Keshav Santhanam
Artificial Intelligence · 2020–2024
A researcher in the Science corpus: 8 papers; trusts 68 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 215 citations into it
- Computer Vision and Pattern Recognition — 92 citations into it
- Natural Language Processing — 85 citations into it
- Information Retrieval & Search — 47 citations into it
- Information Systems — 30 citations into it
- Retrieval-Augmented Generation — 23 citations into it
- Hardware and Architecture — 19 citations into it
Whom Keshav Santhanam trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Omar Khattab
- Geoffrey E. Hinton
- Alex Krizhevsky
- Yoshua Bengio
- Matei A. Zaharia
- Diederik P. Kingma
- Ilya Sutskever
- Kaiming He
- Yann LeCun
- Jacob Devlin
Who trusts Keshav Santhanam overall
- John X. Morris
- Amirkeivan Mohtashami
- Omar Khattab
- Zhibin Gou
- Zhuyun Dai
- Zhengbao Jiang
- Eric Mitchell
- Yiwei Ma
- Akari Asai
- Zhihong Shao
Papers from Keshav Santhanam's perspective
Ordered by how strongly the researchers Keshav Santhanam trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- On the Opportunities and Risks of Foundation Models (2021) — 6,923 citations
- Holistic Evaluation of Language Models (2023) — 1,863 citations
- ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction (2021) — 784 citations
- DistIR: An Intermediate Representation for Optimizing Distributed Neural Networks (2021) — 21 citations
- Heterogeneity-Aware Cluster Scheduling Policies for Deep Learning Workloads (2020) — 300 citations
- When Benchmarks are Targets: Revealing the Sensitivity of Large Language Model Leaderboards (2024) — 153 citations
- DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines (2023) — 867 citations
- Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP (2022) — 389 citations