Ilia Kulikov
Artificial Intelligence · 2016–2023
A researcher in the Science corpus: 8 papers; trusts 312 researchers and is trusted by 30 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 153 citations into it; #13,132 of 35,345 by trust here, #6,193 by citations
- Natural Language Processing — 130 citations into it; #1,451 of 5,688 by trust here, #1,229 by citations
- Computer Vision and Pattern Recognition — 56 citations into it
- Model Architectures — 35 citations into it
- Large Language Models — 14 citations into it
- Evaluation & Benchmarks — 13 citations into it; #2,609 of 3,147 by trust here, #2,393 by citations
- Signal Processing — 13 citations into it
- Generative Models — 11 citations into it
Whom Ilia Kulikov trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Ilya Sutskever
- Geoffrey E. Hinton
- Diederik P. Kingma
- Yoshua Bengio
- Oriol Vinyals
- Kyunghyun Cho
- Alex Krizhevsky
- Alex Graves
- Dzmitry Bahdanau
- Sepp Hochreiter
Who trusts Ilia Kulikov overall
- Stephen Roller
- Ari Holtzman
- Sean Welleck
- Abigail See
- Jason Aaron Edward Weston
- Margaret Li
- Emily Dinan
- Byeongchang Kim
- Eric Michael Smith
- Paweł Budzianowski
Papers from Ilia Kulikov's perspective
Ordered by how strongly the researchers Ilia Kulikov 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
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
Their papers
- Neural Text Generation with Unlikelihood Training (2019) — 727 citations
- Don’t Say That! Making Inconsistent Dialogue Unlikely with Unlikelihood Training (2019) — 212 citations
- Consistency of a Recurrent Language Model with Respect to Incomplete Decoding (2020) — 76 citations
- Seamless: Multilingual Expressive and Streaming Speech Translation (2023) — 299 citations
- SeamlessM4T: Massively Multilingual&Multimodal Machine Translation (2023) — 202 citations
- Importance of Search and Evaluation Strategies in Neural Dialogue Modeling (2018) — 93 citations
- Importance of a Search Strategy in Neural Dialogue Modelling (2018) — 44 citations
- The RWTH/UPB/FORTH System Combination for the 4th CHiME Challenge Evaluation (2016) — 48 citations