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latex template set up

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......@@ -16,21 +16,21 @@
%
% These are recommended to typeset algorithms but not required. See the subsubsection on algorithms. Remove them if you don't have algorithms in your paper.
\usepackage{algorithm}
\usepackage{algorithmic}
% \usepackage{algorithmic}
%
% These are are recommended to typeset listings but not required. See the subsubsection on listing. Remove this block if you don't have listings in your paper.
\usepackage{newfloat}
\usepackage{listings}
\DeclareCaptionStyle{ruled}{labelfont=normalfont,labelsep=colon,strut=off} % DO NOT CHANGE THIS
\lstset{%
basicstyle={\footnotesize\ttfamily},% footnotesize acceptable for monospace
numbers=left,numberstyle=\footnotesize,xleftmargin=2em,% show line numbers, remove this entire line if you don't want the numbers.
aboveskip=0pt,belowskip=0pt,%
showstringspaces=false,tabsize=2,breaklines=true}
\floatstyle{ruled}
\newfloat{listing}{tb}{lst}{}
\floatname{listing}{Listing}
% \usepackage{newfloat}
% \usepackage{listings}
% \DeclareCaptionStyle{ruled}{labelfont=normalfont,labelsep=colon,strut=off} % DO NOT CHANGE THIS
% \lstset{%
% basicstyle={\footnotesize\ttfamily},% footnotesize acceptable for monospace
% numbers=left,numberstyle=\footnotesize,xleftmargin=2em,% show line numbers, remove this entire line if you don't want the numbers.
% aboveskip=0pt,belowskip=0pt,%
% showstringspaces=false,tabsize=2,breaklines=true}
% \floatstyle{ruled}
% \newfloat{listing}{tb}{lst}{}
% \floatname{listing}{Listing}
%
% Keep the \pdfinfo as shown here. There's no need
% for you to add the /Title and /Author tags.
......@@ -38,16 +38,7 @@
/TemplateVersion (2024.1)
}
\usepackage[utf8]{inputenc} % allow utf-8 input
\usepackage[T1]{fontenc} % use 8-bit T1 fonts
\usepackage{hyperref} % hyperlinks
\usepackage{url} % simple URL typesetting
\usepackage{booktabs} % professional-quality tables
\usepackage{amsfonts} % blackboard math symbols
\usepackage{nicefrac} % compact symbols for 1/2, etc.
\usepackage{microtype} % microtypography
\usepackage{xcolor} % colors
\usepackage{amsmath}
\usepackage{amsthm}
\usepackage{caption}
......@@ -64,6 +55,14 @@
\newtheorem{definition}{Definition}[section]
\newtheorem{question}{Research Question}[section]
% Bibliography
% \bibliographystyle{unsrtnat}
% \setcitestyle{numbers,square,comma}
% Algorithm
\renewcommand{\algorithmicrequire}{\textbf{Input:}}
\renewcommand{\algorithmicensure}{\textbf{Output:}}
% DISALLOWED PACKAGES
% \usepackage{authblk} -- This package is specifically forbidden
% \usepackage{balance} -- This package is specifically forbidden
......@@ -191,7 +190,7 @@
\maketitle
\begin{abstract}
\begin{abstract}
Counterfactual Explanations offer an intuitive and straightforward way to explain black-box models and offer Algorithmic Recourse to individuals. To address the need for plausible explanations, existing work has primarily relied on surrogate models to learn how the input data is distributed. This effectively reallocates the task of learning realistic explanations for the data from the model itself to the surrogate. Consequently, the generated explanations may seem plausible to humans but need not necessarily describe the behaviour of the black-box model faithfully. We formalise this notion of faithfulness through the introduction of a tailored evaluation metric and propose a novel algorithmic framework for generating \textbf{E}nergy-\textbf{C}onstrained \textbf{C}onformal \textbf{Co}unterfactuals (ECCCos) that are only as plausible as the model permits. Through extensive empirical studies, we demonstrate that ECCCos reconcile the need for faithfulness and plausibility. In particular, we show that for models with gradient access, it is possible to achieve state-of-the-art performance without the need for surrogate models. To do so, our framework relies solely on properties defining the black-box model itself by leveraging recent advances in Energy-Based Modelling and Conformal Prediction. To our knowledge, this is the first venture in this direction for generating faithful Counterfactual Explanations. Thus, we anticipate that ECCCos can serve as a baseline for future research. We believe that our work opens avenues for researchers and practitioners seeking tools to better distinguish trustworthy from unreliable models.
\end{abstract}
......@@ -246,7 +245,7 @@
\begin{figure}
\centering
\includegraphics[width=0.8\textwidth]{../artifacts/results/images/mnist_motivation.png}
\includegraphics[width=0.4\textwidth]{../artifacts/results/images/mnist_motivation.png}
\caption{Counterfactuals for turning a 9 (nine) into a 7 (seven): original image (left); then from left to right the counterfactuals generated using \textit{Wachter}, \textit{Schut} and \textit{REVISE}.}\label{fig:motiv}
\end{figure}
......@@ -330,7 +329,7 @@
\begin{figure}
\centering
\includegraphics[width=1.0\textwidth]{../artifacts/results/images/poc_gradient_fields.png}
\includegraphics[width=0.5\textwidth]{../artifacts/results/images/poc_gradient_fields.png}
\caption{Gradient fields and counterfactual paths for different generators. The objective is to generate a counterfual in the `blue' class for a sample from the `orange' class. Bright yellow stars indicate conditional samples generated through SGLD. The underlying classifier is a Joint Energy Model.}\label{fig:poc}
\end{figure}
......
@book{em:86,
editor = "Engelmore, Robert and Morgan, Anthony",
title = "Blackboard Systems",
year = 1986,
address = "Reading, Mass.",
publisher = "Addison-Wesley",
}
@inproceedings{c:83,
author = "Clancey, William J.",
year = 1983,
title = "{Communication, Simulation, and Intelligent
Agents: Implications of Personal Intelligent Machines
for Medical Education}",
booktitle="Proceedings of the Eighth International Joint Conference on Artificial Intelligence {(IJCAI-83)}",
pages = "556-560",
address = "Menlo Park, Calif",
publisher = "{IJCAI Organization}",
}
@inproceedings{c:84,
author = "Clancey, William J.",
year = 1984,
title = "{Classification Problem Solving}",
booktitle = "Proceedings of the Fourth National
Conference on Artificial Intelligence",
pages = "45-54",
address = "Menlo Park, Calif.",
publisher="AAAI Press",
}
@article{r:80,
author = {Robinson, Arthur L.},
title = {New Ways to Make Microcircuits Smaller},
volume = {208},
number = {4447},
pages = {1019--1022},
year = {1980},
doi = {10.1126/science.208.4447.1019},
publisher = {American Association for the Advancement of Science},
issn = {0036-8075},
URL = {https://science.sciencemag.org/content/208/4447/1019},
eprint = {https://science.sciencemag.org/content/208/4447/1019.full.pdf},
journal = {Science},
}
@article{r:80x,
author = "Robinson, Arthur L.",
year = 1980,
title = "{New Ways to Make Microcircuits Smaller---Duplicate Entry}",
journal = "Science",
volume = 208,
pages = "1019-1026",
}
@article{hcr:83,
title = {Strategic explanations for a diagnostic consultation system},
journal = {International Journal of Man-Machine Studies},
volume = {20},
number = {1},
pages = {3-19},
year = {1984},
issn = {0020-7373},
doi = {https://doi.org/10.1016/S0020-7373(84)80003-6},
url = {https://www.sciencedirect.com/science/article/pii/S0020737384800036},
author = {Diane Warner Hasling and William J. Clancey and Glenn Rennels},
abstract = {This article examines the problem of automatte explanation of reasoning, especially as it relates to expert systems. By explanation we mean the ability of a program to discuss what it is doing in some understandable way. We first present a general framework in which to view explanation and review some of the research done in this area. We then focus on the explanation system for NEOMYCIN, a medical consultation program. A consultation program interactively helps a user to solve a problem. Our goal is to have NEOMYCIN explain its problem-solving strategies. An explanation of strategy describes the plan the program is using to reach a solution. Such an explanation is usually concrete, referring to aspects of the current problem situation. Abstract explanations articulate a general principle, which can be applied in different situations; such explanations are useful in teaching and in explaining by analogy. We describe the aspects of NEOMYCIN that make abstract strategic explanations possible—the representation of strategic knowledge explicitly and separately from domain knowledge— and demonstrate how this representation can be used to generate explanations.}
}
@article{hcrt:83,
author = "Hasling, Diane Warner and Clancey, William J. and Rennels, Glenn R. and Test, Thomas",
year = 1983,
title = "{Strategic Explanations in Consultation---Duplicate}",
journal = "The International Journal of Man-Machine Studies",
volume = 20,
number = 1,
pages = "3-19",
}
@techreport{r:86,
author = "Rice, James",
year = 1986,
title = "{Poligon: A System for Parallel Problem Solving}",
type = "Technical Report",
number = "KSL-86-19",
institution = "Dept.\ of Computer Science, Stanford Univ.",
}
@phdthesis{c:79,
author = "Clancey, William J.",
year = 1979,
title = "{Transfer of Rule-Based Expertise
through a Tutorial Dialogue}",
type = "{Ph.D.} diss.",
school = "Dept.\ of Computer Science, Stanford Univ.",
address = "Stanford, Calif.",
}
@unpublished{c:21,
author = "Clancey, William J.",
title = "{The Engineering of Qualitative Models}",
year = 2021,
note = "Forthcoming",
}
@misc{c:22,
title={Attention Is All You Need},
author={Ashish Vaswani and Noam Shazeer and Niki Parmar and Jakob Uszkoreit and Llion Jones and Aidan N. Gomez and Lukasz Kaiser and Illia Polosukhin},
year={2017},
eprint={1706.03762},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
@misc{c:23,
title = "Pluto: The 'Other' Red Planet",
author = "{NASA}",
howpublished = "\url{https://www.nasa.gov/nh/pluto-the-other-red-planet}",
year = 2015,
note = "Accessed: 2018-12-06"
}
\ No newline at end of file
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