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Paper Citation Record · LEDGER

Causal Representation Learning from Multiple Distributions: A General Setting

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 16 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 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 16 of 16 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:07:51.846715Z

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.

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 43a012fe-f3e6-4ee8-8a7e-6795e89b1016 · inbound

Human-aligned Deep Learning: Explainability, Causality, and Biological Inspiration cites this paper.

Human-aligned Deep Learning: Explainability, Causality, and Biological Inspiration Causal Representation Learning from Multiple Distributions: A General Setting

Reference 506

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unresolved
no resolver link, observed 2026-08-16T12:07:51.846715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:07:51.846715Z digest=sha256:0cf09acaed8fda7690a58f63f103ab3f34bfb7f48643ca8abfc3b080c5256474

Observation a8c6c311-7fb3-4219-8137-08405c61ae63 · inbound

Causal View of Time Series Imputation: Some Identification Results on Missing Mechanism cites this paper.

Causal View of Time Series Imputation: Some Identification Results on Missing Mechanism Causal Representation Learning from Multiple Distributions: A General Setting

Reference 73

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unresolved
no resolver link, observed 2026-08-15T22:28:25.815657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:28:25.815657Z digest=sha256:2b1a81a5ce23e38ebcd5e2700169247b77bab570e3c32593c2838d2973474fac

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 2026-08-20T06:33:59.587034+00:00.

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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 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-08T16:19:53.680007Z digest=sha256:b07955bb4ef42fc329fa1867463e716b772a3dccaa969a50b942adea318b685f

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

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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 2026-08-20T06:33:59.587034+00:00.

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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 2026-08-20T06:33:59.587034+00:00.

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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

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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 2026-08-20T06:33:59.587034+00:00.

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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

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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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-21T07:43:49.653592Z digest=sha256:2cf08ea356cd91c066873f167619ed7b574f39455cb58c39055deff01bb8bb64

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 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-20T08:06:41.392876Z digest=sha256:5e977034db4500eaa7bec713de2ab7042938992d79b9b90647e130fcfd99daba

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 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-21T08:04:32.512031Z digest=sha256:1c9ad8e479d207716bee362aeda0ff4e091f6ffd9bf6295d25335fa80da78ca0

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

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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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-21T05:42:48.667216Z digest=sha256:59cb2088f2b9d24d2ec4e6d6335672dbd88859a19cf9c91eaf69079b314759f5

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

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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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-21T05:37:56.792564Z digest=sha256:cb01c7efb7b56a9711ccf4995fe86656b4739e2fbc2196932b4ea3989661ca85

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.

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