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Paper Citation Record · LEDGER

Structure Maintained Representation Learning Neural Network for Causal Inference

As of 15 August 2026, this Paper Citation Record lists 6 of 6 outbound references and 0 inbound Pith citation observations for arXiv:2508.01865.

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

pith.paper-citation-record.v1
2508.01865 v1

Coverage vector

measured 6 of 6 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T05:24:25.594424Z

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

6 of 6 outbound references displayed

  • verified exact1
  • verified fuzzy2
  • unresolved3
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f91385fa-5f63-4770-b3e3-bc26da1b2b1c · outbound

This paper cites Ace: Adaptively similarity-preserved representation learning for individual treatment effect estimation.

Structure Maintained Representation Learning Neural Network for Causal Inference Ace: Adaptively similarity-preserved representation learning for individual treatment effect estimation

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:24:25.969755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T05:24:25.594424Z digest=sha256:b8d44c01fd7e72ecfa4129c52aa972557297e206558147a523acf7eaae351d4a

Observation d2a6bb03-941f-4e81-9e68-ec31bbcc8ed3 · outbound

This paper cites Learning Weighted Representations for Generalization Across Designs.

Structure Maintained Representation Learning Neural Network for Causal Inference Learning Weighted Representations for Generalization Across Designs

Reference 2016

Resolution
unresolved
no resolver link, observed 2026-08-06T05:24:25.427569Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:24:25.427569Z digest=sha256:14c099bf7286f11c1594a5539ecb8dfe84abf991cb7fe13357bd43a454aa7554

Observation 78084569-0dbe-4a9a-b9fb-f3b55b78be67 · outbound

This paper cites Causal Inference: A Missing Data Perspective.

Structure Maintained Representation Learning Neural Network for Causal Inference Causal Inference: A Missing Data Perspective

Reference 2017

Resolution
unresolved
no resolver link, observed 2026-08-06T05:24:25.228483Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:24:25.228483Z digest=sha256:6f0d424a90120c495c6f42959f75d4536c6fe60995e1b8eb2187ba05c259208b

Observation f5772bdf-4536-45b9-8362-6fdc3d69304d · outbound

This paper cites Deep Counterfactual Networks with Propensity-Dropout.

Structure Maintained Representation Learning Neural Network for Causal Inference Deep Counterfactual Networks with Propensity-Dropout

Reference 2018

Resolution
verified exact
local_arxiv, observed 2026-08-06T05:24:25.809971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T05:24:25.144479Z digest=sha256:5b7d586be68edffe72c4f20711e17c641a9506f407c5438c08147372f94af66f

Observation 282d537e-058c-4d20-9ff8-021e891db606 · outbound

This paper cites Dr-vidal- doubly robust variational information-theoretic deep adversarial learning for counterfactual prediction and treatment effect estimation on real world data.

Structure Maintained Representation Learning Neural Network for Causal Inference Dr-vidal- doubly robust variational information-theoretic deep adversarial learning for counterfactual prediction and treatment effect estimation on real world data

Reference 2021

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T05:24:26.146205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-06T05:24:25.333384Z digest=sha256:8765085948fe8cbfdff2faea106a82786c958232eb00edd5b28d75faca5276ca

Observation 387def19-6c8f-40e8-9976-398bd35603e4 · outbound

This paper cites On Mutual Information Maximization for Representation Learning.

Structure Maintained Representation Learning Neural Network for Causal Inference On Mutual Information Maximization for Representation Learning

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-06T05:24:25.551345Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T05:24:25.551345Z digest=sha256:6f12334f965b1c1669a302826663ae18eb3816d34b638783ceb2ed64677cfaa3

Pith citing papers

No inbound Pith citation observations are available.