Hritik Bansal

About Hritik Bansal

Hritik Bansal, With an exceptional h-index of 10 and a recent h-index of 10 (since 2020), a distinguished researcher at Indian Institute of Technology Delhi, specializes in the field of Multimodal, Generative AI, LLMs.

His recent articles reflect a diverse array of research interests and contributions to the field:

Survey of Bias In Text-to-Image Generation: Definition, Evaluation, and Mitigation

Climatelearn: Benchmarking machine learning for weather and climate modeling

ConTextual: Evaluating Context-Sensitive Text-Rich Visual Reasoning in Large Multimodal Models

Scaling transformer neural networks for skillful and reliable medium-range weather forecasting

VideoCon: Robust video-language alignment via contrast captions

MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts

Peering through preferences: Unraveling feedback acquisition for aligning large language models

Visit-bench: A benchmark for vision-language instruction following inspired by real-world use

Hritik Bansal Information

University

Position

___

Citations(all)

292

Citations(since 2020)

291

Cited By

13

hIndex(all)

10

hIndex(since 2020)

10

i10Index(all)

10

i10Index(since 2020)

10

Email

University Profile Page

Google Scholar

Hritik Bansal Skills & Research Interests

Multimodal

Generative AI

LLMs

Top articles of Hritik Bansal

Survey of Bias In Text-to-Image Generation: Definition, Evaluation, and Mitigation

arXiv preprint arXiv:2404.01030

2024/4/1

Climatelearn: Benchmarking machine learning for weather and climate modeling

Advances in Neural Information Processing Systems

2024/2/13

ConTextual: Evaluating Context-Sensitive Text-Rich Visual Reasoning in Large Multimodal Models

arXiv preprint arXiv:2401.13311

2024/1/24

Hritik Bansal
Hritik Bansal

H-Index: 2

Kai-Wei Chang
Kai-Wei Chang

H-Index: 3

Scaling transformer neural networks for skillful and reliable medium-range weather forecasting

arXiv preprint arXiv:2312.03876

2023/12/6

VideoCon: Robust video-language alignment via contrast captions

arXiv preprint arXiv:2311.10111

2023/11/15

Hritik Bansal
Hritik Bansal

H-Index: 2

Kai-Wei Chang
Kai-Wei Chang

H-Index: 3

MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts

arXiv preprint arXiv:2310.02255

2023/10

Peering through preferences: Unraveling feedback acquisition for aligning large language models

arXiv preprint arXiv:2308.15812

2023/8/30

Hritik Bansal
Hritik Bansal

H-Index: 2

Visit-bench: A benchmark for vision-language instruction following inspired by real-world use

NeurIPS 2023 - Dataset and Benchmark Track

2023/8/12

Dynosaur: A dynamic growth paradigm for instruction-tuning data curation

EMNLP 2023

2023/5/23

Leaving reality to imagination: Robust classification via generated datasets

arXiv preprint arXiv:2302.02503

2023/2/5

Hritik Bansal
Hritik Bansal

H-Index: 2

Cleanclip: Mitigating data poisoning attacks in multimodal contrastive learning

2023

Rethinking the role of scale for in-context learning: An interpretability-based case study at 66 billion scale

arXiv preprint arXiv:2212.09095

2022/12/18

Cyclip: Cyclic contrastive language-image pretraining

Advances in Neural Information Processing Systems

2022/12/6

Shashank Goel
Shashank Goel

H-Index: 2

Hritik Bansal
Hritik Bansal

H-Index: 2

How well can text-to-image generative models understand ethical natural language interventions?

EMNLP 2022

2022/10/27

Geomlama: Geo-diverse commonsense probing on multilingual pre-trained language models

EMNLP 2022

2022/5/24

Systematic generalization in neural networks-based multivariate time series forecasting models

2021/7/18

Hritik Bansal
Hritik Bansal

H-Index: 2

Gantavya Bhatt
Gantavya Bhatt

H-Index: 1

Can RNNs trained on harder subject-verb agreement instances still perform well on easier ones?

arXiv preprint arXiv:2010.04976

2020/10/10

An improved sex-specific and age-dependent classification model for Parkinson's diagnosis using handwriting measurement

Computer Methods and Programs in Biomedicine

2019/12/28

How much complexity does an RNN architecture need to learn syntax-sensitive dependencies?

arXiv preprint arXiv:2005.08199

2020/5/17

See List of Professors in Hritik Bansal University(Indian Institute of Technology Delhi)

Co-Authors

academic-engine