SOTAVerified

Explanation Generation

Papers

Showing 126150 of 235 papers

TitleStatusHype
Improving Personalized Explanation Generation through Visualization0
Towards Reasoning-Aware Explainable VQA0
A Framework for Generating Explanations from Temporal Personal Health Data0
In Search for a SAT-friendly Binarized Neural Network Architecture0
INTERACTION: A Generative XAI Framework for Natural Language Inference Explanations0
Interpretability of Blackbox Machine Learning Models through Dataview Extraction and Shadow Model creation0
InterPrompt: Interpretable Prompting for Interrelated Interpersonal Risk Factors in Reddit Posts0
Is Explanation the Cure? Misinformation Mitigation in the Short Term and Long Term0
Joint Mind Modeling for Explanation Generation in Complex Human-Robot Collaborative Tasks0
Causal Screening to Interpret Graph Neural Networks0
Calibrating Trust of Multi-Hop Question Answering Systems with Decompositional Probes0
Why the Agent Made that Decision: Explaining Deep Reinforcement Learning with Vision Masks0
Truth Table Deep Convolutional Neural Network, A New SAT-Encodable Architecture - Application To Complete Robustness0
XAI Benchmark for Visual Explanation0
Breaking Common Sense: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images0
LLMExplainer: Large Language Model based Bayesian Inference for Graph Explanation Generation0
LLM-GAN: Construct Generative Adversarial Network Through Large Language Models For Explainable Fake News Detection0
Boosting Knowledge Graph-based Recommendations through Confidence-Aware Augmentation with Large Language Models0
Towards LLM-guided Causal Explainability for Black-box Text Classifiers0
LLMs for Coding and Robotics Education0
Logic-Scaffolding: Personalized Aspect-Instructed Recommendation Explanation Generation using LLMs0
M6-Rec: Generative Pretrained Language Models are Open-Ended Recommender Systems0
MemeIntel: Explainable Detection of Propagandistic and Hateful Memes0
Active entailment encoding for explanation tree construction using parsimonious generation of hard negatives0
Mixed Logical and Probabilistic Reasoning for Planning and Explanation Generation in Robotics0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1VLIS (Lynx)Accuracy80Unverified
2VLIS (LLaVA)Accuracy73Unverified
3Ground-truth Caption -> GPT3 (Oracle)Human (%)68Unverified
4Predicted Caption -> GPT3Human (%)33Unverified
5BLIP2 FlanT5-XXL (Fine-tuned)Human (%)27Unverified
6BLIP2 FlanT5-XL (Fine-tuned)Human (%)15Unverified
7BLIP2 FlanT5-XXL (Zero-shot)Human (%)0Unverified
#ModelMetricClaimedVerifiedStatus
1PJ-XB487.4Unverified
2FMB478.8Unverified
#ModelMetricClaimedVerifiedStatus
1OFA-XHuman Explanation Rating85.7Unverified
2OFA-X-MTHuman Explanation Rating80.4Unverified
#ModelMetricClaimedVerifiedStatus
1OFA-X-MTHuman Explanation Rating77.3Unverified
2OFA-XHuman Explanation Rating68.9Unverified
#ModelMetricClaimedVerifiedStatus
1OFA-XHuman Explanation Rating89.5Unverified
2OFA-X-MTHuman Explanation Rating87.8Unverified