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Explanation Generation

Papers

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Showing 151–200 of 235 papers

TitleStatusHype
Towards Generating Robust, Fair, and Emotion-Aware Explanations for Recommender Systems—0
Towards Human Cognition Level-based Experiment Design for Counterfactual Explanations (XAI)—0
Towards Reasoning-Aware Explainable VQA—0
Truth Table Deep Convolutional Neural Network, A New SAT-Encodable Architecture - Application To Complete Robustness—0
Unlocking the `Why' of Buying: Introducing a New Dataset and Benchmark for Purchase Reason and Post-Purchase Experience—0
Unsupervised Explanation Generation for Machine Reading Comprehension—0
Unsupervised Explanation Generation via Correct Instantiations—0
Weak Robust Compatibility Between Learning Algorithms and Counterfactual Explanation Generation Algorithms—0
What and How of Machine Learning Transparency: Building Bespoke Explainability Tools with Interoperable Algorithmic Components—0
What Does Evaluation of Explainable Artificial Intelligence Actually Tell Us? A Case for Compositional and Contextual Validation of XAI Building Blocks—0
When Backdoors Speak: Understanding LLM Backdoor Attacks Through Model-Generated Explanations—0
Which Linguist Invented the Lightbulb? Presupposition Verification for Question-Answering—0
`Why didn't you allocate this task to them?' Negotiation-Aware Explicable Task Allocation and Contrastive Explanation Generation—0
Why should I not follow you? Reasons For and Reasons Against in Responsible Recommender Systems—0
Why the Agent Made that Decision: Explaining Deep Reinforcement Learning with Vision Masks—0
XAI Benchmark for Visual Explanation—0
YNU-oxz at SemEval-2020 Task 4: Commonsense Validation Using BERT with Bidirectional GRU—0
Graph-Guided Textual Explanation Generation Framework—0
Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification—0
Hierarchical Aspect-guided Explanation Generation for Explainable Recommendation—0
Hierarchical Expertise-Level Modeling for User Specific Robot-Behavior Explanations—0
Hierarchical Interaction Summarization and Contrastive Prompting for Explainable Recommendations—0
How to Do Human Evaluation: Best Practices for User Studies in NLP—0
ICCV23 Visual-Dialog Emotion Explanation Challenge: SEU_309 Team Technical Report—0
Implementing Evidential Reasoning in Expert Systems—0
Improving Personalized Explanation Generation through Visualization—0
In Search for a SAT-friendly Binarized Neural Network Architecture—0
INTERACTION: A Generative XAI Framework for Natural Language Inference Explanations—0
Interpretability of Blackbox Machine Learning Models through Dataview Extraction and Shadow Model creation—0
InterPrompt: Interpretable Prompting for Interrelated Interpersonal Risk Factors in Reddit Posts—0
Is Explanation the Cure? Misinformation Mitigation in the Short Term and Long Term—0
Global Human-guided Counterfactual Explanations for Molecular Properties via Reinforcement LearningCode0
GNN2R: Weakly-Supervised Rationale-Providing Question Answering over Knowledge GraphsCode0
Preference Distillation for Personalized Generative RecommendationCode0
XEdgeAI: A Human-centered Industrial Inspection Framework with Data-centric Explainable Edge AI ApproachCode0
Generating High-Quality Explanations for Navigation in Partially-Revealed EnvironmentsCode0
Generating High-Quality Explanations for Navigation in Partially-Revealed EnvironmentsCode0
Explainable Debugger for Black-box Machine Learning ModelsCode0
Advisable Learning for Self-Driving Vehicles by Internalizing Observation-to-Action RulesCode0
Adapting to Change: Robust Counterfactual Explanations in Dynamic Data LandscapesCode0
Beyond Persuasion: Towards Conversational Recommender System with Credible ExplanationsCode0
RealFactBench: A Benchmark for Evaluating Large Language Models in Real-World Fact-CheckingCode0
Using Stratified Sampling to Improve LIME Image ExplanationsCode0
RecExplainer: Aligning Large Language Models for Explaining Recommendation ModelsCode0
IndMask: Inductive Explanation for Multivariate Time Series Black-Box ModelsCode0
A Framework for Learning Ante-hoc Explainable Models via ConceptsCode0
Analogy Generation by Prompting Large Language Models: A Case Study of InstructGPTCode0
Red Dragon AI at TextGraphs 2019 Shared Task: Language Model Assisted Explanation GenerationCode0
Explainable Agency by Revealing Suboptimality in Child-Robot Learning ScenariosCode0
Evaluating Evidence Attribution in Generated Fact Checking ExplanationsCode0
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All datasetsWHOOPS!CLEVR-Xe-SNLI-VEVCRVQA-X

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1VLIS (Lynx)Accuracy80—Unverified
2VLIS (LLaVA)Accuracy73—Unverified
3Ground-truth Caption -> GPT3 (Oracle)Human (%)68—Unverified
4Predicted Caption -> GPT3Human (%)33—Unverified
5BLIP2 FlanT5-XXL (Fine-tuned)Human (%)27—Unverified
6BLIP2 FlanT5-XL (Fine-tuned)Human (%)15—Unverified
7BLIP2 FlanT5-XXL (Zero-shot)Human (%)0—Unverified
#ModelMetricClaimedVerifiedStatus
1PJ-XB487.4—Unverified
2FMB478.8—Unverified
#ModelMetricClaimedVerifiedStatus
1OFA-XHuman Explanation Rating85.7—Unverified
2OFA-X-MTHuman Explanation Rating80.4—Unverified
#ModelMetricClaimedVerifiedStatus
1OFA-X-MTHuman Explanation Rating77.3—Unverified
2OFA-XHuman Explanation Rating68.9—Unverified
#ModelMetricClaimedVerifiedStatus
1OFA-XHuman Explanation Rating89.5—Unverified
2OFA-X-MTHuman Explanation Rating87.8—Unverified