Relevant bibliographies by topics / Explanation

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Explanation'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Explanation"

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Atanasova, Pepa, Jakob Grue Simonsen, Christina Lioma, and Isabelle Augenstein. "Diagnostics-Guided Explanation Generation." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 10 (2022): 10445–53. http://dx.doi.org/10.1609/aaai.v36i10.21287.

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Explanations shed light on a machine learning model's rationales and can aid in identifying deficiencies in its reasoning process. Explanation generation models are typically trained in a supervised way given human explanations. When such annotations are not available, explanations are often selected as those portions of the input that maximise a downstream task's performance, which corresponds to optimising an explanation's Faithfulness to a given model. Faithfulness is one of several so-called diagnostic properties, which prior work has identified as useful for gauging the quality of an expl
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Clark, Stephen R. L. "The Limits of Explanation: Limited Explanations." Royal Institute of Philosophy Supplement 27 (March 1990): 195–210. http://dx.doi.org/10.1017/s1358246100005117.

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When I was first approached to read a paper at the conference from which this volume takes its beginning I expected that Flint Schier, with whom I had taught a course on the Philosophy of Biology in my years at Glasgow, would be with us to comment and to criticize. I cannot let this occasion pass without expressing once again my own sense of loss. I am sure that we would all have gained by his presence, and hope that he would find things both to approve, and disapprove, in the following venture.
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Kleih, Björn-Christian. "Die mündliche Erklärung zur Abstimmung gemäß § 31 Absatz 1 GOBT – eine parlamentarische Wundertüte mit Potenzial?" Zeitschrift für Parlamentsfragen 51, no. 4 (2020): 865–87. http://dx.doi.org/10.5771/0340-1758-2020-4-865.

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According to the Rules of Procedure of the German Bundestag (”GOBT”), every Member of Parliament is granted a five minutes’ verbal explanation of vote . It is granted for nearly every kind of vote in the House . The verbal explanation is often considered a privilege to MPs going against the position taken by their group . Yet, it is also used to confirm the party position and it is abused to continue already closed debates . In either case, they can be a grab bag for both parliament’s plenum and its president; the verbal explanation’s content is only revealed when the explanation is given . A
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Fogelin, Lars. "Inference to the Best Explanation: A Common and Effective Form of Archaeological Reasoning." American Antiquity 72, no. 4 (2007): 603–26. http://dx.doi.org/10.2307/25470436.

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Processual and postprocessual archaeologists implicitly employ the same epistemological system to evaluate the worth of different explanations: inference to the best explanation. This is good since inference to the best explanation is the most effective epistemological approach to archaeological reasoning available. Underlying the logic of inference to the best explanation is the assumption that the explanation that accounts for the most evidence is also most likely to be true. This view of explanation often reflects the practice of archaeological reasoning better than either the hypothetico-d
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Brdnik, Saša, Vili Podgorelec, and Boštjan Šumak. "Assessing Perceived Trust and Satisfaction with Multiple Explanation Techniques in XAI-Enhanced Learning Analytics." Electronics 12, no. 12 (2023): 2594. http://dx.doi.org/10.3390/electronics12122594.

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This study aimed to observe the impact of eight explainable AI (XAI) explanation techniques on user trust and satisfaction in the context of XAI-enhanced learning analytics while comparing two groups of STEM college students based on their Bologna study level, using various established feature relevance techniques, certainty, and comparison explanations. Overall, the students reported the highest trust in local feature explanation in the form of a bar graph. Additionally, master’s students presented with global feature explanations also reported high trust in this form of explanation. The high
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Weisberg, Deena Skolnick, Frank C. Keil, Joshua Goodstein, Elizabeth Rawson, and Jeremy R. Gray. "The Seductive Allure of Neuroscience Explanations." Journal of Cognitive Neuroscience 20, no. 3 (2008): 470–77. http://dx.doi.org/10.1162/jocn.2008.20040.

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Explanations of psychological phenomena seem to generate more public interest when they contain neuroscientific information. Even irrelevant neuroscience information in an explanation of a psychological phenomenon may interfere with people's abilities to critically consider the underlying logic of this explanation. We tested this hypothesis by giving naïve adults, students in a neuroscience course, and neuroscience experts brief descriptions of psychological phenomena followed by one of four types of explanation, according to a 2 (good explanation vs. bad explanation) × 2 (without neuroscience
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Skorupski, John. "Explanation in the Social Sciences: Explanation and Understanding in Social Science." Royal Institute of Philosophy Supplement 27 (March 1990): 119–34. http://dx.doi.org/10.1017/s1358246100005075.

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Hempelian orthodoxy on the nature of explanation in general, and on explanation in the social sciences in particular, holds that(a) full explanations are arguments(b) full explanations must include at least one law(c) reason explanations are causalDavid Ruben disputes (a) and (b) but he does not dispute (c). Nor does he dispute that ‘explanations in both natural and social science need laws in other ways, even when not as part of the explanation itself (p. 97 above). The distance between his view and the covering law theory, he points out, ‘is not as great as it may first appear to be’ (p. 97
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Yamaguchi, Shin'ya, and Kosuke Nishida. "Explanation Bottleneck Models." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 20 (2025): 21886–94. https://doi.org/10.1609/aaai.v39i20.35495.

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Recent concept-based interpretable models have succeeded in providing meaningful explanations by pre-defined concept sets. However, the dependency on the pre-defined concepts restricts the application because of the limited number of concepts for explanations. This paper proposes a novel interpretable deep neural network called explanation bottleneck models (XBMs). XBMs generate a text explanation from the input without pre-defined concepts and then predict a final task prediction based on the generated explanation by leveraging pre-trained vision-language encoder-decoder models. To achieve bo
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Swinburne, Richard. "The Limits of Explanation: The Limits of Explanation." Royal Institute of Philosophy Supplement 27 (March 1990): 177–93. http://dx.doi.org/10.1017/s1358246100005105.

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In purporting to explain the occurrence of some event or process we cite the causal factors which, we assert, brought it about or keeps it in being. The explanation is a true one if those factors did indeed bring it about or keep it in being. In discussing explanation I shall henceforward (unless I state otherwise) concern myself only with true explanations. I believe that there are two distinct kinds of way in which causal factors operate in the world, two distinct kinds of causality, and so two distinct kinds of explanation. For historical reasons, I shall call these kinds of causality and e
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Gillett, Carl. "WHY CONSTITUTIVE MECHANISTIC EXPLANATION CANNOT BE CAUSAL." American Philosophical Quarterly 57, no. 1 (2020): 31–50. http://dx.doi.org/10.2307/48570644.

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Abstract In his “New Consensus” on explanation, Wesley Salmon (1989) famously argued that there are two kinds of scientific explanation: global, derivational, and unifying explanations, and then local, ontic explanations backed by causal relations. Following Salmon’s New Consensus, the dominant view in philosophy of science is what I term “neo-Causalism” which assumes that all ontic explanations of singular fact/event are causal explanations backed by causal relations, and that scientists only search for causal patterns or relations and only offer causal explanations of singular facts/events.
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Dissertations / Theses on the topic "Explanation"

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Deulofeu, Batllori Roger. "Scientific explanation in biology. Beyond mechanistic explanation." Doctoral thesis, Universitat de Barcelona, 2020. http://hdl.handle.net/10803/668748.

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Understanding how scientists explain has been one of the major goals of the philosophy of science. Given that explaining is one of the most important tasks that scientists aim at and given the high specialization that currently affects all scientific disciplines, we encounter what might at first glance appear to us as many different types of explanations and very different ways of explaining natural phenomena. This suggests a pluralist picture regarding scientific explanation, particularly in biology, namely the existence of different accounts of explanation that do not share an interesting co
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Paez, Andres. "Explanations in K : an analysis of explanation as a belief revision operation /." Oberhausen : Athena, 2006. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=015470212&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA.

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Hegemann, Lena. "Reciprocal Explanations : An Explanation Technique for Human-AI Partnership in Design Ideation." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-281339.

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Advancements in creative artificial intelligence (AI) are leading to systems that can actively work together with designers in tasks such as ideation, i.e. the creation, development, and communication of ideas. In human group work, making suggestions and explaining the reasoning behind them as well as comprehending other group member’s explanations aids reflection, trust, alignment of goals and inspiration through diverse perspectives. Despite their ability to inspire through independent suggestions, state-of-the-art creative AI systems do not leverage these advantages of group work due to mis
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Almeqdad, Qais Ibrahim. "Self-explanation and explanation in children with learning difficulties." Thesis, University of Cambridge, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.612344.

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Roberts, Rosemary. "What makes an explanation a good explanation? : adult learners' criteria for acceptance of a good explanation /." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape7/PQDD_0006/MQ42436.pdf.

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Hörberg, Eric. "Is explanation overrated? : A research on how explanation affects performance." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-157513.

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School results are dropping in Sweden and actions are taken by the swedish government to prevent it. This report questions these actions.With a parallel between school and video games, in that they are both about teaching a student/player how to do something, a game is made to test how further explanation of the games mechanics affects the players ability to learn about them. The results are in line with other studies, overexplaining is hurting the players ability to learn about the game.
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Lipton, P. "Explanation and evidence." Thesis, University of Oxford, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.371691.

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Bodle, Matthew James. "Grounding and explanation." Thesis, King's College London (University of London), 2018. https://kclpure.kcl.ac.uk/portal/en/theses/grounding-and-explanation(23a3509e-ffbe-4750-a928-7cb031e0c6de).html.

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This thesis defends the notion of grounding — an explanatory connection of non-causal determination. I present four challenges to developing a systematic theory of grounding, and show that they can be met satisfactorily. The first challenge is that grounding is unintelligible or uninformative—or at any rate, that its work can be done by more familiar notions. If so, the notion of grounding is not even prima facie justified. I argue that grounding is at least as informative as—and, in some respects, more informative than—the more familiar notions it is supposed to supplant. It is necessary beca
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Nickel, Bernhard Ph D. Massachusetts Institute of Technology. "Truth in explanation." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/33711.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Linguistics and Philosophy, 2005.<br>Includes bibliographical references (p. 155-163).<br>My thesis consists of three papers on truth and explanations in science. Broadly, the question I ask is semantic. Should the best account of certain bits of our scientific practice focus on the concept of truth? More specifically, should the crucial distinctions between good and bad aspects of that practice be drawn in terms of truth? My thesis consists of three case studies: ceteris paribus laws in the special sciences, appeals to idealizat
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Taylor, Elanor Lycan William G. "Models and explanation." Chapel Hill, N.C. : University of North Carolina at Chapel Hill, 2008. http://dc.lib.unc.edu/u?/etd,1914.

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Thesis (M.A.)--University of North Carolina at Chapel Hill, 2008.<br>Title from electronic title page (viewed Dec. 11, 2008). "... in partial fulfillment of the requirements for the degree of Master of Arts in the Department of Philosophy." Discipline: Philosophy; Department/School: Philosophy.
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Books on the topic "Explanation"

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1940-, Cornwell John, ed. Explanations: Styles of explanation in science. Oxford University Press, 2004.

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Hon, Giora, and Sam S. Rakover, eds. Explanation. Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-015-9731-9.

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David-Hillel, Ruben, ed. Explanation. Oxford University Press, 1993.

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1958-, Campbell Joseph Keim, O'Rourke Michael 1963-, and Silverstein Harry 1942-, eds. Causation and explanation. MIT Press, 2007.

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Weber, Erik, Jeroen Van Bouwel, and Leen De Vreese. Scientific Explanation. Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-6446-0.

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PERSSON, JOHANNES, and PETRI YLIKOSKI, eds. RETHINKING EXPLANATION. Springer Netherlands, 2007. http://dx.doi.org/10.1007/978-1-4020-5581-2.

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1947-, Kitcher Philip, and Salmon Wesley C, eds. Scientific explanation. University of Minnesota Press, 1989.

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Theophylactus. The explanation. Chysostom Press, 1992.

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Johannes, Persson, and Ylikoski Petri, eds. Rethinking explanation. Springer, 2007.

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Ruben, David-Hillel. Explaining explanation. Routledge, 1990.

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Book chapters on the topic "Explanation"

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Hon, Giora. "The Why and How of Explanation: An Analytical Exposition." In Explanation. Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-015-9731-9_1.

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Salmon, Merrilee H. "Explanation in Archaeology." In Explanation. Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-015-9731-9_10.

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Uttal, William R. "Can Psychological Processes be Explained? A Call for a Revitalized Behaviorism." In Explanation. Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-015-9731-9_11.

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Balaban, Oded. "The Use of Error as an Explanatory Category in Politics." In Explanation. Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-015-9731-9_12.

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Lorand, Ruth. "Are There Aesthetic Explanations?" In Explanation. Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-015-9731-9_13.

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Lipton, Peter. "What Good is an Explanation?" In Explanation. Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-015-9731-9_2.

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Salmon, Wesley C. "Explanation and Confirmation: A Bayesian Critique of Inference to the Best Explanation." In Explanation. Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-015-9731-9_3.

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Lipton, Peter. "Is Explanation a Guide to Inference? A Reply to Wesley C. Salmon." In Explanation. Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-015-9731-9_4.

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Salmon, Wesley C. "Reflections of a Bashful Bayesian: A Reply to Peter Lipton." In Explanation. Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-015-9731-9_5.

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Harari-Eshel, Orna. "Knowledge and Explanation in Aristotle’s Posterior Analytics." In Explanation. Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-015-9731-9_6.

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Conference papers on the topic "Explanation"

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Noppel, Maximilian, and Christian Wressnegger. "Composite Explanation-Aware Attacks." In 2025 IEEE Security and Privacy Workshops (SPW). IEEE, 2025. https://doi.org/10.1109/spw67851.2025.00022.

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Gupta, Sharmi Dev, Barry O'Sullivan, and Luis Quesada. "Counterfactual Explanation Through Constraint Relaxation." In 2024 IEEE 36th International Conference on Tools with Artificial Intelligence (ICTAI). IEEE, 2024. https://doi.org/10.1109/ictai62512.2024.00064.

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Jadhav, Ghanshyam. "Classical Explanation of Photoelectric Effect." In 2025 Fifth International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT). IEEE, 2025. https://doi.org/10.1109/icaect63952.2025.10958964.

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Feldhus, Nils. "Conversational XAI and Explanation Dialogues." In Proceedings of the 20th Workshop of Young Researchers' Roundtable on Spoken Dialogue Systems. Association for Computational Linguistics, 2024. https://doi.org/10.18653/v1/2024.yrrsds-1.1.

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Yepmo, Véronne. "Anomaly Explanation." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/844.

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With the surge of deep learning and laws aiming at regulating the use of artificial intelligence, providing explanations to algorithms outputs has been a hot topic in the recent years. Most works are devoted to the explanation of classifiers outputs. The explanation of unsupervised machine learning algorithms, like anomaly detection, has received less attention from the XAI community. But this little interest is not imputable to the irrelevance of the topic. In this paper, we demonstrate the importance of anomaly explanation, the areas still needing investigation based upon our previous contri
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Chowdhury, Tanya, Razieh Rahimi, and James Allan. "Equi-explanation Maps: Concise and Informative Global Summary Explanations." In FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency. ACM, 2022. http://dx.doi.org/10.1145/3531146.3533112.

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Mahmud, Saaduddin, Sandhya Saisubramanian, and Shlomo Zilberstein. "Explanation-Guided Reward Alignment." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/53.

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Agents often need to infer a reward function from observations to learn desired behaviors. However, agents may infer a reward function that does not align with the original intent because there can be multiple reward functions consistent with its observations. Operating based on such misaligned rewards can be risky. Furthermore, black-box representations make it difficult to verify the learned rewards and prevent harmful behavior. We present a framework for verifying and improving reward alignment using explanations and show how explanations can help detect misalignment and reveal failure case
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Bhatt, Umang, Adrian Weller, and José M. F. Moura. "Evaluating and Aggregating Feature-based Model Explanations." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/417.

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A feature-based model explanation denotes how much each input feature contributes to a model's output for a given data point. As the number of proposed explanation functions grows, we lack quantitative evaluation criteria to help practitioners know when to use which explanation function. This paper proposes quantitative evaluation criteria for feature-based explanations: low sensitivity, high faithfulness, and low complexity. We devise a framework for aggregating explanation functions. We develop a procedure for learning an aggregate explanation function with lower complexity and then derive a
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Chakraborti, Tathagata, Sarath Sreedharan, Yu Zhang, and Subbarao Kambhampati. "Plan Explanations as Model Reconciliation: Moving Beyond Explanation as Soliloquy." In Twenty-Sixth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/23.

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When AI systems interact with humans in the loop, they are often called on to provide explanations for their plans and behavior. Past work on plan explanations primarily involved the AI system explaining the correctness of its plan and the rationale for its decision in terms of its own model. Such soliloquy is wholly inadequate in most realistic scenarios where the humans have domain and task models that differ significantly from that used by the AI system. We posit that the explanations are best studied in light of these differing models. In particular, we show how explanation can be seen as
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Srinivasan, Ramya, and Ajay Chander. "Explanation Perspectives from the Cognitive Sciences---A Survey." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/670.

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With growing adoption of AI across fields such as healthcare, finance, and the justice system, explaining an AI decision has become more important than ever before. Development of human-centric explainable AI (XAI) systems necessitates an understanding of the requirements of the human-in-the-loop seeking the explanation. This includes the cognitive behavioral purpose that the explanation serves for its recipients, and the structure that the explanation uses to reach those ends. An understanding of the psychological foundations of explanations is thus vital for the development of effective huma
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Reports on the topic "Explanation"

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Santos, Jr, and Eugene. Modelling Temporal Abductive Explanation. Defense Technical Information Center, 1993. http://dx.doi.org/10.21236/ada263096.

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VanLehn, Kurt, William Ball, and Bernadette Kowalski. Explanation-Based Learning of Correctness: Towards a Model of the Self-Explanation Effect. Defense Technical Information Center, 1990. http://dx.doi.org/10.21236/ada225644.

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Ford, Nicholas, and Charles Yuji Horioka. The 'Real' Explanation of the PPP Puzzle. National Bureau of Economic Research, 2016. http://dx.doi.org/10.3386/w22198.

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Rosenbloom, Paul S., Soowon Lee, and Amy Unruh. Bias in Planning and Explanation-Based Learning. Defense Technical Information Center, 1993. http://dx.doi.org/10.21236/ada269608.

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Feiner, Steven K., and Kathleen R. McKeown. Coordinating Text and Graphics in Explanation Generation. Defense Technical Information Center, 1989. http://dx.doi.org/10.21236/ada460217.

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VanLehn, Kirt, Randolph M. Jones, and Michelene T. Chi. A Model of the Self-Explanation Effect. Defense Technical Information Center, 1991. http://dx.doi.org/10.21236/ada241200.

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Schulz, Jan, Daniel Mayerhoffer, and Anna Gebhard. A Network-Based Explanation of Perceived Inequality. Otto-Friedrich-Universität, 2021. http://dx.doi.org/10.20378/irb-49393.

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Across income groups and countries, the public perception of economic inequality and many other macroeconomic variables such as inflation or unemployment rates is spectacularly wrong. These misperceptions have far-reaching consequences, as it is perceived inequality, not actual inequality informing redistributive preferences. The prevalence of this phenomenon is independent of social class and welfare regime, which suggests the existence of a common mechanism behind public perceptions. We propose a network-based explanation of perceived inequality building on recent advances in random geometri
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Wang, Pengfei, and Yi Wen. Financial Development and Economic Volatility: A Unified Explanation. Federal Reserve Bank of St. Louis, 2009. http://dx.doi.org/10.20955/wp.2009.022.

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Ford, Nicholas, and Charles Yuji Horioka. The "Real" Explanation of the Feldstein-Horioka Puzzle. National Bureau of Economic Research, 2016. http://dx.doi.org/10.3386/w22081.

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Rathke, Christian, and David F. Redmiles. Multiple Representation Perspectives for Supporting Explanation in Context. Defense Technical Information Center, 1993. http://dx.doi.org/10.21236/ada447671.

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