Angler: Helping Machine Translation Practitioners Prioritize Model
Improvements

Angler: Helping Machine Translation Practitioners Prioritize Model Improvements

12 April 2023

Samantha Robertson

Dominik Moritz

Papers citing "Angler: Helping Machine Translation Practitioners Prioritize Model Improvements"

8 / 8 papers shown

Title
Compress and Compare: Interactively Evaluating Efficiency and Behavior Across ML Model Compression Experiments Angie Boggust Venkatesh Sivaraman Yannick Assogba Donghao Ren Dominik Moritz Fred Hohman VLM 50 3 0 06 Aug 2024
Canvil: Designerly Adaptation for LLM-Powered User Experiences K. J. Kevin Feng Q. V. Liao Ziang Xiao Jennifer Wortman Vaughan Amy X. Zhang David W. McDonald 31 16 0 17 Jan 2024
WizMap: Scalable Interactive Visualization for Exploring Large Machine Learning Embeddings Zijie J. Wang Fred Hohman Duen Horng Chau 26 20 0 15 Jun 2023
Discovering and Validating AI Errors With Crowdsourced Failure Reports Ángel Alexander Cabrera Abraham J. Druck Jason I. Hong Adam Perer HAI 45 54 0 23 Sep 2021
GENder-IT: An Annotated English-Italian Parallel Challenge Set for Cross-Linguistic Natural Gender Phenomena Eva Vanmassenhove J. Monti 27 1 0 05 Aug 2021
The Tatoeba Translation Challenge -- Realistic Data Sets for Low Resource and Multilingual MT Jörg Tiedemann 160 164 0 13 Oct 2020
Are We Modeling the Task or the Annotator? An Investigation of Annotator Bias in Natural Language Understanding Datasets Mor Geva Yoav Goldberg Jonathan Berant 237 319 0 21 Aug 2019
Improving fairness in machine learning systems: What do industry practitioners need? Kenneth Holstein Jennifer Wortman Vaughan Hal Daumé Miroslav Dudík Hanna M. Wallach FaML HAI 192 742 0 13 Dec 2018