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Found 5 papers, 1 papers with code
The Dangers of Underclaiming: Reasons for Caution When Reporting How NLP Systems Fail
Researchers in NLP often frame and discuss research results in ways that serve to deemphasize the field’s successes, often in response to the field’s widespread hype.
SocioProbe: What, When, and Where Language Models Learn about Sociodemographics
Our results show that PLMs do encode these sociodemographics, and that this knowledge is sometimes spread across the layers of some of the tested PLMs.
Deep Learning for Natural Language Inference
This tutorial discusses cutting-edge research on NLI, including recent advance on dataset development, cutting-edge deep learning models, and highlights from recent research on using NLI to understand capabilities and limits of deep learning models for language understanding and reasoning.
Language Modeling Teaches You More than Translation Does: Lessons Learned Through Auxiliary Syntactic Task Analysis
Recently, researchers have found that deep LSTMs trained on tasks like machine translation learn substantial syntactic and semantic information about their input sentences, including part-of-speech.
A Gold Standard Dependency Corpus for English
This resource addresses the lack of a gold standard dependency treebank for English, as well as the limited availability of gold standard syntactic annotations for English informal text genres.
