Typed states for the displayed outbound observations.
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Paper Citation Record · LEDGER
How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives
As of 22 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 2 inbound Pith citation observations for arXiv:2412.10220.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
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Pith citing papers itemized under the disclosed page cap.
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A source-named dated measurement, never combined with another source.
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Reference resolution
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External citation measurements
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Outbound references
Observation 66e8265a-312d-4d50-bcfb-756138f8f99a · outbound
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives Unresolved cited work
Reference 1
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives Flemish AI Research Program
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives Lundberg and Su-In Lee
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This paper cites ”why should i trust you?”: Explain- ing the predictions of any classifier.
How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives ”why should i trust you?”: Explain- ing the predictions of any classifier
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives A value for n-person games
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives The inadequacy of shapley values for explainabil- ity, 2023
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives Ex- plainability is not a game
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives Natural language explanations for machine learning classification decisions
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives Tell Me a Story! Narrative-Driven XAI with Large Language Models
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives LLMs for XAI: Future Directions for Explaining Explanations
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives Natural Language Counterfactual Explanations for Graphs Using Large Language Models
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives GraphNarrator: Generating Textual Explanations for Graph Neural Networks
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives GraphXAIN: Narratives to Explain Graph Neural Networks
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives Faithful and plausible natu- ral language explanations for image classifi- cation: A pipeline approach
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives In-Context Explainers: Harnessing LLMs for Explaining Black Box Models
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives Explaining ma- chine learning models with interactive natural language conversations using talktomodel
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives ME- TEOR: An automatic metric for MT evalu- ation with improved correlation with human judgments
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives Keane, Eoin M
Reference 19
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives Do models explain them- selves? Counterfactual simulatability of natural language explanations
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives BLEURT: Learning robust metrics for text generation
Reference 22
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives The disagreement problem in ex- plainable machine learning: A practitioner’s perspective
Reference 23
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives F ActScore: Fine-grained atomic evaluation of factual precision in long form text generation
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives PRobELM: Plausibility ranking evaluation for language models
Reference 25
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives A Survey on Natural Language Counterfactual Generation
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives You Can Generate It Again: Data-to-Text Generation with Verification and Correction Prompting
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives The Landscape of Emerging AI Agent Architectures for Reasoning, Planning, and Tool Calling: A Survey
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives Sentence- bert: Sentence embeddings using siamese bert-networks
Reference 29
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives Towards few-shot fact-checking via perplexity
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives GPT-4 Technical Report
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives Claude sonnet 3.5
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives Perplexity from PLM Is Unreliable for Evaluating Text Quality
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives Efficient Estimation of Word Representations in Vector Space
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives Mistral large 2
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives Adaptive chameleon or stubborn sloth: Revealing the behavior of large language models in knowledge conflicts
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives Context-faithful prompting for large language models
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives Llama 3 model card
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives The llama 3 herd of mod- els, 2024
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives Entity-based knowledge con- flicts in question answering
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives 19 org/CorpusID:201646309
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives URL https: //doi.org/10.24963/ijcai.2021/609
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives doi:10.1038/s42256- 023-00692-8
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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives URL https://huggingface.co/ mistralai/Mistral-Large-Instruct-2407
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Pith citing papers
Observation 3ecd87ac-c046-4939-811b-e477401c76f1 · inbound
A Two-Stage LLM Framework for Accessible and Verified XAI Explanations cites this paper.
A Two-Stage LLM Framework for Accessible and Verified XAI Explanations How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives
Reference 14
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On the Importance and Evaluation of Narrativity in Natural Language AI Explanations cites this paper.
On the Importance and Evaluation of Narrativity in Natural Language AI Explanations How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives
Reference 25
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