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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 2026-08-12T06:34:41.77262+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

  • verified exact0
  • verified fuzzy0
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  • malformed identifier0
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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

Resolution
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 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-05-08T17:50:54.323470Z digest=sha256:40948397217af0864310af250bcf3faf97510b3e533c97cdd4a6c156c150d71d

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 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-05-08T16:19:53.680007Z digest=sha256:1e5496400ec5d264a17c0afe30ca377e6af7fbab44639f2703c9f532551e6823

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 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-05-13T02:12:54.796350Z digest=sha256:c75cd2bf10615aa0d5da21085263515a697d89c27f94aa5f722a78eeaaac8f11

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-15T02:55:46.616590Z digest=sha256:19579199f2bbc6584aff3ed9f9336698b762e9eccb9468521869f3c4580cce5e

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-20T20:39:11.311301Z digest=sha256:2ce98f7bd0d82017989853c163756d5b8e138a4ddc1346a0221826b38aab9d25

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-21T07:43:49.653592Z digest=sha256:db5db52e79d4f7a9ede7d757551bf7ce50444fce6cd40fbbd2ff22bfee08c805

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 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-05-20T08:06:41.392876Z digest=sha256:a49da9e24713eaf9fdd1add3711d1aa31b59810ae4a2c72626e52b634cc78dd6

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 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-05-21T08:04:32.512031Z digest=sha256:bb87a386276507d468b23cdb5b70f168f95a8046fd4fceb603427c87de2ba400

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-21T05:42:48.667216Z digest=sha256:b2280f788d73adcaa415296f7e95dbe1f6125925a3b7dc70ba8232f1083875ca

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 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-21T05:37:56.792564Z digest=sha256:0f4a01a26b11c84327e4b1f8521a2813c82e9852a0c7f1dbded83f9d7208614d

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=sha256:836fe8999a8b3fd3b9ca62d17595b2a6ec7f9018cc6635d41c198c74557cb41e