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Paper Citation Record · LEDGER

Structure Maintained Representation Learning Neural Network for Causal Inference

As of 9 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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T05:24:25.594424Z digest=sha256:2cdfa79b817e372aeab2f23a8f177a47b7d7b9c44e1dbcedb7b6f46e74452c9e

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=sha256:2d172599da7c79edea82e7178592dbb501f7a286d44b8454b4a5cc2311943949

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=sha256:73b80db08803e77b9be3f114f68f55e9781e7a1678377ce3d36e2877b7f06423

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T05:24:25.144479Z digest=sha256:adb3af41963289b4a8fa4781f60106463139b25d626204c6d5523b0d5814822b

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T05:24:25.333384Z digest=sha256:1c44316858079306e0f23915ddf9fd6796879ef3ddb958b8097e4c5e12e380eb

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:b5dfdf74d3a837cdc2e1dbdd8053f443459ab2808812ea1a9df36bf02515fe7b

Pith citing papers

No inbound Pith citation observations are available.