Paper Citation Record · LEDGER

How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives

As of 13 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.

pith.paper-citation-record.v1
2412.10220 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

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measured 49 of 49 standing notices

One-hop event checks from named stored sources.

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measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T15:25:46.925378Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-11T10:36:02.611276Z

Reference resolution

47 of 47 outbound references displayed

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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 Unresolved cited work

Reference 2

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This paper cites Flemish AI Research Program.

How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives Flemish AI Research Program

Reference 3

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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives Lundberg and Su-In Lee

Reference 4

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Observation 066475d5-bf48-49a3-b03e-2192637f8faf · outbound

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

Reference 5

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This paper cites A value for n-person games.

How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives A value for n-person games

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This paper cites The inadequacy of shapley values for explainabil- ity, 2023.

How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives The inadequacy of shapley values for explainabil- ity, 2023

Reference 7

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Observation 9ad79fb9-c267-417e-85d8-edbd5a8324eb · outbound

This paper cites Ex- plainability is not a game.

How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives Ex- plainability is not a game

Reference 8

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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

Reference 9

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Observation deceb318-f251-4882-a7e4-c8a7c4ff4d12 · outbound

This paper cites Tell Me a Story! Narrative-Driven XAI with Large Language Models.

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

Reference 10

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This paper cites LLMs for XAI: Future Directions for Explaining Explanations.

How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives LLMs for XAI: Future Directions for Explaining Explanations

Reference 11

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This paper cites Natural Language Counterfactual Explanations for Graphs Using Large Language Models.

How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives Natural Language Counterfactual Explanations for Graphs Using Large Language Models

Reference 12

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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

Reference 14

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This paper cites Faithful and plausible natu- ral language explanations for image classifi- cation: A pipeline approach.

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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This paper cites In-Context Explainers: Harnessing LLMs for Explaining Black Box Models.

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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This paper cites Explaining ma- chine learning models with interactive natural language conversations using talktomodel.

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

Reference 17

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This paper cites ME- TEOR: An automatic metric for MT evalu- ation with improved correlation with human judgments.

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

Reference 20

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How good is my story? Towards quantitative metrics for evaluating LLM-generated XAI narratives Unresolved cited work

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This paper cites BLEURT: Learning robust metrics for text generation.

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

Reference 24

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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

Reference 26

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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

Reference 27

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This paper cites The Landscape of Emerging AI Agent Architectures for Reasoning, Planning, and Tool Calling: A Survey.

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

Reference 28

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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 Zhang, Mark Har- man, and Meng Wang

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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 Unresolved cited work

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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

Reference 2407

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Pith citing papers

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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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