR Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Yitzhak Gadre, Hritik Bansal, Etash Kumar Guha, Sedrick Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee F. Chen, Suchin Gururangan, Mitchell Wortsman, Alon Albalak, Yonatan Bitton, Marianna Nezhurina, Amro Abbas, Cheng-Yu Hsieh, Dhruba Ghosh, Josh Gardner, Maciej Kilian, Hanlin Zhang, Rulin Shao, Sarah M. Pratt, Sunny Sanyal, Gabriel Ilharco, Giannis Daras, Kalyani Marathe, Aaron Gokaslan, Jieyu Zhang, Khyathi Raghavi Chandu, Thao Nguyen, Igor Vasiljevic, Sham M. Kakade, Shuran Song, Sujay Sanghavi, Fartash Faghri, Sewoong Oh, Luke Zettlemoyer, Kyle Lo, Alaaeldin El-Nouby, Hadi Pouransari, Alexander Toshev, Stephanie Wang, Dirk Groeneveld, Luca Soldaini, Pang Wei Koh, Jenia Jitsev, Thomas Kollar, Alexandros G. Dimakis, Yair Carmon, Achal Dave, Ludwig Schmidt, Vaishaal Shankar
2024	J	`jnl`	GenEARL: A Training-Free Generative Framework for Multimodal Event Argument Role Labeling. CoRR Hritik Bansal, Po-Nien Kung, P. Jeffrey Brantingham, Kai-Wei Chang, Nanyun Peng
2024	J	`jnl`	Generative Verifiers: Reward Modeling as Next-Token Prediction. CoRR Lunjun Zhang, Arian Hosseini, Hritik Bansal, Mehran Kazemi, Aviral Kumar, Rishabh Agarwal
2024	—	`conf`	Improving Event Definition Following For Zero-Shot Event Detection. ACL (1) Zefan Cai, Po-Nien Kung, Ashima Suvarna, Mingyu Derek Ma, Hritik Bansal, Baobao Chang, P. Jeffrey Brantingham, Wei Wang, Nanyun Peng
2024	J	`jnl`	Improving Event Definition Following For Zero-Shot Event Detection. CoRR Zefan Cai, Po-Nien Kung, Ashima Suvarna, Mingyu Derek Ma, Hritik Bansal, Baobao Chang, P. Jeffrey Brantingham, Wei Wang, Nanyun Peng
2024	A*	`conf`	MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts. ICLR Pan Lu, Hritik Bansal, Tony Xia, Jiacheng Liu, Chunyuan Li, Hannaneh Hajishirzi, Hao Cheng, Kai-Wei Chang, Michel Galley, Jianfeng Gao
2024	J	`jnl`	MedMax: Mixed-Modal Instruction Tuning for Training Biomedical Assistants. CoRR Hritik Bansal, Daniel Israel, Siyan Zhao, Shufan Li, Tung Nguyen, Aditya Grover
2024	A*	`conf`	Peering Through Preferences: Unraveling Feedback Acquisition for Aligning Large Language Models. ICLR Hritik Bansal, John Dang, Aditya Grover
2024	A*	`conf`	Scaling transformer neural networks for skillful and reliable medium-range weather forecasting. NeurIPS Tung Nguyen, Rohan Shah, Hritik Bansal, Troy Arcomano, Romit Maulik, Rao Kotamarthi, Ian T. Foster, Sandeep Madireddy, Aditya Grover
2024	J	`jnl`	Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal Sampling. CoRR Hritik Bansal, Arian Hosseini, Rishabh Agarwal, Vinh Q. Tran, Mehran Kazemi
2024	J	`jnl`	Survey of Bias In Text-to-Image Generation: Definition, Evaluation, and Mitigation. CoRR Yixin Wan, Arjun Subramonian, Anaelia Ovalle, Zongyu Lin, Ashima Suvarna, Christina Chance, Hritik Bansal, Rebecca Pattichis, Kai-Wei Chang
2024	J	`jnl`	TALC: Time-Aligned Captions for Multi-Scene Text-to-Video Generation. CoRR Hritik Bansal, Yonatan Bitton, Michal Yarom, Idan Szpektor, Aditya Grover, Kai-Wei Chang
2024	J	`jnl`	Towards a Holistic Framework for Multimodal Large Language Models in Three-dimensional Brain CT Report Generation. CoRR 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, Shih-Hwa Chiou
2024	A*	`conf`	VideoCon: Robust Video-Language Alignment via Contrast Captions. CVPR Hritik Bansal, Yonatan Bitton, Idan Szpektor, Kai-Wei Chang, Aditya Grover
2024	J	`jnl`	VideoPhy: Evaluating Physical Commonsense for Video Generation. CoRR Hritik Bansal, Zongyu Lin, Tianyi Xie, Zeshun Zong, Michal Yarom, Yonatan Bitton, Chenfanfu Jiang, Yizhou Sun, Kai-Wei Chang, Aditya Grover
2023	A*	`conf`	CleanCLIP: Mitigating Data Poisoning Attacks in Multimodal Contrastive Learning. ICCV Hritik Bansal, Fan Yin, Nishad Singhi, Aditya Grover, Yu Yang, Kai-Wei Chang
2023	J	`jnl`	CleanCLIP: Mitigating Data Poisoning Attacks in Multimodal Contrastive Learning. CoRR Hritik Bansal, Nishad Singhi, Yu Yang, Fan Yin, Aditya Grover, Kai-Wei Chang
2023	A*	`conf`	ClimateLearn: Benchmarking Machine Learning for Weather and Climate Modeling. NeurIPS Tung Nguyen, Jason Jewik, Hritik Bansal, Prakhar Sharma, Aditya Grover
2023	J	`jnl`	ClimateLearn: Benchmarking Machine Learning for Weather and Climate Modeling. CoRR Tung Nguyen, Jason Jewik, Hritik Bansal, Prakhar Sharma, Aditya Grover
2023	A*	`conf`	Dynosaur: A Dynamic Growth Paradigm for Instruction-Tuning Data Curation. EMNLP Da Yin, Xiao Liu, Fan Yin, Ming Zhong, Hritik Bansal, Jiawei Han, Kai-Wei Chang
2023	J	`jnl`	Dynosaur: A Dynamic Growth Paradigm for Instruction-Tuning Data Curation. CoRR Da Yin, Xiao Liu, Fan Yin, Ming Zhong, Hritik Bansal, Jiawei Han, Kai-Wei Chang
2023	J	`jnl`	Leaving Reality to Imagination: Robust Classification via Generated Datasets. CoRR Hritik Bansal, Aditya Grover
2023	J	`jnl`	MathVista: Evaluating Math Reasoning in Visual Contexts with GPT-4V, Bard, and Other Large Multimodal Models. CoRR Pan Lu, Hritik Bansal, Tony Xia, Jiacheng Liu, Chunyuan Li, Hannaneh Hajishirzi, Hao Cheng, Kai-Wei Chang, Michel Galley, Jianfeng Gao
2023	J	`jnl`	Peering Through Preferences: Unraveling Feedback Acquisition for Aligning Large Language Models. CoRR Hritik Bansal, John Dang, Aditya Grover
2023	—	`conf`	Rethinking the Role of Scale for In-Context Learning: An Interpretability-based Case Study at 66 Billion Scale. ACL (1) Hritik Bansal, Karthik Gopalakrishnan, Saket Dingliwal, Sravan Bodapati, Katrin Kirchhoff, Dan Roth
2023	J	`jnl`	Scaling transformer neural networks for skillful and reliable medium-range weather forecasting. CoRR Tung Nguyen, Rohan Shah, Hritik Bansal, Troy Arcomano, Sandeep Madireddy, Romit Maulik, Veerabhadra Kotamarthi, Ian T. Foster, Aditya Grover
2023	J	`jnl`	VideoCon: Robust Video-Language Alignment via Contrast Captions. CoRR Hritik Bansal, Yonatan Bitton, Idan Szpektor, Kai-Wei Chang, Aditya Grover
2023	J	`jnl`	VisIT-Bench: A Benchmark for Vision-Language Instruction Following Inspired by Real-World Use. CoRR Yonatan Bitton, Hritik Bansal, Jack Hessel, Rulin Shao, Wanrong Zhu, Anas Awadalla, Josh Gardner, Rohan Taori, Ludwig Schmidt
2023	A*	`conf`	VisIT-Bench: A Dynamic Benchmark for Evaluating Instruction-Following Vision-and-Language Models. NeurIPS Yonatan Bitton, Hritik Bansal, Jack Hessel, Rulin Shao, Wanrong Zhu, Anas Awadalla, Josh Gardner, Rohan Taori, Ludwig Schmidt
2022	A*	`conf`	CyCLIP: Cyclic Contrastive Language-Image Pretraining. NeurIPS Shashank Goel, Hritik Bansal, Sumit Bhatia, Ryan A. Rossi, Vishwa Vinay, Aditya Grover
2022	J	`jnl`	CyCLIP: Cyclic Contrastive Language-Image Pretraining. CoRR Shashank Goel, Hritik Bansal, Sumit Bhatia, Ryan A. Rossi, Vishwa Vinay, Aditya Grover
2022	A*	`conf`	GeoMLAMA: Geo-Diverse Commonsense Probing on Multilingual Pre-Trained Language Models. EMNLP Da Yin, Hritik Bansal, Masoud Monajatipoor, Liunian Harold Li, Kai-Wei Chang
2022	J	`jnl`	GeoMLAMA: Geo-Diverse Commonsense Probing on Multilingual Pre-Trained Language Models. CoRR Da Yin, Hritik Bansal, Masoud Monajatipoor, Liunian Harold Li, Kai-Wei Chang
2022	A*	`conf`	How well can Text-to-Image Generative Models understand Ethical Natural Language Interventions? EMNLP Hritik Bansal, Da Yin, Masoud Monajatipoor, Kai-Wei Chang
2022	J	`jnl`	How well can Text-to-Image Generative Models understand Ethical Natural Language Interventions? CoRR Hritik Bansal, Da Yin, Masoud Monajatipoor, Kai-Wei Chang
2022	J	`jnl`	Rethinking the Role of Scale for In-Context Learning: An Interpretability-based Case Study at 66 Billion Scale. CoRR Hritik Bansal, Karthik Gopalakrishnan, Saket Dingliwal, Sravan Bodapati, Katrin Kirchhoff, Dan Roth
2021	J	`jnl`	Systematic Generalization for Predictive Control in Multivariate Time Series. CoRR Hritik Bansal, Gantavya Bhatt, Pankaj Malhotra, Prathosh A. P.
2021	B	`conf`	Systematic Generalization in Neural Networks-based Multivariate Time Series Forecasting Models. IJCNN Hritik Bansal, Gantavya Bhatt, Pankaj Malhotra, Prathosh AP
2020	J	`jnl`	An improved sex-specific and age-dependent classification model for Parkinson's diagnosis using handwriting measurement. Comput. Methods Programs Biomed. Ujjwal Gupta, Hritik Bansal, Deepak Joshi
2020	J	`jnl`	Can RNNs trained on harder subject-verb agreement instances still perform well on easier ones? CoRR Hritik Bansal, Gantavya Bhatt, Sumeet Agarwal
2020	—	`conf`	How much complexity does an RNN architecture need to learn syntax-sensitive dependencies? ACL (student) Gantavya Bhatt, Hritik Bansal, Rishubh Singh, Sumeet Agarwal
2020	J	`jnl`	How much complexity does an RNN architecture need to learn syntax-sensitive dependencies? CoRR Gantavya Bhatt, Hritik Bansal, Rishubh Singh, Sumeet Agarwal
2019	J	`jnl`	Gender specific and Age dependent classification model for improved diagnosis in Parkinson's disease. CoRR Ujjwal Gupta, Hritik Bansal, Deepak Joshi