Julia Kreutzer

Artificial Intelligence · 2015–2024

A researcher in the Science corpus: 19 papers; trusts 802 researchers and is trusted by 55 researchers here, as inferred from the citation graph.

Subfields

Artificial Intelligence — 548 citations into it; #3,836 of 35,345 by trust here, #4,276 by citations
Natural Language Processing — 367 citations into it; #1,036 of 5,688 by trust here, #1,161 by citations
Computer Vision and Pattern Recognition — 200 citations into it; #7,947 of 21,575 by trust here, #10,334 by citations
Reinforcement Learning — 106 citations into it; #750 of 2,242 by trust here, #1,100 by citations
Evaluation & Benchmarks — 101 citations into it
Large Language Models — 65 citations into it
Management Science and Operations Research — 60 citations into it; #2,316 of 11,946 by trust here, #2,799 by citations
Model Architectures — 60 citations into it

Whom Julia Kreutzer trusts overall

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

Who trusts Julia Kreutzer overall

Papers from Julia Kreutzer's perspective

Ordered by how strongly the researchers Julia Kreutzer 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

Can Neural Machine Translation be Improved with User Feedback? (2018) — 101 citations
Reliability and Learnability of Human Bandit Feedback for Sequence-to-Sequence Reinforcement Learning (2018) — 95 citations
Building Machine Translation Systems for the Next Thousand Languages (2022) — 120 citations
Quality at a Glance: An Audit of Web-Crawled Multilingual Datasets (2021) — 356 citations
Revisiting the Weaknesses of Reinforcement Learning for Neural Machine Translation (2021) — 51 citations
Learning What’s Easy: Fully Differentiable Neural Easy-First Taggers (2017) — 31 citations
Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages (2020) — 322 citations
A Reinforcement Learning Approach to Interactive-Predictive Neural Machine Translation (2018) — 33 citations
Learning to Segment Inputs for NMT Favors Character-Level Processing (2018) — 33 citations
The Low-Resource Double Bind: An Empirical Study of Pruning for Low-Resource Machine Translation (2021) — 64 citations
QUality Estimation from ScraTCH (QUETCH): Deep Learning for Word-level Translation Quality Estimation (2015) — 60 citations
Offline Reinforcement Learning from Human Feedback in Real-World Sequence-to-Sequence Tasks (2020) — 18 citations
Learning Structured Predictors from Bandit Feedback for Interactive NLP (2016) — 34 citations
Stochastic Structured Prediction under Bandit Feedback (2016) — 31 citations
Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model (2024) — 385 citations
Intriguing Properties of Compression on Multilingual Models (2022) — 16 citations
Explaining and Generalizing Back-Translation through Wake-Sleep (2018) — 41 citations
Bandit Structured Prediction for Neural Sequence-to-Sequence Learning (2017) — 56 citations
A Shared Task on Bandit Learning for Machine Translation (2017) — 16 citations