Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-05T13:18:54.729910Z
Paper Citation Record · LEDGER
Causal Interpretation of Sparse Autoencoder Features in Vision
As of 10 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 2 inbound Pith citation observations for arXiv:2509.00749.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-20T18:34:32.616965Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-20T18:38:52.830071Z
Reference resolution
12 of 12 outbound references displayed
- verified exact1
- verified fuzzy6
- unresolved5
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 1bc092a8-f31c-4229-bbb7-ca9b6b8daaf0 · outbound
This paper cites write newline.
Causal Interpretation of Sparse Autoencoder Features in Vision write newline
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T13:18:53.317206Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c52f3fee-5905-469d-b81a-90ab67540a3e · outbound
This paper cites AttnLRP: Attention-Aware Layer-Wise Relevance Propagation for Transformers.
Causal Interpretation of Sparse Autoencoder Features in Vision AttnLRP: Attention-Aware Layer-Wise Relevance Propagation for Transformers
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T13:18:53.385709Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7af6b646-ac2a-471c-a75f-f6242c419e62 · outbound
This paper cites Reproducible scaling laws for contrastive language-image learning.
Causal Interpretation of Sparse Autoencoder Features in Vision Reproducible scaling laws for contrastive language-image learning
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T13:18:53.512067Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 80e25fcf-fc9e-4aca-8c2a-e1864dfe198e · outbound
This paper cites Respect the model: Fine-grained and Robust Explanation with Sharing Ratio Decomposition.
Causal Interpretation of Sparse Autoencoder Features in Vision Respect the model: Fine-grained and Robust Explanation with Sharing Ratio Decomposition
Reference 4
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T13:18:54.988121Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation fe885505-326e-491a-96b5-e40ed7dffa7b · outbound
This paper cites Sparse autoencoders find highly interpretable features in language models.
Causal Interpretation of Sparse Autoencoder Features in Vision Sparse autoencoders find highly interpretable features in language models
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T13:18:53.762149Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0119348a-9783-4458-8c85-43cd5e9b5d23 · outbound
This paper cites Sparse autoencoders reveal selective remapping of visual concepts during adaptation.
Causal Interpretation of Sparse Autoencoder Features in Vision Sparse autoencoders reveal selective remapping of visual concepts during adaptation
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T13:18:56.459202Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation abfebcba-45cf-4990-80dd-7c992a50904c · outbound
This paper cites A unified approach to interpreting model predictions.
Causal Interpretation of Sparse Autoencoder Features in Vision A unified approach to interpreting model predictions
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T13:18:54.025129Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6cc49a37-4544-4602-bbf3-5f42481fcd53 · outbound
This paper cites Sparse autoencoders learn monosemantic features in vision-language models, 2025.
Causal Interpretation of Sparse Autoencoder Features in Vision Sparse autoencoders learn monosemantic features in vision-language models, 2025
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T13:18:56.138272Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation e83ec275-b9bc-4d03-95e3-9bc987630caf · outbound
This paper cites Evaluating the visualization of what a deep neural network has learned.
Causal Interpretation of Sparse Autoencoder Features in Vision Evaluating the visualization of what a deep neural network has learned
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T13:18:55.887963Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 7ba564cc-eafd-4e48-ba22-2cc96ba106b5 · outbound
This paper cites Sparse autoencoders for scientifically rigorous interpretation of vision models, 2025.
Causal Interpretation of Sparse Autoencoder Features in Vision Sparse autoencoders for scientifically rigorous interpretation of vision models, 2025
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T13:18:55.671653Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 04ab4746-f347-4919-b950-c458ac9f9b09 · outbound
This paper cites Axiomatic attribution for deep networks.
Causal Interpretation of Sparse Autoencoder Features in Vision Axiomatic attribution for deep networks
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T13:18:55.450947Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 6e794d40-fa50-4f06-b454-4bfff9a298f9 · outbound
This paper cites Interpreting CLIP with hierarchical sparse autoencoders.
Causal Interpretation of Sparse Autoencoder Features in Vision Interpreting CLIP with hierarchical sparse autoencoders
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T13:18:55.223686Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Pith citing papers
Observation 7d948b78-2e59-438a-8eb1-e60e590932bf · inbound
Beyond Semantics: Disentangling Information Scope in Sparse Autoencoders for CLIP cites this paper.
Beyond Semantics: Disentangling Information Scope in Sparse Autoencoders for CLIP Causal Interpretation of Sparse Autoencoder Features in Vision
Reference 17
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T23:25:49.694167Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation d216a604-90bf-499f-af0c-9b3365a96ccc · inbound
Sparse Autoencoders enable Robust and Interpretable Fine-tuning of CLIP models cites this paper.
Sparse Autoencoders enable Robust and Interpretable Fine-tuning of CLIP models Causal Interpretation of Sparse Autoencoder Features in Vision
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T18:38:52.832107Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.