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Found 6 papers, 3 papers with code
Online Advertisements with LLMs: Opportunities and Challenges
This paper explores the potential for leveraging Large Language Models (LLM) in the realm of online advertising systems.
Regret Analysis of Repeated Delegated Choice
To mitigate this behavior, the principal announces an eligible set which screens out a certain set of solutions.
PRIME: Prioritizing Interpretability in Failure Mode Extraction
To improve on these shortcomings, we propose a novel approach that prioritizes interpretability in this problem: we start by obtaining human-understandable concepts (tags) of images in the dataset and then analyze the model's behavior based on the presence or absence of combinations of these tags.
Robustness of AI-Image Detectors: Fundamental Limits and Practical Attacks
Moreover, we show that watermarking methods are vulnerable to spoofing attacks where the attacker aims to have real images identified as watermarked ones, damaging the reputation of the developers.
Text-To-Concept (and Back) via Cross-Model Alignment
We observe that the mapping between an image's representation in one model to its representation in another can be learned surprisingly well with just a linear layer, even across diverse models.
Run-Off Election: Improved Provable Defense against Data Poisoning Attacks
Based on this approach, we propose DPA+ROE and FA+ROE defense methods based on Deep Partition Aggregation (DPA) and Finite Aggregation (FA) approaches from prior work.
