Performance Analysis
T2Vs Meet VLMs: A Scalable Multimodal Dataset for Visual Harmfulness Recognition Chen Y eh 1 Y ou-Ming Chang 1 Wei-Chen Chiu 1 Ning Y u
Warning: This paper contains inappropriate/harmful visual contents. While widespread access to the Internet and the rapid advancement of generative models boost people's creativity and productivity, the risk of encountering inappropriate or harmful content also increases.
Context-Aware Testing: A New Paradigm for Model Testing with Large Language Models
The predominant de facto paradigm of testing ML models relies on either using only held-out data to compute aggregate evaluation metrics or by assessing the performance on different subgroups.
FreqMark: Invisible Image Watermarking via Frequency Based Optimization in Latent Space
However, existing watermarking methods fall short in robustness against regeneration attacks.
FairMedFM: Fairness Benchmarking for Medical Imaging Foundation Models
Authors are listed in alphabetical order.
Emotion-LLaMA: Multimodal Emotion Recognition and Reasoning with Instruction Tuning
Accurate emotion perception is crucial for various applications, including human-computer interaction, education, and counseling.
Rethinking Out-of-Distribution Detection on Imbalanced Data Distribution
ImOOD, to formulate the OOD detection problem on imbalanced data distribution.
Conformal Classification with Equalized Coverage for Adaptively Selected Groups
These sets reflect the model's confidence
The Elephant in the Room: Towards A Reliable Time-Series Anomaly Detection Benchmark
However, the field has long faced the "elephant in the room:" critical