Papers by Julia Rayz

5 papers
Implications of Using Internet Sting Corpora to Approximate Underage Victims (2021.findings-acl)

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Challenge: Existing systems for classification and triaging child exploitation cases require a high quality of data.
Approach: They propose to annotate a corpus of underage victim chats with convicted predators to compare their goals and tactics.
Outcome: The proposed model is based on a corpus of victim, vigilante, and LEO conversations with convicted predators.
Exploring BERT’s Sensitivity to Lexical Cues using Tests from Semantic Priming (2020.findings-emnlp)

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Challenge: Using English lexical stimuli, we find that BERT models show "priming" predicting a word with greater probability when the context includes a related word versus an unrelated one.
Approach: They analyze a pre-trained BERT model with tests informed by semantic priming . they find that BERT too shows "priming" predicting a word with greater probability when context includes a related word versus an unrelated one.
Outcome: The proposed model shows a tendency to be distracted by related prime words as context becomes more informative, and lower probability of related words.
COMPS: Conceptual Minimal Pair Sentences for testing Robust Property Knowledge and its Inheritance in Pre-trained Language Models (2023.eacl-main)

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Challenge: Existing pre-trained language models (PLMs) lack robustness in demonstrating simple reasoning, despite having the prerequisite knowledge.
Approach: They propose to test pre-trained language models' ability to attribute properties to concepts and their ability to demonstrate property inheritance behavior.
Outcome: The proposed model can easily distinguish between concepts on the basis of a property when they are trivially different, but find it relatively difficult when concepts are related on the base of nuanced knowledge representations.
Embodied Language Learning: Opportunities, Challenges, and Future Directions (2024.findings-acl)

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Challenge: embodied language learning is a form of language understanding where the language learner is situated in the world, perceives it, and interacts with it.
Approach: They propose to use a concept of World Scopes to measure progress in language understanding research.
Outcome: The proposed framework identifies gaps and suggests future directions for language understanding research.
Hire Me or Not? Examining Language Model’s Behavior with Occupation Attributes (2025.coling-main)

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Challenge: Large language models (LLMs) have been widely integrated into production pipelines due to their impressive performance across multiple tasks.
Approach: They construct a dataset using a standard occupation classification knowledge base and tested it on three families of LLMs.
Outcome: The proposed framework analyzes LLMs’ behavior with respect to gender stereotypes in the context of occupation decision making.

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