1 citations · 2 across the 7 of their papers we have counts for
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Towards Unified Benchmark and Models for Multi-Modal Perceptual Metrics
Sara Ghazanfari, Siddharth Garg, Nicolas Flammarion +3
Human perception of similarity across uni- and multimodal inputs is highly complex, making it challenging to develop automated metrics that accurately mimic it. General purpose vis…
Out-of-Distribution Detection with Overlap Index
Hao Fu, Prashanth Krishnamurthy, Siddharth Garg +1
Out-of-distribution (OOD) detection is crucial for the deployment of machine learning models in the open world. While existing OOD detectors are effective in identifying OOD sample…
EMMA: Efficient Visual Alignment in Multi-Modal LLMs
Sara Ghazanfari, Alexandre Araujo, Prashanth Krishnamurthy +2
Multi-modal Large Language Models (MLLMs) have recently exhibited impressive general-purpose capabilities by leveraging vision foundation models to encode the core concepts of imag…
On the (In)feasibility of ML Backdoor Detection as an Hypothesis Testing Problem
Georg Pichler, Marco Romanelli, Divya Prakash Manivannan +3
We introduce a formal statistical definition for the problem of backdoor detection in machine learning systems and use it to analyze the feasibility of such problems, providing evi…
Novel Quadratic Constraints for Extending LipSDP beyond Slope-Restricted Activations
Patricia Pauli, Aaron Havens, Alexandre Araujo +4
Recently, semidefinite programming (SDP) techniques have shown great promise in providing accurate Lipschitz bounds for neural networks. Specifically, the LipSDP approach (Fazlyab…