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05/03/2023
Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes
Deploying large language models (LLMs) is challenging because they are m...
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08/31/2022
Concept Gradient: Concept-based Interpretation Without Linear Assumption
Concept-based interpretations of black-box models are often more intuiti...
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03/02/2022
Faith-Shap: The Faithful Shapley Interaction Index
Shapley values, which were originally designed to assign attributions to...
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02/25/2022
Human-Centered Concept Explanations for Neural Networks
Understanding complex machine learning models such as deep neural networ...
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02/24/2022
Threading the Needle of On and Off-Manifold Value Functions for Shapley Explanations
A popular explainable AI (XAI) approach to quantify feature importance o...
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02/24/2022
First is Better Than Last for Training Data Influence
The ability to identify influential training examples enables us to debu...
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05/31/2020
Evaluations and Methods for Explanation through Robustness Analysis
Among multiple ways of interpreting a machine learning model, measuring ...
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04/12/2020
Minimizing FLOPs to Learn Efficient Sparse Representations
Deep representation learning has become one of the most widely adopted a...
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10/17/2019
On Concept-Based Explanations in Deep Neural Networks
Deep neural networks (DNNs) build high-level intelligence on low-level r...
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01/27/2019
How Sensitive are Sensitivity-Based Explanations?
We propose a simple objective evaluation measure for explanations of a c...
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12/23/2018
Unsupervised Speech Recognition via Segmental Empirical Output Distribution Matching
We consider the problem of training speech recognition systems without u...
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11/23/2018
Representer Point Selection for Explaining Deep Neural Networks
We propose to explain the predictions of a deep neural network, by point...
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11/17/2017
Multi-Label Zero-Shot Learning with Structured Knowledge Graphs
In this paper, we propose a novel deep learning architecture for multi-l...
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07/18/2017
Order-Free RNN with Visual Attention for Multi-Label Classification
In this paper, we propose the joint learning attention and recurrent neu...
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07/12/2016
