SOTAVerified

Explanation Generation

Papers

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Showing 101–150 of 235 papers

TitleStatusHype
Artwork Explanation in Large-scale Vision Language Models—0
Unlocking the `Why' of Buying: Introducing a New Dataset and Benchmark for Purchase Reason and Post-Purchase Experience—0
Explainability for Machine Learning Models: From Data Adaptability to User Perception—0
Explaining Veracity Predictions with Evidence Summarization: A Multi-Task Model ApproachCode0
LLMs for Coding and Robotics Education—0
Sentiment-enhanced Graph-based Sarcasm Explanation in DialogueCode0
Explaining latent representations of generative models with large multimodal models—0
Eclectic Rule Extraction for Explainability of Deep Neural Network based Intrusion Detection Systems—0
Logic-Scaffolding: Personalized Aspect-Instructed Recommendation Explanation Generation using LLMs—0
Mismatch Quest: Visual and Textual Feedback for Image-Text MisalignmentCode0
Assertion Enhanced Few-Shot Learning: Instructive Technique for Large Language Models to Generate Educational Explanations—0
GNN2R: Weakly-Supervised Rationale-Providing Question Answering over Knowledge GraphsCode0
InterPrompt: Interpretable Prompting for Interrelated Interpersonal Risk Factors in Reddit Posts—0
From Wrong To Right: A Recursive Approach Towards Vision-Language Explanation—0
RecExplainer: Aligning Large Language Models for Explaining Recommendation Models—0
Is Explanation the Cure? Misinformation Mitigation in the Short Term and Long Term—0
Counterfactual Explanation Generation with s(CASP)—0
Explaining Interactions Between Text SpansCode0
XAI Benchmark for Visual Explanation—0
Generating Explanations in Medical Question-Answering by Expectation Maximization Inference over Evidence—0
Towards LLM-guided Causal Explainability for Black-box Text Classifiers—0
Exploring Iterative Enhancement for Improving Learnersourced Multiple-Choice Question Explanations with Large Language ModelsCode0
Reward Engineering for Generating Semi-structured ExplanationCode0
Dynamic MOdularized Reasoning for Compositional Structured Explanation Generation—0
Affective Visual Dialog: A Large-Scale Benchmark for Emotional Reasoning Based on Visually Grounded Conversations—0
RecMind: Large Language Model Powered Agent For Recommendation—0
Explaining with Attribute-based and Relational Near Misses: An Interpretable Approach to Distinguishing Facial Expressions of Pain and Disgust—0
Adapting to Change: Robust Counterfactual Explanations in Dynamic Data LandscapesCode0
Sustainable transparency in Recommender Systems: Bayesian Ranking of Images for ExplainabilityCode0
Explaining Competitive-Level Programming Solutions using LLMs—0
Effects of Explanation Specificity on Passengers in Autonomous Driving—0
Beyond Labels: Empowering Human Annotators with Natural Language Explanations through a Novel Active-Learning ArchitectureCode0
Distinguish Before Answer: Generating Contrastive Explanation as Knowledge for Commonsense Question Answering—0
Explainable Recommender with Geometric Information Bottleneck—0
Textual Explanations for Automated Commentary DrivingCode0
Efficiently Explaining CSPs with Unsatisfiable Subset Optimization (extended algorithms and examples)—0
Empowering CAM-Based Methods with Capability to Generate Fine-Grained and High-Faithfulness ExplanationsCode0
Breaking Common Sense: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images—0
Parallel Sentence-Level Explanation Generation for Real-World Low-Resource Scenarios—0
Towards a Unified Model for Generating Answers and Explanations in Visual Question Answering—0
Explanation Regeneration via Information BottleneckCode0
Unsupervised Explanation Generation via Correct Instantiations—0
Towards Reasoning-Aware Explainable VQA—0
Motif-guided Time Series Counterfactual Explanations—0
Towards Human Cognition Level-based Experiment Design for Counterfactual Explanations (XAI)—0
ExPUNations: Augmenting Puns with Keywords and ExplanationsCode0
CLEAR: Generative Counterfactual Explanations on Graphs—0
COFFEE: Counterfactual Fairness for Personalized Text Generation in Explainable Recommendation—0
Explanations from Large Language Models Make Small Reasoners Better—0
Formal Semantic Geometry over Transformer-based Variational AutoEncoder—0
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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