Paper Citation Record · LEDGER

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations

As of 19 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 1 inbound Pith citation observation for arXiv:2508.01728.

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

pith.paper-citation-record.v1
2508.01728 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T05:30:19.549471Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T17:25:34.942028Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T06:51:17.927543Z

Reference resolution

42 of 42 outbound references displayed

verified exact1
verified fuzzy31
unresolved9
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation aca572df-e05f-488c-be7b-5bf44839617c · outbound

This paper cites From attribution maps to human-understandable explanations through concept rele- vance propagation.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations From attribution maps to human-understandable explanations through concept rele- vance propagation

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:30:28.254424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 53deeab9-1922-4117-b51d-34734b021aee · outbound

This paper cites Cub-200-resnet50 pretrained model,.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations Cub-200-resnet50 pretrained model,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:30:28.153281Z

Source-reported events for the cited work

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Observation 2a6b4e44-b66c-4ab2-8ba0-c299a3effb4c · outbound

This paper cites Network dissection: Quantifying inter- pretability of deep visual representations.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations Network dissection: Quantifying inter- pretability of deep visual representations

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:30:28.031353Z

Source-reported events for the cited work

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Observation 529f8bf5-7800-46aa-9a1b-ab100c5f43d1 · outbound

This paper cites Understanding the role of individual units in a deep neural network.Proceedings of the National Academy of Sciences, 2020.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations Understanding the role of individual units in a deep neural network.Proceedings of the National Academy of Sciences, 2020

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:30:27.917773Z

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Observation cb80ef1b-f059-47e7-90bd-f5407208918b · outbound

This paper cites Rewiring the connectome: evidence and effects.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations Rewiring the connectome: evidence and effects

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:30:27.835577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 94021550-ea7e-4179-8b62-87341fec68aa · outbound

This paper cites Under- standing distributed representations of concepts in deep neu- ral networks without supervision.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations Under- standing distributed representations of concepts in deep neu- ral networks without supervision

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:30:27.734948Z

Source-reported events for the cited work

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Observation d6eec324-7779-4b4f-aaa7-099e1e52df8d · outbound

This paper cites Towards automated circuit discovery for mechanistic interpretability.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations Towards automated circuit discovery for mechanistic interpretability

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:30:27.633563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 593048a1-e30d-43f1-a342-4f464c232644 · outbound

This paper cites Knowledge Neurons in Pretrained Transformers.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations Knowledge Neurons in Pretrained Transformers

Reference 8

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Observation 2bcb6528-865b-4bcc-a52a-9a4f3d06b7b3 · outbound

This paper cites Models for ex- ceedances over high thresholds.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations Models for ex- ceedances over high thresholds

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:30:27.540609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9e9edd5f-ed8b-4681-8128-795c3143d0d8 · outbound

This paper cites From Colors to Classes: Emergence of Concepts in Vision Transformers.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations From Colors to Classes: Emergence of Concepts in Vision Transformers

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T05:30:17.192036Z

Source-reported events for the cited work

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Observation 69a5868d-9af8-41b1-9b42-e25c7c5514ca · outbound

This paper cites Craft: Concept recursive activation factoriza- tion for explainability.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations Craft: Concept recursive activation factoriza- tion for explainability

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:30:25.325250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9dc7d14d-21f8-4c0d-8ef8-b25a5a27fffa · outbound

This paper cites Transformer Feed-Forward Layers Are Key-Value Memories.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations Transformer Feed-Forward Layers Are Key-Value Memories

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T05:30:17.342129Z

Source-reported events for the cited work

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Observation c4f41fef-be04-4235-b67a-2f3855032c83 · outbound

This paper cites Towards automatic concept-based explanations.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations Towards automatic concept-based explanations

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:30:24.759261Z

Source-reported events for the cited work

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Observation a96433e0-90de-4e39-bc25-192d853097ed · outbound

This paper cites Extreme value theory: an introduction.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations Extreme value theory: an introduction

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:30:24.548709Z

Source-reported events for the cited work

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Observation 2b813e02-80f0-45d6-84da-5ca60e1d75c8 · outbound

This paper cites The organization of behavior: A neu- ropsychological theory.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations The organization of behavior: A neu- ropsychological theory

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:30:24.336320Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 699bfa0b-84a8-4a9e-81e2-6d8d3214ce22 · outbound

This paper cites Natural language descriptions of deep visual features.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations Natural language descriptions of deep visual features

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:30:24.140682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 44bb40ae-549f-4628-8d82-c4d05b40b835 · outbound

This paper cites Distributed representations.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations Distributed representations

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:30:23.961212Z

Source-reported events for the cited work

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Observation 9d9e1a85-d8e0-41c9-8d66-2484965160dc · outbound

This paper cites Learning distributed representations of concepts.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations Learning distributed representations of concepts

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:30:23.805576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 77dc114e-8b1c-4a69-915c-60b01d911435 · outbound

This paper cites Synaptic plasticity-dependent competition rule influences memory formation.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations Synaptic plasticity-dependent competition rule influences memory formation

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:30:23.614074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c05bf929-9731-4766-908f-715ae3f5d3b6 · outbound

This paper cites Identifying inter- pretable subspaces in image representations.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations Identifying inter- pretable subspaces in image representations

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:30:23.423703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2650f7c7-5fbb-4109-b93c-5e335d05dd4d · outbound

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

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations Interpretability be- yond feature attribution: Quantitative testing with concept activation vectors (tcav)

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:30:23.223992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 336e7821-3259-49c1-b649-1919438feeba · outbound

This paper cites Visual concept connectome (vcc): Open world con- cept discovery and their interlayer connections in deep mod- els.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations Visual concept connectome (vcc): Open world con- cept discovery and their interlayer connections in deep mod- els

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:30:23.033053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 621375bf-7253-4349-a371-effe22060895 · outbound

This paper cites Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language Models.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language Models

Reference 23

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Source-reported events for the cited work

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Observation 67e05cb8-4606-4e83-bbf6-c697cd1de977 · outbound

This paper cites Locating and editing factual associations in gpt.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations Locating and editing factual associations in gpt

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:30:22.842605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation cb3f6534-f411-4b48-9d1d-a491a9bd0a0c · outbound

This paper cites Oikarinen and Tsui-Wei Weng.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations Oikarinen and Tsui-Wei Weng

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:30:22.644098Z

Source-reported events for the cited work

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Observation f63ace80-5ded-4c25-af4a-887f1a872d80 · outbound

This paper cites An overview of early vision in inceptionv1.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations An overview of early vision in inceptionv1

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:30:22.459107Z

Source-reported events for the cited work

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Observation 638d498c-8ba2-43ff-b5e0-c9609c80ec83 · outbound

This paper cites RISE: Randomized Input Sampling for Explanation of Black-box Models.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations RISE: Randomized Input Sampling for Explanation of Black-box Models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T05:30:18.387339Z

Source-reported events for the cited work

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Observation 6cf85008-e7e6-4ab7-b532-1fbfc044c435 · outbound

This paper cites Statistical inference using extreme order statistics.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations Statistical inference using extreme order statistics

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:30:22.306848Z

Source-reported events for the cited work

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Observation c44f7308-9aa0-4372-b3bc-28f37e7f40ce · outbound

This paper cites Automatic Discovery of Visual Circuits.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations Automatic Discovery of Visual Circuits

Reference 29

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Observation 5107e09f-2a1a-4c0d-9a0a-061ab399a8b1 · outbound

This paper cites Distributed represen- tations in memory: insights from functional brain imaging.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations Distributed represen- tations in memory: insights from functional brain imaging

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:30:22.057095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1ab76a02-771b-4925-885c-09519cb07d29 · outbound

This paper cites Parallel distributed processing, volume 1: Ex- plorations in the microstructure of cognition: Foundations.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations Parallel distributed processing, volume 1: Ex- plorations in the microstructure of cognition: Foundations

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:30:21.832231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7afbf468-7920-4f3a-a34e-9b234c9bdf82 · outbound

This paper cites Genetic mecha- nisms underlying the evolution of connectivity in the human cortex.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations Genetic mecha- nisms underlying the evolution of connectivity in the human cortex

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:30:21.525213Z

Source-reported events for the cited work

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Observation 2e8cac97-f2f3-4269-a1cc-f2409e1d9d27 · outbound

This paper cites The sankey diagram in energy and material flow management: part ii: methodology and current applica- tions.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations The sankey diagram in energy and material flow management: part ii: methodology and current applica- tions

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:30:21.333569Z

Source-reported events for the cited work

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Observation 9c63f71f-6cb6-4177-b19b-0fc0dc38f590 · outbound

This paper cites Exploratory data analysis.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations Exploratory data analysis

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:30:21.029623Z

Source-reported events for the cited work

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Observation 04c35aab-a854-4818-8335-133f4806664e · outbound

This paper cites The caltech-ucsd birds-200-2011 dataset.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations The caltech-ucsd birds-200-2011 dataset

Reference 35

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Observation caf6b1a8-31c9-4e19-a95f-2ca8352ca1b5 · outbound

This paper cites Hint: Hierarchical neuron concept explainer.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations Hint: Hierarchical neuron concept explainer

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:30:20.731475Z

Source-reported events for the cited work

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Observation 500d88f3-9155-479b-b9c1-1b0dec2ce635 · outbound

This paper cites Interpretability in the Wild: a Circuit for Indirect Object Identification in GPT-2 small.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations Interpretability in the Wild: a Circuit for Indirect Object Identification in GPT-2 small

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-06T05:30:19.195128Z

Source-reported events for the cited work

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Observation 9e6af155-9ca4-44dc-99ca-f9f6e6d5c2d7 · outbound

This paper cites Discovering Influential Neuron Path in Vision Transformers.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations Discovering Influential Neuron Path in Vision Transformers

Reference 38

Resolution: verified exact; local_arxiv, observed 2026-08-06T05:30:19.973692Z

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Observation d0e1cac4-ae91-47ab-9dcf-294dffb948b5 · outbound

This paper cites Neuroscience: Exploring the brain: By mark f.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations Neuroscience: Exploring the brain: By mark f

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:30:20.358119Z

Source-reported events for the cited work

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Observation 94f90055-a314-44c5-a40c-eaec65e21269 · outbound

This paper cites What part of the neural network does this? understanding lstms by measuring and dissecting neurons.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations What part of the neural network does this? understanding lstms by measuring and dissecting neurons

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T05:30:20.219283Z

Source-reported events for the cited work

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Observation 5d863535-13c6-44fa-9f7d-9ce53377e6e1 · outbound

This paper cites Functional faithfulness in the wild: Circuit discovery with differentiable computation graph pruning.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations Functional faithfulness in the wild: Circuit discovery with differentiable computation graph pruning

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-06T05:30:19.507706Z

Source-reported events for the cited work

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Observation 228ad1bd-d040-489a-b548-b141065bc5f4 · outbound

This paper cites Revisiting the Importance of Individual Units in CNNs via Ablation.

Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations Revisiting the Importance of Individual Units in CNNs via Ablation

Reference 42

Resolution: malformed identifier; no resolver link, observed 2026-08-06T05:30:19.549471Z

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Pith citing papers

Observation d6901e74-2eec-49d3-a75f-b0296c4658fe · inbound

Latent Anomaly Knowledge Excavation: Unveiling Sparse Sensitive Neurons in Vision-Language Models cites this paper.

Latent Anomaly Knowledge Excavation: Unveiling Sparse Sensitive Neurons in Vision-Language Models Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:51:17.998881Z

Source-reported events for the cited work

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