Vardaan Pahuja
Computer Science · The Ohio State University
Publications
35
Citations
298
Est. group size
~1
Recurring co-author estimate
Active years
11
Publishing since 2016
Vardaan Pahuja works on artificial intelligence methods that help computers understand and answer questions posed in natural language, including combining knowledge graphs (structured databases of facts) with text, and visual question answering (having AI systems answer questions about images). More recent work extends into automatically labeling physical traits in images of organisms, connecting language-based AI techniques with biological image analysis.
Publication output was concentrated around 2018, dropped off in surrounding years, and has shown a modest, irregular uptick since 2023.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Automatic Image-Level Morphological Trait Annotation for Organismal Images
arXiv (Cornell University) · 2026
- Automatic Image-Level Morphological Trait Annotation for Organismal Images
arXiv (Cornell University) · 2026
- A Systematic Investigation of KB-Text Embedding Alignment at Scale
Open MIND · 2021
- Learning Sparse Mixture of Experts for Visual Question Answering
arXiv (Cornell University) · 2019
- Visual question answering with modules and language modeling
Open MIND · 2019
- Memory Augmented Self-Play
arXiv (Cornell University) · 2018
- Tooling framework for instantiating natural language querying system
Proceedings of the VLDB Endowment · 2018
- Complex Sequential Question Answering: Towards Learning to Converse Over Linked Question Answer Pairs with a Knowledge Graph
Proceedings of the AAAI Conference on Artificial Intelligence · 2018
- Complex Sequential Question Answering: Towards Learning to Converse Over Linked Question Answer Pairs with a Knowledge Graph
arXiv (Cornell University) · 2018
- Complex Sequential Question Answering: Towards Learning to Converse Over\n Linked Question Answer Pairs with a Knowledge Graph
arXiv (Cornell University) · 2018
- Complex Sequential Question Answering dataset
Figshare · 2018
- Reproducibility Report for "Learning To Count Objects In Natural Images For Visual Question Answering"
ArXiv.org · 2018
- wikidata jsons (in pre-processed format)
Zenodo (CERN European Organization for Nuclear Research) · 2018
- wikidata jsons (in pre-processed format)
Figshare · 2018
- Complex Sequential Question Answering dataset
Zenodo (CERN European Organization for Nuclear Research) · 2018
- arXiv (Cornell University)×14
- Zenodo (CERN European Organization for Nuclear Research)×4
- Figshare×3
- Open MIND×2
- Proceedings of the VLDB Endowment×1
- Yu Gu
Computer Science · The Ohio State University
- Yaqing Wang
Computer Science · Purdue University West Lafayette
- Huan Sun
Computer Science · The Ohio State University
- Zhongwei Wan
Computer Science · The Ohio State University
- Zihan Zhang
Computer Science · The Ohio State University
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 19, 2026.
Claim or correct this profile