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Paper Citation Record · LEDGER

A Concept-Based Explainability Framework for Large Multimodal Models

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2406.08074.

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

pith.paper-citation-record.v1
2406.08074 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T14:23:23.764331Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T16:51:06.991227Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation e657c38f-9a23-4c4b-99c8-5df856ed30c5 · inbound

Devils in Middle Layers of Large Vision-Language Models: Interpreting, Detecting and Mitigating Object Hallucinations via Attention Lens cites this paper.

Devils in Middle Layers of Large Vision-Language Models: Interpreting, Detecting and Mitigating Object Hallucinations via Attention Lens A Concept-Based Explainability Framework for Large Multimodal Models

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-12T14:23:23.764331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:23:23.764331Z digest=sha256:17ae904d069eb8cb62e9ee120210c8ffd8defc79c7b5f6fbe7fd8a338de1e55f

Observation 0e90062f-60ed-447b-97a6-977b09e920cf · inbound

TACO: Training-free Sound Prompted Segmentation via Semantically Constrained Audio-visual CO-factorization cites this paper.

TACO: Training-free Sound Prompted Segmentation via Semantically Constrained Audio-visual CO-factorization A Concept-Based Explainability Framework for Large Multimodal Models

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-12T04:23:41.520270Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:23:41.520270Z digest=sha256:228c84baf7d473aa8632cd2e13ee9f0345a77ee8982ebd921c381dccb3e24d40

Observation 141cc58c-c02f-4707-8a6e-92e4b4dcd9a1 · inbound

Explainable and Interpretable Multimodal Large Language Models: A Comprehensive Survey cites this paper.

Explainable and Interpretable Multimodal Large Language Models: A Comprehensive Survey A Concept-Based Explainability Framework for Large Multimodal Models

Reference 153

Resolution
unresolved
no resolver link, observed 2026-08-11T23:54:23.896012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:54:23.896012Z digest=sha256:5edf6404890a7d85cb14010031226d567628d50f194d023439ba1fe22421a68f

Observation 8552d8f9-5f70-4bb9-b1d0-b42c85d36d3e · inbound

A framework for analyzing concept representations in neural models cites this paper.

A framework for analyzing concept representations in neural models A Concept-Based Explainability Framework for Large Multimodal Models

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-11T16:51:06.994336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-09T14:49:22.776209Z digest=sha256:86787c2416e91c18551474d177b567d28491b538e8e3d8597d9e6d369bfec0a7

Observation 292a6ea8-bc1c-4be5-a638-edb9c0ebff5e · inbound

The Hyperspherical Geometry of CLIP Latent Space: A Semantic Mixture Model cites this paper.

The Hyperspherical Geometry of CLIP Latent Space: A Semantic Mixture Model A Concept-Based Explainability Framework for Large Multimodal Models

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-02T04:33:53.356441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T04:33:53.356441Z digest=sha256:2e15a740382e5d9f15dbacfd25f2742b2e6ebb8bf0f85de240db2f776ac3389e