Sadhika Malladi
Artificial Intelligence · 2020–2024
A researcher in the Science corpus: 3 papers; trusts 157 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 130 citations into it
- Natural Language Processing — 56 citations into it
- Large Language Models — 40 citations into it
- Computer Vision and Pattern Recognition — 37 citations into it
- Evaluation & Benchmarks — 25 citations into it
- Optimization & Training — 23 citations into it
- Representation & Self-Supervised Learning — 19 citations into it
- Prompting & Reasoning — 17 citations into it
Whom Sadhika Malladi trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Diederik P. Kingma
- Yoshua Bengio
- Ilya Sutskever
- Alex Krizhevsky
- Richard Socher
- Yann LeCun
- Kaiming He
- Tomas Mikolov
- Jimmy Ba
Who trusts Sadhika Malladi overall
Papers from Sadhika Malladi's perspective
Ordered by how strongly the researchers Sadhika Malladi 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
- ImageNet: A large-scale hierarchical image database
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Fine-Tuning Language Models with Just Forward Passes (2023) — 422 citations
- LESS: Selecting Influential Data for Targeted Instruction Tuning (2024) — 544 citations
- A Mathematical Exploration of Why Language Models Help Solve Downstream Tasks (2020) — 93 citations