Tag: adversarial machine learning
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Measuring LLM Sycophancy in Financial Applications
Explore how sycophantic behavior in LLMs impacts financial decision-making and learn methods to improve accuracy and trust in financial AI systems.
Assessing AI Models’ Risk of Sabotaging Safety Research
Study evaluates if advanced AI models sabotage or hinder AI safety research, revealing low sabotage rates but highlighting areas for improvement.
Evaluating Vision-Language Models for Astronomy Tasks
Discover how vision-language models perform in observational astronomy across imaging, spectroscopy, and photometry with the AstroVLBench benchmark.
Interoceptive AI Framework for Adaptive Self-Regulation
Discover the interoceptive machine framework enhancing AI with adaptive self-regulation and improved human-computer interaction.
Ranking-Based Explanation Quality Assessment with Listwise Rewards
Discover a novel ranking approach to explanation quality assessment using listwise rewards, improving AI model evaluation and policy optimization.