Paper Citation Record · LEDGER

Learning Multi-Level Features with Matryoshka Sparse Autoencoders

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 48 inbound Pith citation observations for arXiv:2503.17547.

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

pith.paper-citation-record.v1
2503.17547 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 48 of 48 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:43:15.410159Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

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External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation dfd3766a-5b5b-4a41-998c-1079183e7dfb · inbound

The Origins of Representation Manifolds in Large Language Models cites this paper.

The Origins of Representation Manifolds in Large Language Models Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 8

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Source-reported events for the cited work

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Observation 4f48c707-9311-4ae1-a416-49bbd095833e · inbound

Position: Mechanistic Interpretability Should Prioritize Feature Consistency in SAEs cites this paper.

Position: Mechanistic Interpretability Should Prioritize Feature Consistency in SAEs Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T14:02:59.051713Z

Source-reported events for the cited work

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Observation ac1a8290-6e72-4e91-b7c7-0be9661cf1d1 · inbound

Factual Self-Awareness in Language Models: Representation, Robustness, and Scaling cites this paper.

Factual Self-Awareness in Language Models: Representation, Robustness, and Scaling Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 29

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Source-reported events for the cited work

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Observation 50c042c0-98a9-45b1-80ca-1b9e07b552cf · inbound

Train One Sparse Autoencoder Across Multiple Sparsity Budgets to Preserve Interpretability and Accuracy cites this paper.

Train One Sparse Autoencoder Across Multiple Sparsity Budgets to Preserve Interpretability and Accuracy Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 4

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Source-reported events for the cited work

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Observation 988e5cf1-f642-444d-b522-b722a0b3931b · inbound

Incorporating Hierarchical Semantics in Sparse Autoencoder Architectures cites this paper.

Incorporating Hierarchical Semantics in Sparse Autoencoder Architectures Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 2025

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Source-reported events for the cited work

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Observation 10b64f59-8fbe-4986-b96d-8f7e92bc671d · inbound

BlueGlass: A Framework for Composite AI Safety cites this paper.

BlueGlass: A Framework for Composite AI Safety Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 14

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Source-reported events for the cited work

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Observation ae2e7e69-ddb3-45ce-9d79-37508d945371 · inbound

Insights into a radiology-specialised multimodal large language model with sparse autoencoders cites this paper.

Insights into a radiology-specialised multimodal large language model with sparse autoencoders Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 9

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Source-reported events for the cited work

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Observation dd93be14-1c3c-4914-b46a-4a3b389dff4b · inbound

Sparse but Wrong: Incorrect L0 Leads to Incorrect Features in Sparse Autoencoders cites this paper.

Sparse but Wrong: Incorrect L0 Leads to Incorrect Features in Sparse Autoencoders Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 2024

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Source-reported events for the cited work

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Observation 8a58229d-fb4e-4aa8-8b74-8d83bd295050 · inbound

Sealing The Backdoor: Unlearning Adversarial Text Triggers In Diffusion Models Using Knowledge Distillation cites this paper.

Sealing The Backdoor: Unlearning Adversarial Text Triggers In Diffusion Models Using Knowledge Distillation Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 51

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Observation 2c4f7495-47a9-48a4-a50d-a1c8e379146f · inbound

Safe-SAIL: Towards a Fine-grained Safety Landscape of Large Language Models via Sparse Autoencoder Interpretation Framework cites this paper.

Safe-SAIL: Towards a Fine-grained Safety Landscape of Large Language Models via Sparse Autoencoder Interpretation Framework Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-18T18:16:43.795195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7a8ad517-1171-4701-8618-4be505441825 · inbound

Towards Atoms of Large Language Models cites this paper.

Towards Atoms of Large Language Models Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0349ddfd-a514-451c-9bfa-85a6ee2afee6 · inbound

Mechanistic Interpretability of Antibody Language Models Using SAEs cites this paper.

Mechanistic Interpretability of Antibody Language Models Using SAEs Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 2021

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Source-reported events for the cited work

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Observation f9a389fd-ec55-4b82-bf1f-d86919984c36 · inbound

PolySAE: Modeling Feature Interactions in Sparse Autoencoders via Polynomial Decoding cites this paper.

PolySAE: Modeling Feature Interactions in Sparse Autoencoders via Polynomial Decoding Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-03T05:48:08.046788Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ade5bafd-71bb-4827-a4e3-777439b4889c · inbound

Stable and Steerable Sparse Autoencoders with Weight Regularization cites this paper.

Stable and Steerable Sparse Autoencoders with Weight Regularization Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54b3f94b-a4ce-461d-ae04-256f59d7ed20 · inbound

Improving Robustness In Sparse Autoencoders via Masked Regularization cites this paper.

Improving Robustness In Sparse Autoencoders via Masked Regularization Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 8

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T23:55:51.694717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7d293bf9-e144-4fcf-9ca0-d8fdde9a88ca · inbound

Dictionary-Aligned Concept Control for Safeguarding Multimodal LLMs cites this paper.

Dictionary-Aligned Concept Control for Safeguarding Multimodal LLMs Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 11

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T05:35:57.369684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ba62daa4-e5e8-4f4c-9eef-566affe5ee70 · inbound

From Tokens to Concepts: Leveraging SAE for SPLADE cites this paper.

From Tokens to Concepts: Leveraging SAE for SPLADE Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-11T15:11:07.816562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e57f8934-c8c5-4bd3-876e-c60283122d21 · inbound

From Tokens to Concepts: Leveraging SAE for SPLADE cites this paper.

From Tokens to Concepts: Leveraging SAE for SPLADE Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-07-04T23:30:12.038645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9a842034-6079-415b-b9c7-dd8349be1e47 · inbound

Tree SAE: Learning Hierarchical Feature Structures in Sparse Autoencoders cites this paper.

Tree SAE: Learning Hierarchical Feature Structures in Sparse Autoencoders Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 3

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T03:15:54.324345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2ef61865-a337-4a47-8efc-dd15032e932a · inbound

Tree SAE: Learning Hierarchical Feature Structures in Sparse Autoencoders cites this paper.

Tree SAE: Learning Hierarchical Feature Structures in Sparse Autoencoders Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 3

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T07:16:25.309504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c308cd1a-c6c9-4d08-8174-c8c08ee1d91a · inbound

Tensor Product Representation Probes Reveal Shared Structure Across Linear Directions cites this paper.

Tensor Product Representation Probes Reveal Shared Structure Across Linear Directions Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 3

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T07:16:30.283057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4535f8b1-44e4-43b3-be19-a86ad1d49825 · inbound

Do Language Models Encode Knowledge of Linguistic Constraint Violations? cites this paper.

Do Language Models Encode Knowledge of Linguistic Constraint Violations? Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-13T06:27:24.757936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 85f509fb-4327-4872-b295-db4d6f68327a · inbound

Do Language Models Encode Knowledge of Linguistic Constraint Violations? cites this paper.

Do Language Models Encode Knowledge of Linguistic Constraint Violations? Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-15T05:45:05.715255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4212971a-d40a-4f76-add1-5c3847628cf5 · inbound

WriteSAE: Sparse Autoencoders for Recurrent State cites this paper.

WriteSAE: Sparse Autoencoders for Recurrent State Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 59

Resolution: metadata mismatch; arxiv_id, observed 2026-05-14T20:59:28.815697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 050f8176-bb23-4cb4-9104-f83203f5186e · inbound

WriteSAE: Sparse Autoencoders for Recurrent State cites this paper.

WriteSAE: Sparse Autoencoders for Recurrent State Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 59

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T04:59:45.210865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5d789e60-1136-4590-985d-75bb3bca272d · inbound

WriteSAE: Sparse Autoencoders for Recurrent State cites this paper.

WriteSAE: Sparse Autoencoders for Recurrent State Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 59

Resolution: metadata mismatch; arxiv_id, observed 2026-05-20T21:53:47.204449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 538895f4-9bdb-4016-bc9d-a3bd480da609 · inbound

WriteSAE: Sparse Autoencoders for Recurrent State cites this paper.

WriteSAE: Sparse Autoencoders for Recurrent State Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-21T07:49:50.149450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 73bbb688-d283-4122-9be1-700e48d61927 · inbound

Descriptive Collision in Sparse Autoencoder Auto-Interpretability: When One Explanation Describes Many Features cites this paper.

Descriptive Collision in Sparse Autoencoder Auto-Interpretability: When One Explanation Describes Many Features Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-14T20:27:58.925563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d94daa48-28f1-402c-bbaa-fe58c648ac45 · inbound

The Rate-Distortion-Polysemanticity Tradeoff in SAEs cites this paper.

The Rate-Distortion-Polysemanticity Tradeoff in SAEs Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 5

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T21:15:04.074818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ef29cbe4-5fbc-4e64-8cdd-37a10931f375 · inbound

Are Sparse Autoencoder Benchmarks Reliable? cites this paper.

Are Sparse Autoencoder Benchmarks Reliable? Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 5

Resolution: metadata mismatch; arxiv_id, observed 2026-05-20T12:43:16.816953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f9ab20dc-5b04-44e6-96d4-3a87316872b0 · inbound

Probing for Representation Manifolds in Superposition cites this paper.

Probing for Representation Manifolds in Superposition Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 43

Resolution: metadata mismatch; arxiv_id, observed 2026-05-20T11:48:15.054342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1aa28f09-e98d-4638-8563-a6a8a45b07d2 · inbound

Matryoshka Concept Bottleneck Models cites this paper.

Matryoshka Concept Bottleneck Models Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-06-30T18:04:57.912098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 20488253-1250-4e39-92ef-a6aa019f498b · inbound

Sign-Aware Gated Sparse Autoencoders: Modeling Anticorrelated Features with Bi-Jump-ReLU Activations cites this paper.

Sign-Aware Gated Sparse Autoencoders: Modeling Anticorrelated Features with Bi-Jump-ReLU Activations Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 33

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T14:23:30.768006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation afbcad70-c0ed-4f22-9375-fbd162d4110c · inbound

Sign-Aware Gated Sparse Autoencoders: Modeling Anticorrelated Features with Bi-Jump-ReLU Activations cites this paper.

Sign-Aware Gated Sparse Autoencoders: Modeling Anticorrelated Features with Bi-Jump-ReLU Activations Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 32

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc41b531-7c3f-463f-8791-120635d82074 · inbound

Subspace-Aware Sparse Autoencoders for Effective Mechanistic Interpretability cites this paper.

Subspace-Aware Sparse Autoencoders for Effective Mechanistic Interpretability Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 36

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T02:11:29.051237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 85168b2f-b7ad-4caa-97bf-d31e57e4f8f9 · inbound

MM-Matryoshka: Towards Budget-Elastic Visual Document Retrieval via a 2D Multimodal Matryoshka Training Framework cites this paper.

MM-Matryoshka: Towards Budget-Elastic Visual Document Retrieval via a 2D Multimodal Matryoshka Training Framework Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 62

Resolution: verified exact; arxiv_id, observed 2026-07-02T07:26:45.679414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation aeadf5f0-deac-45d1-9fed-5caa5f84796c · inbound

VFUSE: Virulent Feature Understanding with Sparse autoEncoders cites this paper.

VFUSE: Virulent Feature Understanding with Sparse autoEncoders Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 14

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T00:57:29.990683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation aeb88284-f81f-4280-b1ef-a3b12b0169bb · inbound

ICA Lens: Interpreting Language Models Without Training Another Dictionary cites this paper.

ICA Lens: Interpreting Language Models Without Training Another Dictionary Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T09:17:49.077422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ff56213b-bead-4e9a-9612-d63740a43f46 · inbound

Anatomy of Post-Training: Using Interpretability to Characterize Data and Shape the Learning Signal cites this paper.

Anatomy of Post-Training: Using Interpretability to Characterize Data and Shape the Learning Signal Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 245

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T09:07:47.947301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 74f60525-2cdd-419e-8585-cb92693ab7d4 · inbound

Rational Sparse Autoencoder cites this paper.

Rational Sparse Autoencoder Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T17:08:43.960948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 0b41c211-49cd-45e5-9a40-b0e7ed98e96a · inbound

Critical Percolation as a Synthetic Data Model for Interpretability cites this paper.

Critical Percolation as a Synthetic Data Model for Interpretability Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 11

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T03:49:29.645376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation bc2e77cb-2669-4fcd-9876-9963fac35238 · inbound

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

Do Sparse Autoencoders Learn Meaningful Concept Hierarchies? Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 7

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T10:29:45.362219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation abe129d7-1364-4adf-a138-539e04a2db16 · inbound

Beyond the Hard Budget: Sparsity Regularizers for More Interpretable Top-k Sparse Autoencoders cites this paper.

Beyond the Hard Budget: Sparsity Regularizers for More Interpretable Top-k Sparse Autoencoders Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-07-04T13:39:50.936158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 347c5b27-8d15-4393-b4b0-5a027fbf95d6 · inbound

Beyond the Hard Budget: Sparsity Regularizers for More Interpretable Top-k Sparse Autoencoders cites this paper.

Beyond the Hard Budget: Sparsity Regularizers for More Interpretable Top-k Sparse Autoencoders Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-15T10:30:51.183063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5910d1d-1615-4ca3-83de-1c75d4d5eebd · inbound

Turn-Averaged SAEs for Feature Discovery and Long-Context Attribution cites this paper.

Turn-Averaged SAEs for Feature Discovery and Long-Context Attribution Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-07-01T15:35:48.366795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ac712014-e362-469d-b601-5d72cfb819f4 · inbound

Monosemanticity in Recommender Systems cites this paper.

Monosemanticity in Recommender Systems Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 11

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T02:34:13.627523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 96fc9cef-3493-4c34-882d-f0b5b9ba7a35 · inbound

Monosemanticity in Recommender Systems cites this paper.

Monosemanticity in Recommender Systems Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 11

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T22:49:00.652630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b17ebd3c-35dd-4b26-a41c-b9f4ace6dd43 · inbound

Expander Sparse Autoencoders: Parameter-Efficient Dictionaries for Mechanistic Interpretability cites this paper.

Expander Sparse Autoencoders: Parameter-Efficient Dictionaries for Mechanistic Interpretability Learning Multi-Level Features with Matryoshka Sparse Autoencoders

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T17:28:44.170293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.