Accuracy
DetectRL: Benchmarking LLM-Generated Text Detection in Real-World Scenarios
Detecting text generated by large language models (LLMs) is of great recent interest.
OwMatch: Conditional Self-Labeling with Consistency for Open-World Semi-Supervised Learning
Semi-supervised learning (SSL) offers a robust framework for harnessing the potential of unannotated data. Traditionally, SSL mandates that all classes possess labeled instances.
Membership Inference Attacks against Large Vision-Language Models
We believe that our work can deepen the understanding and methodology of MIAs in the context of VLLMs.
Scale-invariant Optimal Sampling for Rare-events Data with Sparse Models
Rare-events data refer to binary-response data that are highly imbalanced, i.e., the number of zeros
MultiOrg: A Multi-rater Organoid-detection Dataset Christina Bukas
Organoids, specifically, are an active area of research, providing excellent models for human organs and their functions.
OxonFair: A Flexible Toolkit for Algorithmic Fairness
This makes it easily extensible and much more expressive than existing toolkits. It supports all 9 and all 10 of the decision-based group metrics of two popular review articles.