Aleksandra Piktus
Artificial Intelligence · 2019–2024
A researcher in the Science corpus: 12 papers; trusts 250 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 459 citations into it; #23,639 of 35,345 by trust here, #5,788 by citations
- Natural Language Processing — 318 citations into it; #4,341 of 5,688 by trust here, #1,221 by citations
- Computer Vision and Pattern Recognition — 185 citations into it; #19,436 of 21,575 by trust here, #6,326 by citations
- Evaluation & Benchmarks — 151 citations into it
- Large Language Models — 141 citations into it
- Information Retrieval & Search — 112 citations into it; #793 of 1,022 by trust here, #233 by citations
- Information Systems — 49 citations into it
- Retrieval-Augmented Generation — 26 citations into it
Whom Aleksandra Piktus trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yoshua Bengio
- Geoffrey E. Hinton
- Diederik P. Kingma
- Ilya Sutskever
- Alex Krizhevsky
- Kaiming He
- Yann LeCun
- Tomas Mikolov
- Jacob Devlin
- Alex Graves
Who trusts Aleksandra Piktus overall
- Fabio Petroni
- Akari Asai
- Sebastian Hofstätter
- Patrick Lewis
- Nicola De Cao
- Marc Marone
- Timo Schick
- Tianyu Gao
- Gautier Izacard
- Luyu Gao
Papers from Aleksandra Piktus's perspective
Ordered by how strongly the researchers Aleksandra Piktus trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- 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
- PAQ: 65 Million Probably-Asked Questions and What You Can Do With Them (2021) — 275 citations
- How Decoding Strategies Affect the Verifiability of Generated Text (2019) — 60 citations
- Generating Fact Checking Briefs (2020) — 66 citations
- Scaling Data-Constrained Language Models (2023) — 422 citations
- The Web Is Your Oyster - Knowledge-Intensive NLP against a Very Large Web Corpus (2021) — 79 citations
- Domain-matched Pre-training Tasks for Dense Retrieval (2021) — 72 citations
- The ROOTS Search Tool: Data Transparency for LLMs (2023) — 42 citations
- Spacerini: Plug-and-play Search Engines with Pyserini and Hugging Face (2023) — 5 citations
- Improving Wikipedia verifiability with AI (2022) — 23 citations
- Replacing Judges with Juries: Evaluating LLM Generations with a Panel of Diverse Models (2024) — 271 citations
- KILT: a Benchmark for Knowledge Intensive Language Tasks (2020) — 820 citations
- How Context Affects Language Models' Factual Predictions (2020) — 271 citations