Natalia Segal

Natural Language Processing · 2013–2016

A researcher in the Science corpus: 2 papers; trusts 5 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Natural Language Processing — 30 citations into it; #5,193 of 5,688 by trust here, #3,421 by citations
• Evaluation & Benchmarks — 7 citations into it; #2,749 of 3,147 by trust here, #3,037 by citations

Whom Natalia Segal trusts overall

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

1. Mauro Cettolo
2. Philipp Koehn
3. Trevor J. Hastie
4. Chris Callison-Burch

Who trusts Natalia Segal overall

1. José G. C. de Souza

Papers from Natalia Segal's perspective

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

1. Effective Approaches to Attention-based Neural Machine Translation
2. Europarl: A Parallel Corpus for Statistical Machine Translation
3. Scikit-learn: Machine Learning in Python
4. Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
5. A Simple, Fast, and Effective Reparameterization of IBM Model 2
6. WIT3: Web Inventory of Transcribed and Translated Talks
7. Findings of the 2015 Workshop on Statistical Machine Translation
8. Structured Output Layer neural network language model
9. Parallel Data, Tools and Interfaces in OPUS
10. Manual and Automatic Evaluation of Machine Translation between European Languages

Their papers

• SYSTRAN's Pure Neural Machine Translation Systems (2016) — 128 citations
• Design and Analysis of a Large Corpus of Post-Edited Translations: Quality Estimation, Failure Analysis and the Variability of Post-Edition (2013) — 16 citations