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Found 4 papers, 2 papers with code
A Strong Baseline for Temporal Video-Text Alignment
In this paper, we consider the problem of temporally aligning the video and texts from instructional videos, specifically, given a long-term video, and associated text sentences, our goal is to determine their corresponding timestamps in the video.
Defining and Quantifying the Emergence of Sparse Concepts in DNNs
This paper aims to illustrate the concept-emerging phenomenon in a trained DNN.
Towards a Game-Theoretic View of Baseline Values in the Shapley Value
In the computation of Shapley values, people usually set an input variable to its baseline value to represent the absence of this variable.
Can We Faithfully Represent Masked States to Compute Shapley Values on a DNN?
Masking some input variables of a deep neural network (DNN) and computing output changes on the masked input sample represent a typical way to compute attributions of input variables in the sample.
