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20212026
most citedA Property Induction Framework for Neural Language Models

10 citations · 11 across the 11 of their papers we have counts for

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cs.CL2026

From Execution to Education: A Bloom-Aligned Framework for Measuring Educational Control in LLMs

Yi Zhang, Julia Rayz

We introduce a Bloom-aligned framework for measuring educational control in Large Language Models (LLMs): the ability to preserve a task's instructional intent while shifting its c…

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.CL202210 cited

A Property Induction Framework for Neural Language Models

Kanishka Misra, Julia Taylor Rayz, Allyson Ettinger

To what extent can experience from language contribute to our conceptual knowledge? Computational explorations of this question have shed light on the ability of powerful neural la…

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…