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Paper Citation Record · LEDGER

Interpreting CLIP with Hierarchical Sparse Autoencoders

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2502.20578.

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

pith.paper-citation-record.v1
2502.20578 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T04:21:37.945531Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T10:29:45.381568Z

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 40e9ba27-afc7-41c9-b4ae-4c1f5104a87c · inbound

Model Science: getting serious about verification, explanation and control of AI systems cites this paper.

Model Science: getting serious about verification, explanation and control of AI systems Interpreting CLIP with Hierarchical Sparse Autoencoders

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-05T15:17:08.750129Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:17:08.750129Z digest=sha256:ff858514fff4d3c206dae961ba253a0a3756feb8c6f8a02500e464ad0a76ef11

Observation 649409cd-4791-4d95-9c02-9c21950b5840 · inbound

Beyond Semantics: Disentangling Information Scope in Sparse Autoencoders for CLIP cites this paper.

Beyond Semantics: Disentangling Information Scope in Sparse Autoencoders for CLIP Interpreting CLIP with Hierarchical Sparse Autoencoders

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-05-10T23:25:49.648993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T19:11:09.646784Z digest=sha256:2b3af01851b8087e0a2433e65bff2a969ac45f2b371b569aa0d0f2bffca70c6c

Observation d80e7d68-daff-45bf-92d1-45de7d58215f · 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 Interpreting CLIP with Hierarchical Sparse Autoencoders

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-05-11T06:51:18.661250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T17:25:34.942028Z digest=sha256:d3e43b6a8e5979740682de4fc0c04f71561252bade15623a4b0764e811231e8d

Observation 5e061a45-da44-4704-bea1-3eefb05f90e4 · inbound

LatentDiff: Scaling Semantic Dataset Comparison to Millions of Images cites this paper.

LatentDiff: Scaling Semantic Dataset Comparison to Millions of Images Interpreting CLIP with Hierarchical Sparse Autoencoders

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-05-11T15:21:06.342597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-09T20:16:30.677208Z digest=sha256:27d9df4645b4850c3ae5d5b0e099237f5bb174d1abef89c4c746da8b5cfd1ac2

Observation 00e8bf1b-99a6-4145-a3c7-71e00b2d5cd0 · inbound

Birds of a Feather Flock Together: Background-Invariant Representations via Linear Structure in VLMs cites this paper.

Birds of a Feather Flock Together: Background-Invariant Representations via Linear Structure in VLMs Interpreting CLIP with Hierarchical Sparse Autoencoders

Reference 46

Resolution
verified exact
arxiv_id, observed 2026-05-13T07:27:29.738280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-13T07:26:02.947081Z digest=sha256:82b78f6fde46a8c0d86496ae9e0a0c6ac3a645822c865f1dc0ecbe82b3580ec7

Observation 16347d71-bd03-4899-9d7a-6981aa767f7a · inbound

Conceptualizing Embeddings: Sparse Disentanglement for Vision-Language Models cites this paper.

Conceptualizing Embeddings: Sparse Disentanglement for Vision-Language Models Interpreting CLIP with Hierarchical Sparse Autoencoders

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-22T05:51:07.675541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-22T05:50:50.415408Z digest=sha256:201b2e09d3fab56a45530dcb673e6a198a5a191c22f8062d7e426ad7f43ead22

Observation 9d3f2067-430f-42d0-9510-4117d291f1c6 · inbound

Transcoders Trace Visual Grounding and Hallucinations in Vision-Language Models cites this paper.

Transcoders Trace Visual Grounding and Hallucinations in Vision-Language Models Interpreting CLIP with Hierarchical Sparse Autoencoders

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-05-25T06:25:23.797271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-25T06:22:09.828982Z digest=sha256:719fbbf4a265fe343df96074318cc664da0f676bcee43b8c6a6e52f6bfe3e894

Observation 2359aad6-4f2c-4d69-8887-4b6c1ad3352b · inbound

Do Sparse Autoencoders Learn Meaningful Concept Hierarchies? cites this paper.

Do Sparse Autoencoders Learn Meaningful Concept Hierarchies? Interpreting CLIP with Hierarchical Sparse Autoencoders

Reference 52

Resolution
verified exact
arxiv_id, observed 2026-07-04T10:29:45.383322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-26T08:46:48.220801Z digest=sha256:d2b62056bae7de25a40f6393b5e79fee22c1d68760afbd3761f91dab76f0303e

Observation 80d6cde7-00a8-44c1-910a-a427fec3fbcc · 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 Interpreting CLIP with Hierarchical Sparse Autoencoders

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-02T04:33:54.132265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T04:33:54.132265Z digest=sha256:a938c1d147d5d8a50459afb220da5ba593a97ae0d078d7ed203e239f70822899

Observation 042d60b7-a730-412b-81af-7bb13f4d123c · inbound

Measuring Monosemanticity in Sparse Autoencoders via Latent Activation Coherence cites this paper.

Measuring Monosemanticity in Sparse Autoencoders via Latent Activation Coherence Interpreting CLIP with Hierarchical Sparse Autoencoders

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-01T17:08:25.162245Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T17:08:25.162245Z digest=sha256:070111151e758d01a68557308576a081d26d3dd6a71b7d45912b3c3f4ac7cdca

Observation 3258d3f7-0d1a-4378-a531-552f699071fb · inbound

V-FIND: Revealing the Intrinsic Forgery Knowledge Encoded in Video Forgery Detectors cites this paper.

V-FIND: Revealing the Intrinsic Forgery Knowledge Encoded in Video Forgery Detectors Interpreting CLIP with Hierarchical Sparse Autoencoders

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-08T04:21:37.945531Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T04:21:37.945531Z digest=sha256:83bf50306b2bcf012d6a9465a0690711d7404abf1ce712696e00e78a753a2559

Observation c855e95e-b08c-4704-9ee6-55ec85f0598a · inbound

IRIS: A Visual Cortex-Inspired Framework for Analyzing Orientation Selectivity in Vision Transformers cites this paper.

IRIS: A Visual Cortex-Inspired Framework for Analyzing Orientation Selectivity in Vision Transformers Interpreting CLIP with Hierarchical Sparse Autoencoders

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T04:50:37.397809Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:50:37.397809Z digest=sha256:90321f59db4cc1f23909f0aaa1c887753c7797c69dc10dbd77faa219dd8066d2