Shikhar Vashishth
Artificial Intelligence · 2019–2025
A researcher in the Science corpus: 4 papers; trusts 81 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 80 citations into it; #26,205 of 35,345 by trust here, #14,181 by citations
- Graph Learning — 30 citations into it
- Natural Language Processing — 29 citations into it; #5,034 of 5,688 by trust here, #4,361 by citations
- Computer Vision and Pattern Recognition — 26 citations into it
- Representation & Self-Supervised Learning — 17 citations into it
- Management Science and Operations Research — 10 citations into it
- Knowledge Graphs & Representation — 9 citations into it
- Model Architectures — 9 citations into it
Whom Shikhar Vashishth trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Richard Socher
- Yoshua Bengio
- Geoffrey E. Hinton
- Antoine Bordes
- Diederik P. Kingma
- Ilya Sutskever
- Alex Krizhevsky
- Jason Aaron Edward Weston
- Yann LeCun
- Christopher D. Manning
Who trusts Shikhar Vashishth overall
- Jing Zhang
- Martin Tutek
- Apoorv Saxena
- Lyle Regenwetter
- Ekagra Ranjan
- Ning Wang
- Nicola De Cao
- Zhaocheng Zhu
- Bo Chen
- Partha P. Talukdar
Papers from Shikhar Vashishth's perspective
Ordered by how strongly the researchers Shikhar Vashishth trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Attention Interpretability Across NLP Tasks (2019) — 191 citations
- Composition-based Multi-Relational Graph Convolutional Networks (2019) — 1,165 citations
- Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities (2025) — 3,609 citations
- InteractE: Improving Convolution-based Knowledge Graph Embeddings by Increasing Feature Interactions (2019) — 399 citations