Katja Filippova

Artificial Intelligence · 2010–2023

A researcher in the Science corpus: 9 papers; trusts 201 researchers and is trusted by 59 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 118 citations into it; #4,335 of 35,345 by trust here, #7,471 by citations
• Natural Language Processing — 92 citations into it; #955 of 5,688 by trust here, #1,769 by citations
• Computer Vision and Pattern Recognition — 44 citations into it; #5,388 of 21,575 by trust here, #8,122 by citations
• Model Architectures — 15 citations into it
• Evaluation & Benchmarks — 14 citations into it; #2,363 of 3,147 by trust here, #2,330 by citations
• Generative Models — 14 citations into it; #536 of 1,956 by trust here, #1,651 by citations
• Optimization & Training — 9 citations into it
• Representation & Self-Supervised Learning — 7 citations into it

Whom Katja Filippova trusts overall

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

1. James Clarke
2. Ilya Sutskever
3. Geoffrey E. Hinton
4. Oriol Vinyals
5. Michael Collins
6. Diederik P. Kingma
7. Yoshua Bengio
8. Mirella Lapata
9. Regina Barzilay
10. Bonnie J. Dorr

Who trusts Katja Filippova overall

1. Sebastian Gehrmann
2. François Rousseau
3. Mahak Gambhir
4. Max Grusky
5. Dong Nguyen
6. Elvys Linhares Pontes
7. Carlos A. Colmenares
8. Mengyao Cao
9. Yashar Mehdad
10. Hannah Rashkin

Papers from Katja Filippova's perspective

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

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

Their papers

• Overcoming the Lack of Parallel Data in Sentence Compression (2013) — 178 citations
• Sentence Compression by Deletion with LSTMs (2015) — 266 citations
• Eval all, trust a few, do wrong to none: Comparing sentence generation models (2018) — 41 citations
• Controlled Hallucinations: Learning to Generate Faithfully from Noisy Data (2020) — 145 citations
• Dissecting Recall of Factual Associations in Auto-Regressive Language Models (2023) — 547 citations
• We Need To Talk About Random Splits (2020) — 113 citations
• Pattern Learning for Relation Extraction with a Hierarchical Topic Model (2012) — 84 citations
• User Demographics and Language in an Implicit Social Network (2012) — 68 citations
• Multi-Sentence Compression: Finding Shortest Paths in Word Graphs (2010) — 237 citations