Shishir G. Patil

Artificial Intelligence · 2022–2025

A researcher in the Science corpus: 6 papers; trusts 102 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 136 citations into it; #30,889 of 35,345 by trust here, #10,942 by citations
• Computer Vision and Pattern Recognition — 65 citations into it; #18,953 of 21,575 by trust here, #7,852 by citations
• Large Language Models — 59 citations into it; #642 of 799 by trust here, #549 by citations
• Efficiency & Compression — 29 citations into it
• Natural Language Processing — 23 citations into it
• Model Architectures — 14 citations into it
• Hardware and Architecture — 12 citations into it
• Optimization & Training — 12 citations into it

Whom Shishir G. Patil trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Kaiming He
2. Karen Simonyan
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Yoshua Bengio
6. Andrew Zisserman
7. Jacob Devlin
8. Diederik P. Kingma
9. Ilya Sutskever
10. Yann LeCun

Who trusts Shishir G. Patil overall

1. Ji Lin
2. Yashar Talebirad
3. Naman Jain
4. Tianjun Zhang
5. Qiusi Zhan
6. Yuchen Zhuang
7. Grégoire Mialon
8. Minghao Li
9. Qiaoyu Tang
10. Ligeng Zhu

Papers from Shishir G. Patil's perspective

Ordered by how strongly the researchers Shishir G. Patil trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Gorilla: Large Language Model Connected with Massive APIs (2023) — 1,419 citations
• POET: Training Neural Networks on Tiny Devices with Integrated Rematerialization and Paging (2022) — 54 citations
• The Berkeley Function Calling Leaderboard (BFCL): From Tool Use to Agentic Evaluation of Large Language Models (2025) — 390 citations
• RAFT: Adapting Language Model to Domain Specific RAG (2024) — 371 citations
• MemGPT: Towards LLMs as Operating Systems (2023) — 960 citations
• Training Neural Networks on Tiny Devices with Integrated Rematerialization and Paging (2022)