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Found 7 papers, 1 papers with code
Learning Shortcuts: On the Misleading Promise of NLU in Language Models
The advent of large language models (LLMs) has enabled significant performance gains in the field of natural language processing.
Calibration Error Estimation Using Fuzzy Binning
Neural network-based decisions tend to be overconfident, where their raw outcome probabilities do not align with the true decision probabilities.
On Information Hiding in Natural Language Systems
With data privacy becoming more of a necessity than a luxury in today's digital world, research on more robust models of privacy preservation and information security is on the rise.
Interpretable Privacy Preservation of Text Representations Using Vector Steganography
Contextual word representations generated by language models (LMs) learn spurious associations present in the training corpora.
Low Anisotropy Sense Retrofitting (LASeR) : Towards Isotropic and Sense Enriched Representations
Contextual word representation models have shown massive improvements on a multitude of NLP tasks, yet their word sense disambiguation capabilities remain poorly explained.
Fuzzy Classification of Multi-intent Utterances
In this work, we propose a scheme to address the ambiguity in single-intent as well as multi-intent natural language utterances by creating degree memberships over fuzzified intent classes.
Model Choices Influence Attributive Word Associations: A Semi-supervised Analysis of Static Word Embeddings
Static word embeddings encode word associations, extensively utilized in downstream NLP tasks.
