Interpretable visual reasoning: a survey
WebMar 31, 2024 · The collaborative reasoning for understanding each image-question pair is very critical but under-explored for an interpretable Visual Question Answering (VQA) system. Although very recent works also tried the explicit compositional processes to assemble multiple sub-tasks embedded in the questions, their models heavily rely on the … WebarXiv.org e-Print archive
Interpretable visual reasoning: a survey
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WebFeb 9, 2024 · In contrast, explainable case-based reasoning (XCBR) approaches can provide such explanations , and thus is of interest to XAI researchers. We present a taxonomy of XCBR approaches by categorizing ... WebAbstract. In the paper, we consider the task of Visual Question Answering, an important task for creating General Artificial Intelligence (AI) systems. We propose an interpretable model called GS-VQA. The main idea behind it is that a complex compositional question could be decomposed into a sequence of simple questions about objects ...
WebSep 24, 2024 · Abstract: Collaborative reasoning for understanding image-question pairs is a very critical but underexplored topic in interpretable visual question answering systems. Although very recent studies have attempted to use explicit compositional processes to assemble multiple subtasks embedded in questions, their models heavily rely on … WebApr 5, 2024 · However, despite the high accuracy achieved by deep learning models, they often lack interpretability, which can make it challenging to understand the reasoning behind the model's predictions.
WebJan 14, 2024 · Interpretable VQA. Taxonomy for Interpretable Visual Reasoning (IVR) proposed in a recent survey divides the models into four categories according to the way … WebMar 25, 2024 · After creating a large pre-trained model, it is used in downstream tasks by applying fine-tuning and few-shot learning. VLN model based on the pre-trained model obtains a better performance and robustness with a relatively small size. Fig. 1. Organization of the survey of visual language navigation. Full size image.
WebJan 28, 2024 · We believe that high model interpretability may help people break several bottlenecks of deep learning, e.g., learning from a few annotations, learning via …
WebDec 28, 2024 · A Survey on Neural Network Interpretability. Along with the great success of deep neural networks, there is also growing concern about their black-box nature. The interpretability issue affects people's trust on deep learning systems. It is also related to many ethical problems, e.g., algorithmic discrimination. body in irishWebJul 31, 2024 · Interpretable visual reasoning: A survey. TL;DR: A taxonomy based on four explanation forms of vision, text, graph and symbol used in current visual … body in italianoWebNatural language rationales could provide intuitive, higher-level explanations that are easily understandable by humans, complementing the more broadly studied lower-level explanations based on gradients or attention weights. We present the first study focused on generating natural language rationales across several complex visual reasoning tasks: … body in illinois river by bass pro shopWebMar 7, 2024 · Knowledge acquisition and reasoning are essential in intelligent welding decisions. However, the challenges of unstructured knowledge acquisition and weak knowledge linkage across phases limit the development of welding intelligence, especially in the integration of domain information engineering. This paper proposes a cognitive … glenair toolsWebOct 17, 2024 · We study the problem of concept induction in visual reasoning, i.e., identifying concepts and their hierarchical relationships from question-answer pairs associated with images; and achieve an interpretable model via working on the induced symbolic concept space. To this end, we first design a new framework named object … glenair united kingdomWebFeb 2, 2024 · We believe that the high model interpretability may help people to break several bottlenecks of deep learning, e.g., learning from very few annotations, learning … body injector neulastaWebDec 4, 2024 · Interpretable Visual Reasoning via Induced Symbolic Space. This is the repo to host the code for OCCAM (Object-Centric Compositional Attention Model) in the following paper:. Zhonghao Wang, Mo Yu, Kai Wang, Jinjun Xiong, Wen-mei Hwu, Mark Hasegawa-Johnson and Humphrey Shi, Interpretable Visual Reasoning via Induced … body in informative essay