Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Interpreting CLIP with Sparse Linear Concept Embeddings (SpLiCE)
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2402.10376.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T00:46:32.566316Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-23T02:55:19.737143Z
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 e24d8c85-59a2-4ef4-b75a-56614f039731 · inbound
Beyond Cross-Modal Alignment: Measuring and Leveraging Modality Gap in Vision-Language Models cites this paper.
Beyond Cross-Modal Alignment: Measuring and Leveraging Modality Gap in Vision-Language Models Interpreting CLIP with Sparse Linear Concept Embeddings (SpLiCE)
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T02:55:19.739238Z
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.
Observation 5b7508f2-a33c-44c2-9209-593e178dffe3 · inbound
Quantifying Structure in CLIP Embeddings: A Statistical Framework for Concept Interpretation cites this paper.
Quantifying Structure in CLIP Embeddings: A Statistical Framework for Concept Interpretation Interpreting CLIP with Sparse Linear Concept Embeddings (SpLiCE)
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T00:46:32.566316Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d092a9c8-e782-4bf8-9063-2ac28c24e2ce · inbound
Beyond Accuracy: Metrics that Uncover What Makes a 'Good' Visual Descriptor cites this paper.
Beyond Accuracy: Metrics that Uncover What Makes a 'Good' Visual Descriptor Interpreting CLIP with Sparse Linear Concept Embeddings (SpLiCE)
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T20:13:45.126162Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 650bd057-0edb-4670-908b-4c980c962b1b · 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 Sparse Linear Concept Embeddings (SpLiCE)
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T15:17:08.525032Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 42675fb1-4117-4ba7-a699-37027d9c2c01 · inbound
Making Interpretable Discoveries from Unstructured Data: A High-Dimensional Multiple Hypothesis Testing Approach cites this paper.
Making Interpretable Discoveries from Unstructured Data: A High-Dimensional Multiple Hypothesis Testing Approach Interpreting CLIP with Sparse Linear Concept Embeddings (SpLiCE)
Reference 44
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T02:00:39.992703Z
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.
Observation 95269639-066c-4c2c-9a44-7c6451f8d7bb · inbound
Making Interpretable Discoveries from Unstructured Data: A High-Dimensional Multiple Hypothesis Testing Approach cites this paper.
Making Interpretable Discoveries from Unstructured Data: A High-Dimensional Multiple Hypothesis Testing Approach Interpreting CLIP with Sparse Linear Concept Embeddings (SpLiCE)
Reference 44
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T00:23:29.812352Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cf7125b6-8178-4fc8-a963-6e3876b2cf33 · inbound
Zero-Shot Textual Explanations via Translating Decision-Critical Features cites this paper.
Zero-Shot Textual Explanations via Translating Decision-Critical Features Interpreting CLIP with Sparse Linear Concept Embeddings (SpLiCE)
Reference 4
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T18:10:27.636126Z
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.
Observation 64c01702-8c85-4c30-a626-dff2d32539d6 · 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 Sparse Linear Concept Embeddings (SpLiCE)
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T04:33:52.123264Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8fc961ab-4d6f-4d86-bfe5-bc02fa66dd53 · inbound
Attributes Should Come from Images, Not Class Names: Distribution-Conditioned Attribute Selection for Vision-Language Models cites this paper.
Attributes Should Come from Images, Not Class Names: Distribution-Conditioned Attribute Selection for Vision-Language Models Interpreting CLIP with Sparse Linear Concept Embeddings (SpLiCE)
Reference 2
- Resolution
- malformed identifier
- no resolver link, observed 2026-08-01T14:41:33.468879Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.