Related papers: Supported Abstract Argumentation for Case-Based Reasoning

Related papers

Splitting Assumption-Based Argumentation Frameworks [9.546922368727428]
Assumption-Based Argumentation (ABA) is a well-established formalism for modelling and reasoning over debates.<n>This paper investigates the concept of splitting on the knowledge base rather than on its graph-based instantiation.
arXiv Detail & Related papers (2026-04-30T14:56:26Z)
SAD: A Large-Scale Strategic Argumentative Dialogue Dataset [60.33125467375306]
In practice, argumentation is often realized as multi-turn dialogue.<n>We present the first large-scale textbfStrategic textbfArgumentative textbfDialogue dataset, consisting of 392,822 examples.
arXiv Detail & Related papers (2026-01-12T11:11:37Z)
Object-Centric Case-Based Reasoning via Argumentation [15.635254331470486]
Slot Attention Argumentation for Case-Based Reasoning (SAA-CBR) is a neuro-symbolic pipeline for image classification that integrates object-centric learning via a neural Slot Attention (SA) component with symbolic reasoning conducted by Abstract Argumentation for Case-Based Reasoning (AA-CBR)<n>We explore novel integrations of AA-CBR with the neural component, including feature combination strategies, casebase reduction via representative samples, novel count-based partial orders, and an application of Supported AA-CBR, a bipolar variant of AA-CBR.
arXiv Detail & Related papers (2025-09-30T19:04:27Z)
Revisiting Follow-the-Perturbed-Leader with Unbounded Perturbations in Bandit Problems [60.58442311545223]
Follow-the-Regularized-Leader (FTRL) policies have achieved Best-of-Both-Worlds (BOBW) results in various settings through hybrid regularizers.<n>We revisit classical FTRL-FTPL duality for unbounded perturbations and establish BOBW results for FTPL under a broad family of asymmetric Fr'echet-type perturbations.
arXiv Detail & Related papers (2025-08-26T02:12:18Z)
On Strong and Weak Admissibility in Non-Flat Assumption-Based Argumentation [4.583931917131698]
We study two prominent alternatives to the standard notion of admissibility from abstract argumentation.<n>We introduce the respective preferred, complete and grounded semantics for general (sometimes called non-flat) ABA.<n>We show that the central modularization property is maintained under classical, strong, and weak admissibility.
arXiv Detail & Related papers (2025-08-15T03:13:07Z)
Neuro-Argumentative Learning with Case-Based Reasoning [12.489784979345654]
We introduce Gradual Abstract Argumentation for Case-Based Reasoning (Gradual AA-CBR), a data-driven, neurosymbolic classification model.<n>Each argument in the debate is an observed case from the training data, favouring their labelling.<n>Cases attack or support those with opposing or agreeing labellings, with the strength of each argument and relationship learned through gradient-based methods.
arXiv Detail & Related papers (2025-05-21T16:49:47Z)
AlignRAG: Leveraging Critique Learning for Evidence-Sensitive Retrieval-Augmented Reasoning [61.28113271728859]
RAG has become a widely adopted paradigm for enabling knowledge-grounded large language models (LLMs)<n>Standard RAG pipelines often fail to ensure that model reasoning remains consistent with the evidence retrieved, leading to factual inconsistencies or unsupported conclusions.<n>In this work, we reinterpret RAG as Retrieval-Augmented Reasoning and identify a central but underexplored problem: textitReasoning Misalignment.
arXiv Detail & Related papers (2025-04-21T04:56:47Z)
On the Correspondence of Non-flat Assumption-based Argumentation and Logic Programming with Negation as Failure in the Head [20.981256612743145]
We show a correspondence between non-flat ABA and LPs with negation as failure in their head. We then extend this result to so-called set-stable ABA semantics, originally defined for the fragment of non-flat ABA called bipolar ABA. We showcase how to define set-stable semantics for LPs with negation as failure in their head and show the correspondence to set-stable ABA semantics.
arXiv Detail & Related papers (2024-05-15T15:10:03Z)
CASA: Causality-driven Argument Sufficiency Assessment [79.13496878681309]
We propose CASA, a zero-shot causality-driven argument sufficiency assessment framework. PS measures how likely introducing the premise event would lead to the conclusion when both the premise and conclusion events are absent. Experiments on two logical fallacy detection datasets demonstrate that CASA accurately identifies insufficient arguments.
arXiv Detail & Related papers (2024-01-10T16:21:18Z)
Technical Report on the Learning of Case Relevance in Case-Based Reasoning with Abstract Argumentation [14.755026411356315]
We show how relevance can be learnt automatically in practice with the help of decision trees. We also show that AA-CBR with decision-tree-based learning of case relevance results in a more compact representation than their decision tree counterparts.
arXiv Detail & Related papers (2023-10-30T15:01:41Z)
CAR: Conceptualization-Augmented Reasoner for Zero-Shot Commonsense Question Answering [56.592385613002584]
We propose Conceptualization-Augmented Reasoner (CAR) to tackle the task of zero-shot commonsense question answering. CAR abstracts a commonsense knowledge triple to many higher-level instances, which increases the coverage of CommonSense Knowledge Bases. CAR more robustly generalizes to answering questions about zero-shot commonsense scenarios than existing methods.
arXiv Detail & Related papers (2023-05-24T08:21:31Z)
Machine Reading Comprehension using Case-based Reasoning [92.51061570746077]
We present an accurate and interpretable method for answer extraction in machine reading comprehension. Our method builds upon the hypothesis that contextualized answers to similar questions share semantic similarities with each other.
arXiv Detail & Related papers (2023-05-24T07:09:56Z)
Non-flat ABA is an Instance of Bipolar Argumentation [23.655909692988637]
Assumption-based Argumentation (ABA) is a well-known structured argumentation formalism. A common restriction imposed on ABA frameworks (ABAFs) is that they are flat. No translation exists from general, possibly non-flat ABAFs into any kind of abstract argumentation formalism.
arXiv Detail & Related papers (2023-05-21T13:18:08Z)
Contextual bandits with concave rewards, and an application to fair ranking [108.48223948875685]
We present the first algorithm with provably vanishing regret for Contextual Bandits with Concave Rewards (CBCR) We derive a novel reduction from the CBCR regret to the regret of a scalar-reward problem. Motivated by fairness in recommendation, we describe a special case of CBCR with rankings and fairness-aware objectives.
arXiv Detail & Related papers (2022-10-18T16:11:55Z)
Counterfactual Variable Control for Robust and Interpretable Question Answering [57.25261576239862]
Deep neural network based question answering (QA) models are neither robust nor explainable in many cases. In this paper, we inspect such spurious "capability" of QA models using causal inference. We propose a novel approach called Counterfactual Variable Control (CVC) that explicitly mitigates any shortcut correlation.
arXiv Detail & Related papers (2020-10-12T10:09:05Z)
Cautious Monotonicity in Case-Based Reasoning with Abstract Argumentation [10.616061367794385]
We prove that $AAtext -CBR_succeq$ is not cautiously monotonic. We also prove that such variation is equivalent to using $AAtext -CBR_succeq$ with a restricted casebase.
arXiv Detail & Related papers (2020-07-10T10:08:30Z)

This list is automatically generated from the titles and abstracts of the papers in this site.