Rajarshi Das
Artificial Intelligence · 2002–2022
A researcher in the Science corpus: 21 papers; trusts 788 researchers and is trusted by 50 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 425 citations into it; #5,810 of 35,345 by trust here, #3,582 by citations
- Natural Language Processing — 340 citations into it; #2,253 of 5,688 by trust here, #1,674 by citations
- Computer Vision and Pattern Recognition — 157 citations into it; #7,453 of 21,575 by trust here, #6,671 by citations
- Information Retrieval & Search — 91 citations into it; #383 of 1,022 by trust here, #218 by citations
- Information Systems — 81 citations into it; #5,010 of 8,771 by trust here, #2,471 by citations
- Evaluation & Benchmarks — 66 citations into it
- Large Language Models — 46 citations into it
- Reinforcement Learning — 38 citations into it; #1,560 of 2,242 by trust here, #1,100 by citations
Whom Rajarshi Das trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Yoshua Bengio
- Ilya Sutskever
- Ronald J. Williams
- Alex Krizhevsky
- Alex Graves
- Sepp Hochreiter
- Oriol Vinyals
- Yann LeCun
Who trusts Rajarshi Das overall
- Haitian Sun
- Yuyu Zhang
- Jinhyuk Lee
- Jiadong Liang
- Bhuwan Dhingra
- Manzil Zaheer
- Minjoon Seo
- Akari Asai
- Hannaneh Hajishirzi
- Hongyu Ren
Papers from Rajarshi Das's perspective
Ordered by how strongly the researchers Rajarshi Das 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
- Gradient-based learning applied to document recognition
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- 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
- Multi-step Retriever-Reader Interaction for Scalable Open-domain Question Answering (2019) — 173 citations
- Chains of Reasoning over Entities, Relations, and Text using Recurrent Neural Networks (2016) — 278 citations
- Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases using Reinforcement Learning (2017) — 615 citations
- Multi-step Entity-centric Information Retrieval for Multi-Hop Question Answering (2019) — 54 citations
- Question Answering on Knowledge Bases and Text using Universal Schema and Memory Networks (2017) — 144 citations
- Do Multi-hop Readers Dream of Reasoning Chains? (2019) — 27 citations
- When Not to Trust Language Models: Investigating Effectiveness and Limitations of Parametric and Non-Parametric Memories (2022) — 199 citations
- When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric Memories (2022) — 1,304 citations
- Case-based Reasoning for Natural Language Queries over Knowledge Bases (2021) — 212 citations
- A Systematic Classification of Knowledge, Reasoning, and Context within the ARC Dataset (2018) — 94 citations
- Gaussian LDA for Topic Models with Word Embeddings (2015) — 363 citations
- Choosing Samples to Compute Heuristic-Strategy Nash Equilibrium (2003) — 65 citations
- ProtoQA: A Question Answering Dataset for Prototypical Common-Sense Reasoning (2020) — 68 citations
- Weaver: Deep Co-Encoding of Questions and Documents for Machine Reading (2018) — 20 citations
- A Survey on Semantic Parsing (2018) — 139 citations
- Optimal power allocation in server farms (2009) — 540 citations
- Autonomic multi-agent management of power and performance in data centers (2008) — 139 citations
- On the use of hybrid reinforcement learning for autonomic resource allocation (2007) — 127 citations
- A Hybrid Reinforcement Learning Approach to Autonomic Resource Allocation (2006) — 396 citations
- Utility functions in autonomic systems (2004) — 490 citations