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Paper Citation Record · LEDGER

Bipartite causal inference with interference, time series data, and a random network

As of 13 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 3 inbound Pith citation observations for arXiv:2404.04775.

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

pith.paper-citation-record.v1
2404.04775 v3

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-24T02:22:38.540827Z

measured 32 of 32 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T00:34:03.709632Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T14:06:24.762819Z

Reference resolution

29 of 29 outbound references displayed

  • verified exact4
  • verified fuzzy25
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 51afafc0-31a6-4f11-81fe-e040e86c5a10 · outbound

This paper cites Econometric methods for program evaluation.

Bipartite causal inference with interference, time series data, and a random network Econometric methods for program evaluation

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-05-24T02:23:46.656457Z

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=2026-05-24T02:22:38.540827Z digest=sha256:9f2d74f31010c58939e166d707166856f31f35cd40a3d56d7545a02402f4e718

Observation 98ab579b-a59a-4953-b736-c64930ceacdd · outbound

This paper cites Large sample properties of matching estimators for average treatment effects.

Bipartite causal inference with interference, time series data, and a random network Large sample properties of matching estimators for average treatment effects

Reference 2

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verified fuzzy
raw_fallback, observed 2026-05-24T02:23:46.637148Z

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=2026-05-24T02:22:38.540827Z digest=sha256:b3735655c5c772d496e2644c16fafabb1fd15225a196c786c717d89a2271e2ec

Observation 0bbc07da-ff86-4ac4-897f-a090777b0616 · outbound

This paper cites Network synthetic interventions: A causal framework for panel data under network interference.

Bipartite causal inference with interference, time series data, and a random network Network synthetic interventions: A causal framework for panel data under network interference

Reference 3

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verified fuzzy
raw_fallback, observed 2026-05-24T02:23:46.626150Z

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=2026-05-24T02:22:38.540827Z digest=sha256:8f43f59040e17d3a1e86c1d7e5420a0c24d6b58b8c5fc31bb27becbcbcf08dea

Observation 751b5693-8c3e-44eb-a7ab-699e9e2b778b · outbound

This paper cites Aronow and Cyrus Samii.

Bipartite causal inference with interference, time series data, and a random network Aronow and Cyrus Samii

Reference 4

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verified fuzzy
raw_fallback, observed 2026-05-24T02:23:46.646300Z

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=2026-05-24T02:22:38.540827Z digest=sha256:19e4dcbe3854ed6a1b369886e521a55f0a80e7c4949fc63b83c53a0e8f6260bb

Observation 94453072-5369-44f8-ba3b-35684be8e872 · outbound

This paper cites Controlling the false discovery rate: a practical and powerful approach to multiple testing.

Bipartite causal inference with interference, time series data, and a random network Controlling the false discovery rate: a practical and powerful approach to multiple testing

Reference 5

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verified fuzzy
raw_fallback, observed 2026-05-24T02:23:46.650090Z

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=2026-05-24T02:22:38.540827Z digest=sha256:a9cc0c68838409828113102c249857914d13113fdc2f87e01d8b1a66d1d3dd04

Observation 8260d434-a098-4c56-b5cf-d20548fb1804 · outbound

This paper cites Time series experiments and causal estimands: Exact randomization tests and trading.

Bipartite causal inference with interference, time series data, and a random network Time series experiments and causal estimands: Exact randomization tests and trading

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-05-24T02:23:46.643369Z

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=2026-05-24T02:22:38.540827Z digest=sha256:52cf2274f89c38ead165b915708a57483582859ae01483b39a26658e9f9c9350

Observation d11d660b-8ef8-4efa-8553-88a43e718105 · outbound

This paper cites Cluster randomized designs for one-sided bipartite experiments.

Bipartite causal inference with interference, time series data, and a random network Cluster randomized designs for one-sided bipartite experiments

Reference 7

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verified fuzzy
raw_fallback, observed 2026-05-24T02:23:46.666022Z

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=2026-05-24T02:22:38.540827Z digest=sha256:b44700e8426f56679d90f5a3a08005b9d92265489c417744369636262cb558c7

Observation 9208a74c-7749-4a75-aa8a-c8a35d861558 · outbound

This paper cites Estimation and inference for synthetic control methods with spillover effects.

Bipartite causal inference with interference, time series data, and a random network Estimation and inference for synthetic control methods with spillover effects

Reference 8

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verified exact
arxiv_id, observed 2026-05-24T02:23:45.786157Z

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=2026-05-24T02:22:38.540827Z digest=sha256:b9a4f6bedbfa92f7e9dba58da6456f9ec591faac8cf6a481e85b0c5292c6cd47

Observation 9c4991f1-14b8-42e8-ab4c-651ac22c9a1b · outbound

This paper cites An Approach to Causal Inference over Stochastic Networks.

Bipartite causal inference with interference, time series data, and a random network An Approach to Causal Inference over Stochastic Networks

Reference 9

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verified exact
arxiv_id, observed 2026-05-24T02:23:45.793790Z

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=2026-05-24T02:22:38.540827Z digest=sha256:37a19143fa6719018cd5ca848b057fe9c79412e791e7b65ab7a414789d7814f2

Observation 643f0010-c5e2-49aa-9fc3-4bfc8b1a0cf5 · outbound

This paper cites The inclusive synthetic control method.

Bipartite causal inference with interference, time series data, and a random network The inclusive synthetic control method

Reference 10

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verified fuzzy
raw_fallback, observed 2026-05-24T02:23:46.662542Z

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=2026-05-24T02:22:38.540827Z digest=sha256:07dc65ae1d3d1d162ec3f315c25719df572152b4ca45f44f7814ead8cec16f64

Observation 283bcf8f-8ecd-42ee-a2e5-11a388ff0c3f · outbound

This paper cites Urban bike and pedestrian activity impacts from wildfire smoke events in seattle, wa.

Bipartite causal inference with interference, time series data, and a random network Urban bike and pedestrian activity impacts from wildfire smoke events in seattle, wa

Reference 11

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verified fuzzy
raw_fallback, observed 2026-05-24T02:23:46.669654Z

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=2026-05-24T02:22:38.540827Z digest=sha256:146a8a9e15a3958a37add946f575a7eff944456554b2e3186c9c02b7d2874d5a

Observation 2b7c2ffa-54cd-408a-b66e-2e082b52830c · outbound

This paper cites Causal inference with bipartite designs.

Bipartite causal inference with interference, time series data, and a random network Causal inference with bipartite designs

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-05-24T02:23:46.659676Z

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=2026-05-24T02:22:38.540827Z digest=sha256:4eaa3778bb4811221d51f6ab8389293371a490c3d5b6f6f43b3d0afaf4975448

Observation efbf4b85-5985-48c6-a51c-395d66ecd917 · outbound

This paper cites Identification and estimation of treatment and interference effects in observational studies on networks.

Bipartite causal inference with interference, time series data, and a random network Identification and estimation of treatment and interference effects in observational studies on networks

Reference 13

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verified fuzzy
raw_fallback, observed 2026-05-24T02:23:46.629767Z

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=2026-05-24T02:22:38.540827Z digest=sha256:a48df469c5ce2acea5b16268ba870a8871f7ddb90b361d9edb3bec0e8ba1fec8

Observation 2128872b-90c2-4b7a-92db-369fa4a52188 · outbound

This paper cites Direct and spillover effects of a new tramway line on the commercial vitality of peripheral streets. A synthetic-control approach.

Bipartite causal inference with interference, time series data, and a random network Direct and spillover effects of a new tramway line on the commercial vitality of peripheral streets. A synthetic-control approach

Reference 14

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verified exact
arxiv_id, observed 2026-05-24T02:23:45.808006Z

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=2026-05-24T02:22:38.540827Z digest=sha256:b6e6350fde8252f2564677cf7cf529c9f2c7e71df7da05051e470d9deaac75a6

Observation 4ee0b461-9f78-4084-8078-95e25ea90bc1 · outbound

This paper cites Design and analysis of bipartite experiments under a linear exposure-response model.

Bipartite causal inference with interference, time series data, and a random network Design and analysis of bipartite experiments under a linear exposure-response model

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-05-24T02:23:46.633868Z

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=2026-05-24T02:22:38.540827Z digest=sha256:c8f9b7f082dfeaa7c595fc1ca7f93ca35bdbb3827061f9ec020775e2fcc9b347

Observation 35ec3931-3bf2-4958-970f-2f4ffb824342 · outbound

This paper cites Matching as nonparametric preprocessing for reducing model dependence in parametric causal inference.

Bipartite causal inference with interference, time series data, and a random network Matching as nonparametric preprocessing for reducing model dependence in parametric causal inference

Reference 16

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verified fuzzy
raw_fallback, observed 2026-05-24T02:23:46.615470Z

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=2026-05-24T02:22:38.540827Z digest=sha256:fe2ebe124cd387c1e946149b785aa3fbd4736c052bc6fe8a5c6781405ed7f7f2

Observation 02921689-51a6-4afb-8529-3270a264b44c · outbound

This paper cites Causal inference in the social sciences.

Bipartite causal inference with interference, time series data, and a random network Causal inference in the social sciences

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-05-24T02:23:46.619128Z

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=2026-05-24T02:22:38.540827Z digest=sha256:289dc9d0e29172b4720037f435e41bb7cba707d14a659fb4ec44657eefff9533

Observation b668ea3a-7ba3-4bc2-ab70-9bec797eb2aa · outbound

This paper cites Enhancing a geographic regression discontinuity design through matching to estimate the effect of ballot initiatives on voter turnout.

Bipartite causal inference with interference, time series data, and a random network Enhancing a geographic regression discontinuity design through matching to estimate the effect of ballot initiatives on voter turnout

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-05-24T02:23:46.640245Z

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=2026-05-24T02:22:38.540827Z digest=sha256:58ece07da393e465232e2396cdec988fc4dc47b6789e0a740d49f789955b894e

Observation 17277c76-3bc4-4d78-9287-1c2f80754c7d · outbound

This paper cites Estimating causal effects in the presence of partial interference using multivariate bayesian structural time series models.

Bipartite causal inference with interference, time series data, and a random network Estimating causal effects in the presence of partial interference using multivariate bayesian structural time series models

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-05-24T02:23:46.622623Z

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=2026-05-24T02:22:38.540827Z digest=sha256:34f32fd7205945d468c4355e931795cbcba1d1769e113dceee8e876c1fd85d6e

Observation 3ee677c9-2957-4c46-aca8-7148358f1909 · outbound

This paper cites Variance reduction in bipartite experiments through correlation clustering.

Bipartite causal inference with interference, time series data, and a random network Variance reduction in bipartite experiments through correlation clustering

Reference 20

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verified fuzzy
raw_fallback, observed 2026-05-24T02:23:46.692293Z

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=2026-05-24T02:22:38.540827Z digest=sha256:726b790a39d3f909f78f1e84c57d6f614d41b8c29a86658e258dee058d3d3d0e

Observation 8868f1f2-934d-4847-a754-7915c00177a2 · outbound

This paper cites Inclusion of quasi-experimental studies in systematic reviews of health systems research.

Bipartite causal inference with interference, time series data, and a random network Inclusion of quasi-experimental studies in systematic reviews of health systems research

Reference 21

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verified fuzzy
raw_fallback, observed 2026-05-24T02:23:46.682897Z

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=2026-05-24T02:22:38.540827Z digest=sha256:88d92b3cb34c8c7c666a879febae4e5e10cf5e4541a417486920bc69d5d88848

Observation e3196f99-3a09-4804-a88f-54af4a9d8a5e · outbound

This paper cites Constructing a control group using multivariate matched sampling methods that incorporate the propensity score.

Bipartite causal inference with interference, time series data, and a random network Constructing a control group using multivariate matched sampling methods that incorporate the propensity score

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-05-24T02:23:46.653549Z

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=2026-05-24T02:22:38.540827Z digest=sha256:9b9569e3ea848d4ec2fdff5ab1899fcf4a6e02bd871e4a2704e479f9d5aef88b

Observation f13a1dcd-5b21-4f11-b54e-688e1851ff60 · outbound

This paper cites Causal inference with misspecified exposure mappings: separating definitions and assumptions.

Bipartite causal inference with interference, time series data, and a random network Causal inference with misspecified exposure mappings: separating definitions and assumptions

Reference 23

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verified fuzzy
raw_fallback, observed 2026-05-24T02:23:46.679755Z

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=2026-05-24T02:22:38.540827Z digest=sha256:b0a817ec79f44dfef149fe628340d37935bdfa83f32cfde60e0cde09dd85d379

Observation 963c12b3-03b0-4502-82ed-42d765886b5c · outbound

This paper cites Causal health impacts of power plant emission controls under modeled and uncertain physical process interference.

Bipartite causal inference with interference, time series data, and a random network Causal health impacts of power plant emission controls under modeled and uncertain physical process interference

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-05-24T02:23:45.800281Z

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=2026-05-24T02:22:38.540827Z digest=sha256:19d0f9de952413e38eaeae57d90133f8b9b74016c7c9e2175d0ff6eb867b1cfe

Observation 86e979ad-860f-4286-9951-374743d2421b · outbound

This paper cites Bipartite interference and air pollution transport: Estimating health effects of power plant interventions.

Bipartite causal inference with interference, time series data, and a random network Bipartite interference and air pollution transport: Estimating health effects of power plant interventions

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-05-24T02:23:46.688961Z

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=2026-05-24T02:22:38.540827Z digest=sha256:7f4828bb7dee615916b9f68e592cdc26fbbb737849daa9907717db7ceae126bd

Observation 01688199-8562-4f83-a760-02843c633bd0 · outbound

This paper cites Bipartite causal inference with interference.

Bipartite causal inference with interference, time series data, and a random network Bipartite causal inference with interference

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-05-24T02:23:46.686012Z

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=2026-05-24T02:22:38.540827Z digest=sha256:6c031abee69856ba07b6c95c7d043f04e3687312f548120625c174b89a5fd330

Observation c25ed81e-10a8-4430-af26-04ce06fb4fb2 · outbound

This paper cites Using mixed integer programming for matching in an observational study of kidney failure after surgery.

Bipartite causal inference with interference, time series data, and a random network Using mixed integer programming for matching in an observational study of kidney failure after surgery

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-05-24T02:23:46.695748Z

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=2026-05-24T02:22:38.540827Z digest=sha256:7a530942d5d93c3ff2528b018562bdbd34ad5b0e0fc9197645caa4bc04c9a268

Observation cc557917-4e95-4981-bd23-85a539680b27 · outbound

This paper cites Stronger instruments via integer programming in an observational study of late preterm birth outcomes.

Bipartite causal inference with interference, time series data, and a random network Stronger instruments via integer programming in an observational study of late preterm birth outcomes

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-05-24T02:23:46.676522Z

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=2026-05-24T02:22:38.540827Z digest=sha256:2410c4769711e40291072d107b4fe0ecf34f89eced3216528f95af19e4544ad4

Observation bb951778-785f-4bbe-9376-ef3ded93575d · outbound

This paper cites Zubizarreta.

Bipartite causal inference with interference, time series data, and a random network Zubizarreta

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-05-24T02:23:46.673044Z

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=2026-05-24T02:22:38.540827Z digest=sha256:7d7291f93c6cf2486a389b9c32937b079cc96d345cb2fae65761428104f173ec

Pith citing papers

Observation 4cb6b9c7-e4d2-404c-a9f5-63cb973c4eae · inbound

Balancing Interference and Correlation in Spatial Experimental Designs: A Causal Graph Cut Approach cites this paper.

Balancing Interference and Correlation in Spatial Experimental Designs: A Causal Graph Cut Approach Bipartite causal inference with interference, time series data, and a random network

Reference 84

Resolution
metadata mismatch
local_arxiv, observed 2026-08-07T14:06:24.800848Z

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=2026-08-07T14:06:20.482202Z digest=sha256:6af1624e602bf66591e6de8fc5ef2ee72b7b27b6796a5730a1fac0508b5e38b2

Observation d039261a-1def-487a-9d05-030383d944b9 · inbound

GAUGER: Generalized Regression Adjustment via Graph-Weighted Exposure-Level Residualization for Design-Based Inference Under Interference cites this paper.

GAUGER: Generalized Regression Adjustment via Graph-Weighted Exposure-Level Residualization for Design-Based Inference Under Interference Bipartite causal inference with interference, time series data, and a random network

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-01T12:16:06.931996Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T12:16:06.931996Z digest=sha256:6a580dc8aee48d67f5789eed11684b25dd769f2eaf5ba252a0c78c9897a3185e

Observation 7050cdba-5cce-402a-b0f8-63fcc3116b09 · inbound

CLAM: Causal Spatial Disaggregation to Infer Local Effects From Coarse Data cites this paper.

CLAM: Causal Spatial Disaggregation to Infer Local Effects From Coarse Data Bipartite causal inference with interference, time series data, and a random network

Reference 29

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unresolved
no resolver link, observed 2026-08-12T00:34:03.709632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T00:34:03.709632Z digest=sha256:e84a0e6ad625f16a62680b77e613174979ae424acc9860259c24192caa5e48c7