Cover Image

ContextualSHAP : Enhancing SHAP Explanations Through Contextual Language Generation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Dwiyanti, Latifa, Wibisono, Sergio Ryan, Nambo, Hidetaka
Format:	Preprint
Published:	2025
Subjects:	Artificial Intelligence Human-Computer Interaction Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

From Prototypes to Sparse ECG Explanations: SHAP-Driven Counterfactuals for Multivariate Time-Series Multi-class Classification
by: Mozolewski, Maciej, et al.
Published: (2025)

Dynamic Trust Calibration Using Contextual Bandits
by: Henrique, Bruno M., et al.
Published: (2025)

Classroom Simulacra: Building Contextual Student Generative Agents in Online Education for Learning Behavioral Simulation
by: Xu, Songlin, et al.
Published: (2025)

A Mobile Application Front-End for Presenting Explainable AI Results in Diabetes Risk Estimation
by: Willson, Bernardus, et al.
Published: (2025)

Catch Me if You Search: When Contextual Web Search Results Affect the Detection of Hallucinations
by: Nahar, Mahjabin, et al.
Published: (2025)

A Case Study on Contextual Machine Translation in a Professional Scenario of Subtitling
by: Vincent, Sebastian, et al.
Published: (2024)

Towards Human-Centered Construction Robotics: A Reinforcement Learning-Driven Companion Robot for Contextually Assisting Carpentry Workers
by: Wu, Yuning, et al.
Published: (2024)

Counterfactual Explanation-Based Badminton Motion Guidance Generation Using Wearable Sensors
by: Seong, Minwoo, et al.
Published: (2024)

MetaExplainer: A Framework to Generate Multi-Type User-Centered Explanations for AI Systems
by: Chari, Shruthi, et al.
Published: (2025)

Introducing User Feedback-based Counterfactual Explanations (UFCE)
by: Suffian, Muhammad, et al.
Published: (2024)

Explaining News Bias Detection: A Comparative SHAP Analysis of Transformer Model Decision Mechanisms
by: Ghosh, Himel
Published: (2025)

Visual-Conversational Interface for Evidence-Based Explanation of Diabetes Risk Prediction
by: Samimi, Reza, et al.
Published: (2025)

Evaluation of Human-Understandability of Global Model Explanations using Decision Tree
by: Sivaprasad, Adarsa, et al.
Published: (2023)

Explanation through Reward Model Reconciliation using POMDP Tree Search
by: Kraske, Benjamin D., et al.
Published: (2023)

Petal-X: Human-Centered Visual Explanations to Improve Cardiovascular Risk Communication
by: Rojo, Diego, et al.
Published: (2024)

Does Explanation Correctness Matter? Linking Computational XAI Evaluation to Human Understanding
by: Baer, Gregor, et al.
Published: (2026)

Designing User-Centric Behavioral Interventions to Prevent Dysglycemia with Novel Counterfactual Explanations
by: Arefeen, Asiful, et al.
Published: (2023)

Diagrammatization and Abduction to Improve AI Interpretability With Domain-Aligned Explanations for Medical Diagnosis
by: Lim, Brian Y., et al.
Published: (2023)

DiConStruct: Causal Concept-based Explanations through Black-Box Distillation
by: Moreira, Ricardo, et al.
Published: (2024)

A User Study on Contrastive Explanations for Multi-Effector Temporal Planning with Non-Stationary Costs
by: Liu, Xiaowei, et al.
Published: (2024)

Context-Aware Visualization for Explainable AI Recommendations in Social Media: A Vision for User-Aligned Explanations
by: Alkhateeb, Banan, et al.
Published: (2025)

Interactive Example-based Explanations to Improve Health Professionals' Onboarding with AI for Human-AI Collaborative Decision Making
by: Lee, Min Hun, et al.
Published: (2024)

The Art of Saying No: Contextual Noncompliance in Language Models
by: Brahman, Faeze, et al.
Published: (2024)

Enhancing the Interpretability of SHAP Values Using Large Language Models
by: Zeng, Xianlong, et al.
Published: (2024)

Properties and Challenges of LLM-Generated Explanations
by: Kunz, Jenny, et al.
Published: (2024)

LLMs for XAI: Future Directions for Explaining Explanations
by: Zytek, Alexandra, et al.
Published: (2024)

Robots That Know What to Ask: Recovering Misaligned Rewards through Targeted Explanations
by: Merker, Helena, et al.
Published: (2026)

Diffusion Explainer: Visual Explanation for Text-to-image Stable Diffusion
by: Lee, Seongmin, et al.
Published: (2023)

LitPivot: Developing Well-Situated Research Ideas Through Dynamic Contextualization and Critique within the Literature Landscape
by: Kambhamettu, Hita, et al.
Published: (2026)

Lucia: A Temporal Computing Platform for Contextual Intelligence
by: Lin, Weizhe, et al.
Published: (2024)

Multi-Modal Financial Time-Series Retrieval Through Latent Space Projections
by: Bamford, Tom, et al.
Published: (2023)

TalkWithMachines: Enhancing Human-Robot Interaction for Interpretable Industrial Robotics Through Large/Vision Language Models
by: Abbas, Ammar N., et al.
Published: (2024)

Evaluating Contextually Personalized Programming Exercises Created with Generative AI
by: Logacheva, Evanfiya, et al.
Published: (2024)

HelpViz: Automatic Generation of Contextual Visual MobileTutorials from Text-Based Instructions
by: Zhong, Mingyuan, et al.
Published: (2021)

Evaluating Explanations: An Explanatory Virtues Framework for Mechanistic Interpretability -- The Strange Science Part I.ii
by: Ayonrinde, Kola, et al.
Published: (2025)

MedSyn: Enhancing Diagnostics with Human-AI Collaboration
by: Sayin, Burcu, et al.
Published: (2025)

GlyTwin: Digital Twin for Glucose Control in Type 1 Diabetes Through Optimal Behavioral Modifications Using Patient-Centric Counterfactuals
by: Arefeen, Asiful, et al.
Published: (2025)

Reinforcement Learning-Enhanced Procedural Generation for Dynamic Narrative-Driven AR Experiences
by: Joshi, Aniruddha Srinivas
Published: (2025)

ClickAgent: Enhancing UI Location Capabilities of Autonomous Agents
by: Hoscilowicz, Jakub, et al.
Published: (2024)

Toward Ownership Understanding of Objects: Active Question Generation with Large Language Model and Probabilistic Generative Model
by: Hashimoto, Saki, et al.
Published: (2025)