Niranjan Balasubramanian

Artificial Intelligence · 2009–2022

A researcher in the Science corpus: 11 papers; trusts 204 researchers and is trusted by 28 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 165 citations into it; #7,827 of 35,345 by trust here, #7,062 by citations
• Natural Language Processing — 125 citations into it; #1,738 of 5,688 by trust here, #2,385 by citations
• Computer Vision and Pattern Recognition — 55 citations into it; #11,395 of 21,575 by trust here, #7,027 by citations
• Evaluation & Benchmarks — 36 citations into it
• Large Language Models — 26 citations into it
• Information Retrieval & Search — 22 citations into it
• Information Systems — 19 citations into it; #5,661 of 8,771 by trust here, #5,713 by citations
• Model Architectures — 18 citations into it

Whom Niranjan Balasubramanian trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Diederik P. Kingma
4. Ilya Sutskever
5. Alex Krizhevsky
6. Tushar Khot
7. Peter Clark
8. Christopher D. Manning
9. Sepp Hochreiter
10. Yann LeCun

Who trusts Niranjan Balasubramanian overall

1. Tushar Khot
2. Karl Pichotta
3. Peter Alexander Jansen
4. Snigdha Chaturvedi
5. Peter Clark
6. Haoruo Peng
7. Alon Jacovi
8. Yu Wang
9. Harsh Trivedi
10. Nasrin Mostafazadeh

Papers from Niranjan Balasubramanian's perspective

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

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

Their papers

• A study of the knowledge base requirements for passing an elementary science test (2013) — 48 citations
• Generating Coherent Event Schemas at Scale (2013) — 116 citations
• Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions (2022) — 1,143 citations
• The Fine Line between Linguistic Generalization and Failure in Seq2Seq-Attention Models (2018) — 30 citations
• Repurposing Entailment for Multi-Hop Question Answering Tasks (2019) — 50 citations
• ♫ MuSiQue: Multihop Questions via Single-hop Question Composition (2021) — 972 citations
• Controlling Information Aggregation for Complex Question Answering (2018) — 13 citations
• Author’s Sentiment Prediction (2020) — 28 citations
• DeFormer: Decomposing Pre-trained Transformers for Faster Question Answering (2020) — 71 citations
• Energy consumption in mobile phones: a measurement study and implications for network applications (2009) — 1,257 citations
• What’s in an Explanation? Characterizing Knowledge and Inference Requirements for Elementary Science Exams (2016) — 67 citations