Paper Citation Record · LEDGER

Rethinking Explainability in the Era of Multimodal AI

As of 11 August 2026, this Paper Citation Record lists 69 of 69 outbound references and 5 inbound Pith citation observations for arXiv:2506.13060.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.13060 v1

Coverage vector

measured 69 of 69 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:42:29.029561Z

measured 74 of 74 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T00:02:59.058102Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T01:56:27.425584Z

Reference resolution

69 of 69 outbound references displayed

verified exact1
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3af1c08a-96a0-4a21-a3c9-502787544d37 · outbound

This paper cites Phi-3 technical report: A highly capable language model locally on your phone.

Rethinking Explainability in the Era of Multimodal AI Phi-3 technical report: A highly capable language model locally on your phone

Reference 1

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Observation e9e195e2-7211-4c68-b92a-70e74d175dd7 · outbound

This paper cites Explaining image classifiers by removing input features using generative models.

Rethinking Explainability in the Era of Multimodal AI Explaining image classifiers by removing input features using generative models

Reference 2

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This paper cites Rethinking stability for attribution-based explanations.

Rethinking Explainability in the Era of Multimodal AI Rethinking stability for attribution-based explanations

Reference 3

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Observation dac50e95-3d98-4e19-9891-d72c32325bb1 · outbound

This paper cites Openxai: Towards a transparent evaluation of model explanations.

Rethinking Explainability in the Era of Multimodal AI Openxai: Towards a transparent evaluation of model explanations

Reference 4

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Observation ba26f6be-8964-426e-ac0a-ff778ea3e087 · outbound

This paper cites Probing gnn explainers: A rigorous theoretical and empirical analysis of gnn explanation methods.

Rethinking Explainability in the Era of Multimodal AI Probing gnn explainers: A rigorous theoretical and empirical analysis of gnn explanation methods

Reference 5

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Observation 0d929ea4-407b-42d5-b2ee-e84abde6576f · outbound

This paper cites Evaluating explainability for graph neural networks.

Rethinking Explainability in the Era of Multimodal AI Evaluating explainability for graph neural networks

Reference 6

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Observation 68a648b3-10ac-47c0-9a67-1d34044f88a8 · outbound

This paper cites Faithfulness vs.

Rethinking Explainability in the Era of Multimodal AI Faithfulness vs

Reference 7

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Observation e80cc26b-6ede-4b8c-b393-ea0cbb901c9f · outbound

This paper cites On the robustness of interpretability methods.

Rethinking Explainability in the Era of Multimodal AI On the robustness of interpretability methods

Reference 8

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Rethinking Explainability in the Era of Multimodal AI Unresolved cited work

Reference 9

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Observation b30ca549-e23c-44cd-b4d1-2a5e5bf906ef · outbound

This paper cites Bottom-up and top-down attention for image captioning and visual question answering.

Rethinking Explainability in the Era of Multimodal AI Bottom-up and top-down attention for image captioning and visual question answering

Reference 10

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Observation 8b72fe31-4c9f-41bd-a6f8-07b01590d325 · outbound

This paper cites Mechanistic interpretability for ai safety--a review.

Rethinking Explainability in the Era of Multimodal AI Mechanistic interpretability for ai safety--a review

Reference 11

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Observation e9b0ca62-89ea-4dad-96fa-822135289895 · outbound

This paper cites Interpreting clip with sparse linear concept embeddings (splice).

Rethinking Explainability in the Era of Multimodal AI Interpreting clip with sparse linear concept embeddings (splice)

Reference 12

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Observation 9330670c-f551-4adf-8165-41ac0533e532 · outbound

This paper cites A systematic review of natural language processing applied to radiology reports.

Rethinking Explainability in the Era of Multimodal AI A systematic review of natural language processing applied to radiology reports

Reference 13

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Observation 71c8d4e4-7cbe-4f11-8b8a-63ddd07767e2 · outbound

This paper cites Fleurs: Few-shot learning evaluation of universal representations of speech.

Rethinking Explainability in the Era of Multimodal AI Fleurs: Few-shot learning evaluation of universal representations of speech

Reference 14

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Observation ff5ae73b-a5ee-420c-80b2-f58a98d2e890 · outbound

This paper cites Sparse autoencoders find highly interpretable features in language models.

Rethinking Explainability in the Era of Multimodal AI Sparse autoencoders find highly interpretable features in language models

Reference 15

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Observation b83aca68-c528-4830-a315-44dc01d2732c · outbound

This paper cites A survey of the state of explainable AI for natural language processing.

Rethinking Explainability in the Era of Multimodal AI A survey of the state of explainable AI for natural language processing

Reference 16

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Observation 5c4b732f-1d9d-44a5-a94e-5e23da05d5cc · outbound

This paper cites Interpretable explanations of black boxes by meaningful perturbation.

Rethinking Explainability in the Era of Multimodal AI Interpretable explanations of black boxes by meaningful perturbation

Reference 17

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Observation dd7c68a8-f836-4f07-8ee9-9d1bc5b81bec · outbound

This paper cites Attention in natural language processing.

Rethinking Explainability in the Era of Multimodal AI Attention in natural language processing

Reference 18

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Observation 2a22c5e4-73e5-4af5-8ac1-aa13a8c52e87 · outbound

This paper cites Scaling and evaluating sparse autoencoders.

Rethinking Explainability in the Era of Multimodal AI Scaling and evaluating sparse autoencoders

Reference 19

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This paper cites Multimodal neurons in artificial neural networks.

Rethinking Explainability in the Era of Multimodal AI Multimodal neurons in artificial neural networks

Reference 20

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This paper cites Localizing model behavior with path patching.

Rethinking Explainability in the Era of Multimodal AI Localizing model behavior with path patching

Reference 21

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Observation 58b5f494-cf54-4156-b688-bddedc945355 · outbound

This paper cites circuit-tracer.

Rethinking Explainability in the Era of Multimodal AI circuit-tracer

Reference 22

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Observation 53e35e70-3a07-4041-b1ee-a02db5051133 · outbound

This paper cites Sparse autoencoders can interpret randomly initialized transformers.

Rethinking Explainability in the Era of Multimodal AI Sparse autoencoders can interpret randomly initialized transformers

Reference 23

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This paper cites How to use and interpret activation patching.

Rethinking Explainability in the Era of Multimodal AI How to use and interpret activation patching

Reference 24

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Observation 8e6f692f-2762-40d5-ae90-1f88b12c21d3 · outbound

This paper cites Gpt-4o system card.

Rethinking Explainability in the Era of Multimodal AI Gpt-4o system card

Reference 25

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Observation f0aa6866-6edb-45d1-8aac-b804a1dcec0c · outbound

This paper cites Attention is not explanation.

Rethinking Explainability in the Era of Multimodal AI Attention is not explanation

Reference 26

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This paper cites Towards better explanations of class activation mapping.

Rethinking Explainability in the Era of Multimodal AI Towards better explanations of class activation mapping

Reference 27

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Observation 1658005b-6abd-4e3c-b28c-f6c0d9339249 · outbound

This paper cites See what you are told: Visual attention sink in large multimodal models.

Rethinking Explainability in the Era of Multimodal AI See what you are told: Visual attention sink in large multimodal models

Reference 28

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This paper cites Are sparse autoencoders useful? a case study in sparse probing.

Rethinking Explainability in the Era of Multimodal AI Are sparse autoencoders useful? a case study in sparse probing

Reference 29

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Observation 76fd0b06-a54c-44fd-9a18-11a8cf2a2735 · outbound

This paper cites Interpretability beyond feature attribution: Quantitative testing with concept activation vectors (tcav).

Rethinking Explainability in the Era of Multimodal AI Interpretability beyond feature attribution: Quantitative testing with concept activation vectors (tcav)

Reference 30

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This paper cites Visual explanations from hadamard product in multimodal deep networks.

Rethinking Explainability in the Era of Multimodal AI Visual explanations from hadamard product in multimodal deep networks

Reference 31

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This paper cites Sparse autoencoders work on attention layer outputs.

Rethinking Explainability in the Era of Multimodal AI Sparse autoencoders work on attention layer outputs

Reference 32

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This paper cites Concept bottleneck models.

Rethinking Explainability in the Era of Multimodal AI Concept bottleneck models

Reference 33

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Rethinking Explainability in the Era of Multimodal AI Unresolved cited work

Reference 34

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This paper cites The llama 4 herd: The beginning of a new era of natively multimodal ai innovation, 2025.

Rethinking Explainability in the Era of Multimodal AI The llama 4 herd: The beginning of a new era of natively multimodal ai innovation, 2025

Reference 35

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This paper cites Dime: Fine-grained interpretations of multimodal models via disentangled local explanations.

Rethinking Explainability in the Era of Multimodal AI Dime: Fine-grained interpretations of multimodal models via disentangled local explanations

Reference 36

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This paper cites Towards principled evaluations of sparse autoencoders for interpretability and control.

Rethinking Explainability in the Era of Multimodal AI Towards principled evaluations of sparse autoencoders for interpretability and control

Reference 37

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Rethinking Explainability in the Era of Multimodal AI K-sparse autoencoders

Reference 38

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This paper cites Cora Dataset , 2017.

Rethinking Explainability in the Era of Multimodal AI Cora Dataset , 2017

Reference 39

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This paper cites Dual attention networks for multimodal reasoning and matching.

Rethinking Explainability in the Era of Multimodal AI Dual attention networks for multimodal reasoning and matching

Reference 40

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This paper cites Attribution patching: Activation patching at industrial scale.

Rethinking Explainability in the Era of Multimodal AI Attribution patching: Activation patching at industrial scale

Reference 41

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This paper cites Towards interpreting visual information processing in vision-language models.

Rethinking Explainability in the Era of Multimodal AI Towards interpreting visual information processing in vision-language models

Reference 42

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This paper cites Interpreting gpt: the logit lens — lesswrong, 2020.

Rethinking Explainability in the Era of Multimodal AI Interpreting gpt: the logit lens — lesswrong, 2020

Reference 43

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This paper cites Sparse autoencoders enable scalable and reliable circuit identification in language models.

Rethinking Explainability in the Era of Multimodal AI Sparse autoencoders enable scalable and reliable circuit identification in language models

Reference 44

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This paper cites Orchestrating explainable artificial intelligence for multimodal and longitudinal data in medical imaging.

Rethinking Explainability in the Era of Multimodal AI Orchestrating explainable artificial intelligence for multimodal and longitudinal data in medical imaging

Reference 45

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This paper cites Multimodal explanations: Justifying decisions and pointing to the evidence.

Rethinking Explainability in the Era of Multimodal AI Multimodal explanations: Justifying decisions and pointing to the evidence

Reference 46

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Observation 4090a390-ff36-49e6-b878-5d2e5f2043e3 · outbound

This paper cites Perception test: A diagnostic benchmark for multimodal video models.

Rethinking Explainability in the Era of Multimodal AI Perception test: A diagnostic benchmark for multimodal video models

Reference 47

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This paper cites why should i trust you?.

Rethinking Explainability in the Era of Multimodal AI why should i trust you?

Reference 48

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Observation 04b749df-81b9-485d-8747-39cd821ff174 · outbound

This paper cites Multimodal explainable artificial intelligence: A comprehensive review of methodological advances and future research directions.

Rethinking Explainability in the Era of Multimodal AI Multimodal explainable artificial intelligence: A comprehensive review of methodological advances and future research directions

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:29.273333Z

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This paper cites Grad-cam: visual explanations from deep networks via gradient-based localization.

Rethinking Explainability in the Era of Multimodal AI Grad-cam: visual explanations from deep networks via gradient-based localization

Reference 50

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Observation d47a6440-9889-4321-bc0f-404e956b03d2 · outbound

This paper cites Towards a systematic evaluation of hallucinations in large-vision language models, 2025.

Rethinking Explainability in the Era of Multimodal AI Towards a systematic evaluation of hallucinations in large-vision language models, 2025

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:29.251109Z

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Observation f7a6c207-7c7d-489a-85ba-61204051517d · outbound

This paper cites A survey on sparse autoencoders: Interpreting the internal mechanisms of large language models.

Rethinking Explainability in the Era of Multimodal AI A survey on sparse autoencoders: Interpreting the internal mechanisms of large language models

Reference 52

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Observation a04aec4a-c21a-4f5a-9ffe-21c92752d966 · outbound

This paper cites Explain and improve: Lrp-inference fine-tuning for image captioning models.

Rethinking Explainability in the Era of Multimodal AI Explain and improve: Lrp-inference fine-tuning for image captioning models

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:29.228568Z

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Observation db11ca8e-3712-45e5-9120-7b91e1f67191 · outbound

This paper cites A review of multimodal explainable artificial intelligence: Past, present and future.

Rethinking Explainability in the Era of Multimodal AI A review of multimodal explainable artificial intelligence: Past, present and future

Reference 54

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Observation 9478184d-e968-46cf-8c69-23d1654c5cef · outbound

This paper cites Axiomatic attribution for deep networks.

Rethinking Explainability in the Era of Multimodal AI Axiomatic attribution for deep networks

Reference 55

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This paper cites Gemini: a family of highly capable multimodal models.

Rethinking Explainability in the Era of Multimodal AI Gemini: a family of highly capable multimodal models

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:29.202394Z

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Observation a4423586-1adb-4559-a1aa-cd6104720e8d · outbound

This paper cites true features.

Rethinking Explainability in the Era of Multimodal AI true features

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:29.192345Z

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Observation 26f833ad-74c0-4781-a7ba-d512b5e24463 · outbound

This paper cites Interpretable multi-modal hate speech detection.

Rethinking Explainability in the Era of Multimodal AI Interpretable multi-modal hate speech detection

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:29.182634Z

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Observation 13d2d4eb-e3db-46fa-b42e-579c28644c3d · outbound

This paper cites Llms as zero-shot graph learners: Alignment of gnn representations with llm token embeddings.

Rethinking Explainability in the Era of Multimodal AI Llms as zero-shot graph learners: Alignment of gnn representations with llm token embeddings

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:29.172041Z

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Observation c4f7bf7a-9a19-401a-ad58-5cfb88c2a18e · outbound

This paper cites Interpretability-based multimodal convolutional neural networks for skin lesion diagnosis.

Rethinking Explainability in the Era of Multimodal AI Interpretability-based multimodal convolutional neural networks for skin lesion diagnosis

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:29.162541Z

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Observation 42b9148e-0952-4fb0-ae29-825dcfbe4189 · outbound

This paper cites M2lens: Visualizing and explaining multimodal models for sentiment analysis.

Rethinking Explainability in the Era of Multimodal AI M2lens: Visualizing and explaining multimodal models for sentiment analysis

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:29.153262Z

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Observation ebc623f6-6642-4b47-9c22-8659859ed20f · outbound

This paper cites Logitlens4llms: Extending logit lens analysis to modern large language models.

Rethinking Explainability in the Era of Multimodal AI Logitlens4llms: Extending logit lens analysis to modern large language models

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:29.143582Z

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Observation 9bbe7916-e983-4faf-8c4e-eee4039a93e8 · outbound

This paper cites Measuring cross-modal interactions in multimodal models.

Rethinking Explainability in the Era of Multimodal AI Measuring cross-modal interactions in multimodal models

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:29.133461Z

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Observation a6605486-fd69-4385-8619-8359b4bcf3e8 · outbound

This paper cites Attention is not not explanation.

Rethinking Explainability in the Era of Multimodal AI Attention is not not explanation

Reference 64

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This paper cites Audio-text models do not yet leverage natural language.

Rethinking Explainability in the Era of Multimodal AI Audio-text models do not yet leverage natural language

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:29.116161Z

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Observation 0872db54-30ab-424c-bda3-b1f90a1b4014 · outbound

This paper cites Visual entailment: A novel task for fine-grained image understanding.

Rethinking Explainability in the Era of Multimodal AI Visual entailment: A novel task for fine-grained image understanding

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:29.106824Z

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Observation 09e3969f-c253-407b-9aa3-6b7149e17005 · outbound

This paper cites Gnnexplainer: Generating explanations for graph neural networks.

Rethinking Explainability in the Era of Multimodal AI Gnnexplainer: Generating explanations for graph neural networks

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:29.097057Z

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Observation 1f6d3cff-855f-42a1-9d6c-3a80b1249434 · outbound

This paper cites Towards best practices of activation patching in language models: Metrics and methods.

Rethinking Explainability in the Era of Multimodal AI Towards best practices of activation patching in language models: Metrics and methods

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:29.087636Z

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Observation 595c6cf6-5b44-4e92-9567-798b5846efc9 · outbound

This paper cites Vlm ^ 2 -bench: A closer look at how well vlms implicitly link explicit matching visual cues.

Rethinking Explainability in the Era of Multimodal AI Vlm ^ 2 -bench: A closer look at how well vlms implicitly link explicit matching visual cues

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T00:42:29.076856Z

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Pith citing papers

Observation 849a45c3-d30a-4246-b015-ef3208f6beeb · inbound

Decoding the Multimodal Maze: A Systematic Review on the Adoption of Explainability in Multimodal Attention-based Models cites this paper.

Decoding the Multimodal Maze: A Systematic Review on the Adoption of Explainability in Multimodal Attention-based Models Rethinking Explainability in the Era of Multimodal AI

Reference 132

Resolution: verified exact; arxiv_id, observed 2026-05-19T00:36:56.258662Z

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Observation 3f2e7f19-a183-44d1-b173-0ae46d6dd0bc · inbound

Decoding the Multimodal Maze: A Systematic Review on the Adoption of Explainability in Multimodal Attention-based Models cites this paper.

Decoding the Multimodal Maze: A Systematic Review on the Adoption of Explainability in Multimodal Attention-based Models Rethinking Explainability in the Era of Multimodal AI

Reference 132

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Observation e959f135-5479-437f-8687-0b2463a80929 · inbound

Measuring Cross-Modal Synergy: A Benchmark for VLM Explainability cites this paper.

Measuring Cross-Modal Synergy: A Benchmark for VLM Explainability Rethinking Explainability in the Era of Multimodal AI

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-22T06:06:08.728672Z

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Observation 7fa8a946-a63e-4618-b93c-fd9082e53411 · inbound

When Graph Tokens Sink: A Mechanistic Analysis of Graph Language Models cites this paper.

When Graph Tokens Sink: A Mechanistic Analysis of Graph Language Models Rethinking Explainability in the Era of Multimodal AI

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-07-02T01:56:27.435247Z

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Observation 78325e5c-d441-4171-ba4c-b955b76fb338 · inbound

CHARM: Charge Calibration and Acoustic Rescue for LLM-based Multimodal Sarcasm Detection cites this paper.

CHARM: Charge Calibration and Acoustic Rescue for LLM-based Multimodal Sarcasm Detection Rethinking Explainability in the Era of Multimodal AI

Reference 23

Resolution: unresolved; no resolver link, observed 2026-07-14T07:04:04.812401Z

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