1 citations · 1 across the 10 of their papers we have counts for
10 papers
A Fuzzy Evaluation of Sentence Encoders on Grooming Risk Classification
Geetanjali Bihani, Julia Rayz
With the advent of social media, children are becoming increasingly vulnerable to the risk of grooming in online settings. Detecting grooming instances in an online conversation po…
Evaluating Language Models on Grooming Risk Estimation Using Fuzzy Theory
Geetanjali Bihani, Tatiana Ringenberg, Julia Rayz
Encoding implicit language presents a challenge for language models, especially in high-risk domains where maintaining high precision is important. Automated detection of online ch…
The Reliability Paradox: Exploring How Shortcut Learning Undermines Language Model Calibration
Geetanjali Bihani, Julia Rayz
The advent of pre-trained language models (PLMs) has enabled significant performance gains in the field of natural language processing. However, recent studies have found PLMs to s…
Hire Me or Not? Examining Language Model's Behavior with Occupation Attributes
Damin Zhang, Yi Zhang, Geetanjali Bihani +1
With the impressive performance in various downstream tasks, large language models (LLMs) have been widely integrated into production pipelines, like recruitment and recommendation…
Learning Shortcuts: On the Misleading Promise of NLU in Language Models
Geetanjali Bihani, Julia Taylor Rayz
The advent of large language models (LLMs) has enabled significant performance gains in the field of natural language processing. However, recent studies have found that LLMs often…
Calibration Error Estimation Using Fuzzy Binning
Geetanjali Bihani, Julia Taylor Rayz
Neural network-based decisions tend to be overconfident, where their raw outcome probabilities do not align with the true decision probabilities. Calibration of neural networks is…
On Information Hiding in Natural Language Systems
Geetanjali Bihani, Julia Taylor Rayz
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 ris…
Low Anisotropy Sense Retrofitting (LASeR) : Towards Isotropic and Sense Enriched Representations
Geetanjali Bihani, Julia Taylor Rayz
Contextual word representation models have shown massive improvements on a multitude of NLP tasks, yet their word sense disambiguation capabilities remain poorly explained. To addr…
Fuzzy Classification of Multi-intent Utterances
Geetanjali Bihani, Julia Taylor Rayz
Current intent classification approaches assign binary intent class memberships to natural language utterances while disregarding the inherent vagueness in language and the corresp…
Model Choices Influence Attributive Word Associations: A Semi-supervised Analysis of Static Word Embeddings
Geetanjali Bihani, Julia Taylor Rayz
Static word embeddings encode word associations, extensively utilized in downstream NLP tasks. Although prior studies have discussed the nature of such word associations in terms o…