activity
20202025
most citedEvaluating Language Models on Grooming Risk Estimation Using Fuzzy Theory

1 citations · 1 across the 7 of their papers we have counts for

collaborators

9 papers

cs.CL2025

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…

cs.CL20251 cited

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…

cs.CL2024

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…

cs.CL2024

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…

cs.CL2024

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…

cs.CL2022

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…