Jose Garrido Ramas — accepted AI-conference papers

2022

Unsupervised training data re-weighting for natural language understanding with local distribution approximation

Jose Garrido Ramas, Dieu-thu Le, Bei Chen, Manoj Kumar, Kay Rottmann

EMNLP 2022industry

One of the major challenges of training Natural Language Understanding (NLU) production models lies in the discrepancy between the distributions of the offline training data and of the online live data, due to, e.g., biased sampling scheme, cyclic seasonality shifts, annotated training data coming f…

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2021

Identifying and Resolving Annotation Changes for Natural Language Understanding

Jose Garrido Ramas, Giorgio Pessot, Abdalghani Abujabal, Martin Rajman

NAACL 2021industry

Annotation conflict resolution is crucial towards building machine learning models with acceptable performance. Past work on annotation conflict resolution had assumed that data is collected at once, with a fixed set of annotators and fixed annotation guidelines. Moreover, previous work dealt with a…

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