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Paper Citation Record · LEDGER

Causal Representation Learning from Multiple Distributions: A General Setting

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2402.05052.

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

pith.paper-citation-record.v1
2402.05052 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T05:20:30.088064Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T08:04:50.118859Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
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  • 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 42872c26-d969-486c-83fd-e1e1479452dc · inbound

Fast Causal Discovery by Approximate Kernel-based Generalized Score Functions with Linear Computational Complexity cites this paper.

Fast Causal Discovery by Approximate Kernel-based Generalized Score Functions with Linear Computational Complexity Causal Representation Learning from Multiple Distributions: A General Setting

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-11T05:20:30.088064Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T05:20:30.088064Z digest=sha256:11fd8be3690f53ce427c95edea52063ab513256f2cacb3f585019e6d3192c6f2

Observation e1a0700a-c4af-4541-95b5-a069fdd5387e · inbound

Learning General Causal Structures with Hidden Dynamic Process for Climate Analysis cites this paper.

Learning General Causal Structures with Hidden Dynamic Process for Climate Analysis Causal Representation Learning from Multiple Distributions: A General Setting

Reference 98

Resolution
unresolved
no resolver link, observed 2026-08-10T17:16:27.732010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T17:16:27.732010Z digest=sha256:aae0f448d64173ed89d6a5e2fa3af442ba8b7d89746809d37ae5e417cb997771

Observation cae9011a-b560-4fce-8f76-2db8dcc94b29 · inbound

Order-based Rehearsal Learning cites this paper.

Order-based Rehearsal Learning Causal Representation Learning from Multiple Distributions: A General Setting

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-11T17:11:12.335623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-05-08T17:50:54.323470Z digest=sha256:c52546fd61fbb8c2fd3d97757fa0f418cccbf41622a2e74c6dcc94e3f1604329

Observation bc3fe69d-c4c1-49d5-9210-24246a607472 · inbound

MOSAIC: Module Discovery via Sparse Additive Identifiable Causal Learning for Scientific Time Series cites this paper.

MOSAIC: Module Discovery via Sparse Additive Identifiable Causal Learning for Scientific Time Series Causal Representation Learning from Multiple Distributions: A General Setting

Reference 46

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T18:16:12.013848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-05-08T16:19:53.680007Z digest=sha256:c93ad0e2278bb8b528d25475b463fd77cfaf5e7d41ecdca28bebab6623c184de

Observation 2bfa40a3-7492-4a3e-aabb-5bf166e789bf · inbound

DeconDTN-Toolkit: A Library for Evaluation and Enhancement of Robustness to Provenance Shift cites this paper.

DeconDTN-Toolkit: A Library for Evaluation and Enhancement of Robustness to Provenance Shift Causal Representation Learning from Multiple Distributions: A General Setting

Reference 119

Resolution
metadata mismatch
arxiv_id, observed 2026-05-13T02:17:06.778966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-05-13T02:12:54.796350Z digest=sha256:2b95ca1d083da7b786dd9b169e39ab510f66e9e717b94193f5d50012409d4d45

Observation bcd560b2-5695-4157-b758-04eee14b00fb · inbound

MoRe: Modular Representations for Principled Continual Representation Learning on Sequential Data cites this paper.

MoRe: Modular Representations for Principled Continual Representation Learning on Sequential Data Causal Representation Learning from Multiple Distributions: A General Setting

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-15T02:59:40.805601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-15T02:55:46.616590Z digest=sha256:71b2af5fb7fc4c28b8ec02494401cb8cfc420c22392cce5362a726ab51f4b241

Observation 51a0faa2-018a-4aff-bd11-58b8d0ef8795 · inbound

MoRe: Modular Representations for Principled Continual Representation Learning on Sequential Data cites this paper.

MoRe: Modular Representations for Principled Continual Representation Learning on Sequential Data Causal Representation Learning from Multiple Distributions: A General Setting

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-20T20:43:43.492007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-20T20:39:11.311301Z digest=sha256:92fd928c9d21776c36134a042acde0acd1ff593e3d68bbbe021c0f321e95dc60

Observation f359635f-6b40-4cbf-9bbd-79404d39a617 · inbound

MoRe: Modular Representations for Principled Continual Representation Learning on Sequential Data cites this paper.

MoRe: Modular Representations for Principled Continual Representation Learning on Sequential Data Causal Representation Learning from Multiple Distributions: A General Setting

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-21T07:44:02.725863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-21T07:43:49.653592Z digest=sha256:60a947982ee008fa94b87a8fd7c1645a819ae52a83fb41823098ee615a46e629

Observation 0960bcf8-62c5-4ae0-9bf4-327febc97d3e · inbound

What Makes a Representation Good for Single-Cell Perturbation Prediction? cites this paper.

What Makes a Representation Good for Single-Cell Perturbation Prediction? Causal Representation Learning from Multiple Distributions: A General Setting

Reference 17

Resolution
metadata mismatch
arxiv_id, observed 2026-05-20T08:08:08.848801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-05-20T08:06:41.392876Z digest=sha256:ed7c21ebeda7cc52de63b6b2e6bbf25d2a4b12b6bf3bca31367fe6831bd05254

Observation 0481e9b3-27aa-4dfc-8f55-8ae926c6fe88 · inbound

Score-Based Causal Discovery of Latent Variable Causal Models cites this paper.

Score-Based Causal Discovery of Latent Variable Causal Models Causal Representation Learning from Multiple Distributions: A General Setting

Reference 88

Resolution
verified exact
arxiv_id, observed 2026-05-21T08:04:50.121299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-05-21T08:04:32.512031Z digest=sha256:be8ba4c765633b6cf2d24f80a48e8c837da3f204a723a145036f4c0c7d104f39

Observation f3fa5e9b-520d-4846-be00-52cafa56099a · inbound

A Dialogue between Causal and Traditional Representation Learning: Toward Mutual Benefits in a Unified Formulation cites this paper.

A Dialogue between Causal and Traditional Representation Learning: Toward Mutual Benefits in a Unified Formulation Causal Representation Learning from Multiple Distributions: A General Setting

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-21T05:43:58.770041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-21T05:42:48.667216Z digest=sha256:5dd0926f97914c8478269e18987dab19d46c568f60003e2fb8fd321a8c3e10e0

Observation e266e6f6-79c0-4534-83aa-1c8102afa61e · inbound

Multimodal LLMs under Pairwise Modalities cites this paper.

Multimodal LLMs under Pairwise Modalities Causal Representation Learning from Multiple Distributions: A General Setting

Reference 73

Resolution
metadata mismatch
arxiv_id, observed 2026-05-21T05:39:40.673674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-21T05:37:56.792564Z digest=sha256:bb2e7ae9463fdae43db4183e96d47a7340c41184fbce6caaaac633d8cb834d7a

Observation 48c27611-b405-47c5-bdb3-abfb5dc8b15c · inbound

Learning Task-Sufficient World Models by Synergizing Agentic Exploration and Structured Modeling cites this paper.

Learning Task-Sufficient World Models by Synergizing Agentic Exploration and Structured Modeling Causal Representation Learning from Multiple Distributions: A General Setting

Reference 1

Resolution
unresolved
no resolver link, observed 2026-07-11T19:24:48.899301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T19:24:48.899301Z digest=sha256:cc78f0e13b9cb7a5cd4bd7ed279c70d97f9ca0cbe867b8b6a1a5521ac63eefcd