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Found 8 papers, 0 papers with code
Predictive Model Selection for Transfer Learning in Sequence Labeling Tasks
Transfer learning is a popular technique to learn a task using less training data and fewer compute resources.
IBM MNLP IE at CASE 2021 Task 1: Multigranular and Multilingual Event Detection on Protest News
In this paper, we present the event detection models and systems we have developed for Multilingual Protest News Detection - Shared Task 1 at CASE 2021.
IBM MNLP IE at CASE 2021 Task 2: NLI Reranking for Zero-Shot Text Classification
The NLI reranker uses a textual representation of target types that allows it to score the strength with which a type is implied by a text, without requiring training data for the types.
An Empirical Investigation into the Effect of Parameter Choices in Knowledge Distillation
We present a large-scale empirical study of how choices of configuration parameters affect performance in knowledge distillation (KD).
Cross-Lingual Relation Extraction with Transformers
Relation extraction (RE) is one of the most important tasks in information extraction, as it provides essential information for many NLP applications.
Event Presence Prediction Helps Trigger Detection Across Languages
The task of event detection and classification is central to most information retrieval applications.
Cascaded Models for Better Fine-Grained Named Entity Recognition
Named Entity Recognition (NER) is an essential precursor task for many natural language applications, such as relation extraction or event extraction.
Towards Lingua Franca Named Entity Recognition with BERT
In this paper we investigate a single Named Entity Recognition model, based on a multilingual BERT, that is trained jointly on many languages simultaneously, and is able to decode these languages with better accuracy than models trained only on one language.
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