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Found 7 papers, 1 papers with code
Noisy Text Data: Achilles’ Heel of BERT
Owing to the phenomenal success of BERT on various NLP tasks and benchmark datasets, industry practitioners are actively experimenting with fine-tuning BERT to build NLP applications for solving industry use cases.
Root Causing Prediction Anomalies Using Explainable AI
We have found this technique to be a model-agnostic, cheap and effective way to monitor complex data pipelines in production and have deployed a system for continuously analyzing the global feature importance distribution of continuously trained models.
Assistant, Parrot, or Colonizing Loudspeaker? ChatGPT Metaphors for Developing Critical AI Literacies
This study explores how discussing metaphors for AI can help build awareness of the frames that shape our understanding of AI systems, particularly large language models (LLMs) like ChatGPT.
Noisy Text Data: Achilles' Heel of popular transformer based NLP models
However, for most datasets that are used by practitioners to build industrial NLP applications, it is hard to guarantee the presence of any noise in the data.
hinglishNorm - A Corpus of Hindi-English Code Mixed Sentences for Text Normalization
We present hinglishNorm - a human annotated corpus of Hindi-English code-mixed sentences for text normalization task.
hinglishNorm -- A Corpus of Hindi-English Code Mixed Sentences for Text Normalization
We present hinglishNorm -- a human annotated corpus of Hindi-English code-mixed sentences for text normalization task.
Noisy Text Data: Achilles' Heel of BERT
Owing to the phenomenal success of BERT on various NLP tasks and benchmark datasets, industry practitioners are actively experimenting with fine-tuning BERT to build NLP applications for solving industry use cases.
