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Paper Citation Record · LEDGER

Causal Representation Learning from Multiple Distributions: A General Setting

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 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 14 of 14 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 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T20:53:27.086670Z

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

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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 2e1839ca-8962-4c75-83db-1f90e5566c5c · inbound

Navigating Shortcuts, Spurious Correlations, and Confounders: From Origins via Detection to Mitigation cites this paper.

Navigating Shortcuts, Spurious Correlations, and Confounders: From Origins via Detection to Mitigation Causal Representation Learning from Multiple Distributions: A General Setting

Reference 216

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unresolved
no resolver link, observed 2026-08-11T20:53:27.086670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T20:53:27.086670Z digest=sha256:c0ed1ccd38424b6f823d41325cfd2b26410f15ac23b98a55caa27cb230fd4251

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

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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:f013e7d3d81ee1eb74922f14a0eb4cd8539a536f0ac3a23eecb16f9e39bc6d98

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

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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=sha256:5d2ba7f240931366aa8a486e4d66f68e070853275e0a47b898bea1510d6bf9b3

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

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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:d0d2d4b443d43c6e37001adf511c03ce8acb872c11f41268de29fced3e733e2c

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

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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=sha256:543942c98571a5386308d50d46c43ea468011dd8f96b25bbd3e9d9ffc29295d1

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:db031f0fb37f8e126cceb5d4492d187feb63ac48a3e408db7bbacc1caff705a2

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

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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:cc44fa8536c2b50482c69ee28bec6fedf2daf7e6556cd22ac2df75c2ace7ce8a

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=sha256:3831be319e043440817715a2cf8a627a750348151e7cc8a910e822197ff29377

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=sha256:2ce9bebce5093672cad08bdfbdf6ceec089cbe3dfd630e5b53e391fdb3baadc6

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

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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:e3bd1eef32b71fffa99dfe2e02135ed73a06a1c6f7055075fc542657ec0fa7bd

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:e90df7d2567e96aef4cc05cf3a08ca8bf377b5fedff8c74352d692cae5ce17f4

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=sha256:28f10fcaa6fca03095d1b4f299756099850b9b092c057b4045d0682be06365b9

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=sha256:493d12a376f83e6a80a6290386a924353af8513bf0fd3c1d4ef054a8f5dac5c6

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

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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=sha256:836fe8999a8b3fd3b9ca62d17595b2a6ec7f9018cc6635d41c198c74557cb41e