Pith. sign in

Paper Citation Record · LEDGER

From Search To Sampling: Generative Models For Robust Algorithmic Recourse

As of 19 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 1 inbound Pith citation observation for arXiv:2505.07351.

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

pith.paper-citation-record.v1
2505.07351 v1

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:24:45.661930Z

measured 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-28T19:05:28.806009Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-28T19:12:34.989967Z

Reference resolution

49 of 49 outbound references displayed

  • verified exact3
  • verified fuzzy25
  • unresolved21
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 152df9bf-488c-467e-bba9-842d8dd01c51 · outbound

This paper cites write newline.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse write newline

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:45.434299Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:24:45.434299Z digest=sha256:bcc5d3f1b50829f7f79d78157f9cdfef5c29e6e49e873c9188a8190032716c75

Observation 6334bb49-4fe2-42f4-bbaf-909953c37bdb · outbound

This paper cites M achine B ias --- propublica.org, 2016.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse M achine B ias --- propublica.org, 2016

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:24:46.523371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:24:45.441107Z digest=sha256:2ee5acccbbf29fa586ced7424d7022772a008675773a2a18bab6264bdf06528c

Observation 7d56bcaf-8c26-4675-aa10-8610b40ae03d · outbound

This paper cites Getting a CLUE: A Method for Explaining Uncertainty Estimates.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Getting a CLUE: A Method for Explaining Uncertainty Estimates

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:45.445981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:24:45.445981Z digest=sha256:796da081e1452c7384f5996679224c5c6338475ec4ac6b4269dc17dadd743b66

Observation c56c1db8-c318-492b-9c49-bd017e9ea26f · outbound

This paper cites Fairness and Machine Learning: Limitations and Opportunities.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Fairness and Machine Learning: Limitations and Opportunities

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:45.451595Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:24:45.451595Z digest=sha256:6ecbbecbd8dc77be0705620ced07f78ecd6d84f74ff3200d3430e222806cea68

Observation f4fa2a71-060b-46ef-b328-cb9b3881c4f5 · outbound

This paper cites an unresolved cited work.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Unresolved cited work

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:45.458940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:24:45.458940Z digest=sha256:37b484dccffa2a8a52cb2dd720c2550aba3b67b3e62c0a4eebcd6d80b621c244

Observation ae663e55-21a9-41d2-9d59-b894cfb96f9f · outbound

This paper cites Counterfactual Metarules for Local and Global Recourse.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Counterfactual Metarules for Local and Global Recourse

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:45.463540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:24:45.463540Z digest=sha256:840a3bfdadc15602cfa9925cbe4f946cf5308801ebaf9f3bb3b477b1a1403f35

Observation 4a089fe4-c5ef-498e-9363-78a4b2e0a90b · outbound

This paper cites Consistent Counterfactuals for Deep Models.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Consistent Counterfactuals for Deep Models

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:45.468960Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:24:45.468960Z digest=sha256:73c7cc08acd6fdabe2d2b99e68c84c8c696f2b2539207fe1f4289c9aea7123d9

Observation 8b517e43-2df1-475d-bb2b-e9784cde87d5 · outbound

This paper cites Breunig, Hans-Peter Kriegel, Raymond T.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Breunig, Hans-Peter Kriegel, Raymond T

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:45.479071Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:24:45.479071Z digest=sha256:512e39f57a0508db68c9bb5d48695ae4188d7fafbf6a027b565c2f7663fac387

Observation 7c17bc91-4900-420d-8059-b392a38cc4a3 · outbound

This paper cites The Risk to Population Health Equity Posed by Automated Decision Systems: A Narrative Review.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse The Risk to Population Health Equity Posed by Automated Decision Systems: A Narrative Review

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-08-15T22:24:45.967830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:24:45.483211Z digest=sha256:cff133d5482fca1188584e967014e70a2d8ca7b8240efd0e41afe24fda08d9e9

Observation b7d07875-6049-4b48-8079-e4cdd91c8f0a · outbound

This paper cites On the adversarial robustness of causal algorithmic recourse.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse On the adversarial robustness of causal algorithmic recourse

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:24:46.496506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:24:45.487753Z digest=sha256:d0497ea87eb2b0dfabce977401987e3cd3710ad1560b0dd9ea8bcf8f629803c4

Observation cea2695d-ce4e-46b9-a011-165e0988ff83 · outbound

This paper cites Cruds: Counterfactual recourse using disentangled subspaces.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Cruds: Counterfactual recourse using disentangled subspaces

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:24:46.483745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:24:45.491836Z digest=sha256:23625479eefcdb422d7fd81117a8c17d34dd70416a8109da91602d0c372baac1

Observation 2d74e562-57a6-41ef-aaff-efef6fdd519a · outbound

This paper cites Bail or jail? judicial versus algorithmic decision-making in the pretrial system.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Bail or jail? judicial versus algorithmic decision-making in the pretrial system

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:24:46.468310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:24:45.495848Z digest=sha256:ad558335c927878b975b6e78a885a809d3604a45993364a301bbe935c0385ced

Observation 2f9f5bf2-69bb-4e6d-9f52-6dd13c565cde · outbound

This paper cites Fico xml challenge.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Fico xml challenge

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:24:46.454335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:24:45.499890Z digest=sha256:bc9e95305c657485c921bd91c7475c93b485fb78a1c01d3853451652b6cd1c95

Observation 52ab1f40-beb3-4eb6-bf6a-154679e31138 · outbound

This paper cites The risks of recourse in binary classification.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse The risks of recourse in binary classification

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:24:46.437870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:24:45.503575Z digest=sha256:68fde88a0b34853f1b6de4988b284d3e5bcb6561496c182821f9fa2fec357d01

Observation 5d5163c7-43d4-4a41-b512-889ae7b6655d · outbound

This paper cites Trustworthy Actionable Perturbations.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Trustworthy Actionable Perturbations

Reference 15

Resolution
verified exact
local_arxiv, observed 2026-08-15T22:24:45.948735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:24:45.507381Z digest=sha256:d99ad16056b94b4124b94bde0a779ac55e3cdb6d5b6b7a8b553128cdbabcf20b

Observation 55419f02-79e9-4e30-8aa1-e1270da035e7 · outbound

This paper cites On the impact of algorithmic recourse on social segregation.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse On the impact of algorithmic recourse on social segregation

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:24:46.424185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:24:45.511893Z digest=sha256:4d2af020c22120b1c34b2c8013b21ea02e0f920dae9976550a1dfce4e359328a

Observation 7a9e3464-7f04-44d4-ae6a-8662914f4132 · outbound

This paper cites Robust counterfactual explanations for neural networks with probabilistic guarantees.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Robust counterfactual explanations for neural networks with probabilistic guarantees

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:24:46.410169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:24:45.515823Z digest=sha256:a0f52b2aa4106a13b581024b9890e89a4e95231808c0ec8a627fb06bf3f097f4

Observation f3dd1b21-0b89-4a31-8093-8c5df2a47c93 · outbound

This paper cites Strategic classification.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Strategic classification

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:24:46.396164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:24:45.519911Z digest=sha256:3978f90480edb0b1d88318f7d436cf59000cff8d60096bbe61250526a5689bdc

Observation e6816b5f-6da5-4395-8d75-caa7b5844e61 · outbound

This paper cites Towards Realistic Individual Recourse and Actionable Explanations in Black-Box Decision Making Systems.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Towards Realistic Individual Recourse and Actionable Explanations in Black-Box Decision Making Systems

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:45.523899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:24:45.523899Z digest=sha256:c57f84e292f763a03ea60bbc6302e2d20b245b2617eb6292705dd145dbf034c2

Observation 30fdceeb-32f6-493b-877b-fc2cdb734f07 · outbound

This paper cites Leveraging ai and ml to automate financial predictions and recommendations.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Leveraging ai and ml to automate financial predictions and recommendations

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:24:46.382556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:24:45.528530Z digest=sha256:544fb74a8eec4c60b40cefed829d5269451aec1fd685fa8f7288152edd2ddb7f

Observation f2ce44fd-86f8-4645-9528-3e261ca5b450 · outbound

This paper cites the right to explanation, explained.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse the right to explanation, explained

Reference 21

Resolution
verified exact
raw_fallback, observed 2026-08-15T22:24:45.917232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:24:45.532406Z digest=sha256:f78746f54f9123534a0b6aa10c401f742134960b9df84ce5e1e0e90e63a1f283

Observation 03fbe394-78f4-449a-b0ef-57eaa6640d05 · outbound

This paper cites Learning Decision Trees and Forests with Algorithmic Recourse.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Learning Decision Trees and Forests with Algorithmic Recourse

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:45.535982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:24:45.535982Z digest=sha256:668607965392672515f7e42dbbea9d943482e52182a0aa18d69fc1f9d6cdd3ee

Observation 6534a488-27dc-4d0f-8c43-23c1070cec0f · outbound

This paper cites Model-agnostic counterfactual explanations for consequential decisions.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Model-agnostic counterfactual explanations for consequential decisions

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:24:46.369909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:24:45.539820Z digest=sha256:7eb8b36d43c79d369ebbb15b36c642b05f12ad3e7276882f419e6460ee23087e

Observation 29b2c897-cef5-42cb-b05d-a8c8164154cf · outbound

This paper cites u gelgen, Bernhard Sch \.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse u gelgen, Bernhard Sch \

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:24:46.355631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:24:45.544124Z digest=sha256:e92fa4a25a3fa5ae5f696a4b2b7c7a0ef3906f4ad1a1764f6560dbe8fcf702f3

Observation e34a9c8d-1f56-4d61-b6d1-bb1a3830f715 · outbound

This paper cites A survey of algorithmic recourse: Contrastive explanations and consequential recommendations.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse A survey of algorithmic recourse: Contrastive explanations and consequential recommendations

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:24:46.339859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:24:45.548784Z digest=sha256:c97c1c0ac2d379e36a57976e39f987af5ed90fd4e36404e2da9596dbdb5b9db6

Observation b11e6b9d-71e8-42cc-89df-0132777ef92b · outbound

This paper cites Auto-Encoding Variational Bayes.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Auto-Encoding Variational Bayes

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:45.552525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:24:45.552525Z digest=sha256:d0c3adc2a38d34fe8f95f4cdb56f877e292fb341e41014ca129453a29d948a62

Observation 95b5cd37-267b-4f9b-b144-6b0a8c6f047f · outbound

This paper cites Probabilistic graphical models: principles and techniques.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Probabilistic graphical models: principles and techniques

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:45.556459Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:24:45.556459Z digest=sha256:f69d26e3e7796b53553b68e282f75807fce3b3e6b3b5045e336fc8fc95d949b2

Observation 8caeed83-fa6f-415f-8857-5a720917664a · outbound

This paper cites Inverse Classification for Comparison-based Interpretability in Machine Learning.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Inverse Classification for Comparison-based Interpretability in Machine Learning

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:45.561344Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:24:45.561344Z digest=sha256:e97e3278802778ac0b42108156e009a2f278e76c218ce4a0a164e13050f00830

Observation b11789cb-b2a7-4dcf-afb3-3d42a39f4d61 · outbound

This paper cites Derivative-Free Guidance in Continuous and Discrete Diffusion Models with Soft Value-Based Decoding.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Derivative-Free Guidance in Continuous and Discrete Diffusion Models with Soft Value-Based Decoding

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:45.566021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:24:45.566021Z digest=sha256:84bb550b3190474d8a11cf7ca550dde79539e44d764e63c52c46d366cd300dbe

Observation d7a6e394-9285-4c9b-89af-6f6d51b211d0 · outbound

This paper cites Explaining machine learning classifiers through diverse counterfactual explanations.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Explaining machine learning classifiers through diverse counterfactual explanations

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:24:46.314593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:24:45.570708Z digest=sha256:93e33f72b95c0fc21c7a0b161dcc0f4acee457223e7fb73d562c705b07e0718b

Observation bc9da79b-8a29-4e5d-95ca-0078308299df · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Pytorch: An imperative style, high-performance deep learning library

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:45.574894Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:24:45.574894Z digest=sha256:70ffacf34ba73cf76a72104b98d97e06b2e13e6311a4c7f8be5b5a1f675bbef0

Observation c508c243-bba0-440e-8f06-26b71aedc426 · outbound

This paper cites Learning model-agnostic counterfactual explanations for tabular data.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Learning model-agnostic counterfactual explanations for tabular data

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:24:46.292668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:24:45.579394Z digest=sha256:b60bff9e8b354bd69d832921fa8f3b897d4d7d638db9e60bcda8634af64c3670

Observation 42f70c75-5b33-4f6a-b407-be04019e1e4e · outbound

This paper cites On counterfactual explanations under predictive multiplicity.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse On counterfactual explanations under predictive multiplicity

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:24:46.278199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:24:45.584434Z digest=sha256:f6b234066e2b9f2fb67950b6eba3a5046b884bdfb692b11b482218e64fa79b9b

Observation de889f94-7bcb-4c61-8dd1-25e44722c35d · outbound

This paper cites Carla: A python library to benchmark algorithmic recourse and counterfactual explanation algorithms, 2021.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Carla: A python library to benchmark algorithmic recourse and counterfactual explanation algorithms, 2021

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:24:46.261299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:24:45.589363Z digest=sha256:4f9b7bf76f60afbc1c87bf17278318d681a87375905172f81b804a6fc8526a1c

Observation 1b7e3161-2f3d-4d6d-9255-59f418193b1c · outbound

This paper cites Probabilistically robust recourse: Navigating the trade-offs between costs and robustness in algorithmic recourse.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Probabilistically robust recourse: Navigating the trade-offs between costs and robustness in algorithmic recourse

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:24:46.247774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:24:45.593989Z digest=sha256:ae094d5787a707b78076eff3af2f3941d2f3918e4967c7e45d38d3a74875a2d9

Observation 474a476a-ee5e-4411-bf37-fc3cccaafbbb · outbound

This paper cites Pedregosa, G.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Pedregosa, G

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:45.601984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:24:45.601984Z digest=sha256:a40328f8112f1d4959300ff155edc38b2bda028babfbd8ad3ffb3c7d6295576e

Observation 5c9ca4b1-f485-406b-a94f-b2bd60ae31f9 · outbound

This paper cites Algorithmic Recourse in the Wild: Understanding the Impact of Data and Model Shifts.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Algorithmic Recourse in the Wild: Understanding the Impact of Data and Model Shifts

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:45.606397Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:24:45.606397Z digest=sha256:38209a9bb23ce9674f2c177efa6da9c708e99a5c48a2f5969890fd499134db3d

Observation 0e6a90d9-4664-4707-9da3-12b9ebfe0527 · outbound

This paper cites Efficiently stealing your machine learning models.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Efficiently stealing your machine learning models

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:45.611065Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:24:45.611065Z digest=sha256:c848da186882175af394d8a347ec53eb23b7b5725c8251bfc8235769b10bbd83

Observation c5bbbf56-748f-4880-9663-1c7b380ed4d0 · outbound

This paper cites why should i trust you?.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse why should i trust you?

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:45.616253Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:24:45.616253Z digest=sha256:fd358947a69a1435a07047da42e68ef9c72b277cb790f02c0c44485e84055163

Observation def475ad-0651-47ae-ba76-2c31b67833e1 · outbound

This paper cites Foster, Nicholas Mattei, and John P.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Foster, Nicholas Mattei, and John P

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:24:46.217029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:24:45.620573Z digest=sha256:2e2300da594de07add59b96d29dccbf508252e5fe4ecc8a819f096fa8ac74883

Observation 8b5e2618-65c1-421a-a07b-311d42ba5274 · outbound

This paper cites Generating interpretable counterfactual explanations by implicit minimisation of epistemic and aleatoric uncertainties.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Generating interpretable counterfactual explanations by implicit minimisation of epistemic and aleatoric uncertainties

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:24:46.204287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:24:45.625026Z digest=sha256:c64c21d9219f97dd718864751783c70bc43287c5e99ea6ef502be7f63616810c

Observation d2cf75da-f3f7-451f-82e8-960ab58338e1 · outbound

This paper cites Towards robust and reliable algorithmic recourse.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Towards robust and reliable algorithmic recourse

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:24:46.189897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:24:45.629818Z digest=sha256:aab3c667b59ae40418fe1c39e3d9ab4b20e23d8fb1fd4b085f90f4469e68f290

Observation 9b8a9961-b0f1-42a2-824c-e25d21c2e034 · outbound

This paper cites Actionable recourse in linear classification.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Actionable recourse in linear classification

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:24:46.176668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:24:45.634417Z digest=sha256:e7f6691be71049c06ca35ed91595ede1e2cc4a838a1d5cab31cc3c1d37d8849b

Observation 0cfc43fe-26f8-47a2-90f8-3d2660e068f1 · outbound

This paper cites Attention is all you need.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Attention is all you need

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:45.638447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:24:45.638447Z digest=sha256:7ed6b8b384675e374c6783d23d2df6299d28114857e8622ab7e20b5c5a3c963b

Observation 907e2d8c-9e2c-4826-948f-516ed2c4f765 · outbound

This paper cites Counterfactual explanations without opening the black box: Automated decisions and the gdpr.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Counterfactual explanations without opening the black box: Automated decisions and the gdpr

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:24:46.153652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:24:45.645116Z digest=sha256:b9a932d1c1c2bf7536586801ec36ee027b5fc3615d79f447799e667f1415d9de

Observation bdc9b7d4-bb97-4f01-85df-be1a8d3bdeb7 · outbound

This paper cites Mixed-type tabular data synthesis with score-based diffusion in latent space.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Mixed-type tabular data synthesis with score-based diffusion in latent space

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:24:46.139502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:24:45.649814Z digest=sha256:36a43c49ec28940d9f7ba1c4185d85b7e46ac4b11c348666c09fe41b071bb27d

Observation 682032d4-29cb-47da-9b6f-1c8b2251a343 · outbound

This paper cites @esa (Ref.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse @esa (Ref

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:45.653463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:24:45.653463Z digest=sha256:2a071e1e364cee0116b5c233c3131206ccf147f2e36702eb99c494e7229f7ded

Observation 815ddd2d-cda9-4bd9-900b-d2ca71c8df1f · outbound

This paper cites an unresolved cited work.

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Unresolved cited work

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-15T22:24:45.657764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:24:45.657764Z digest=sha256:e4e67ec40d611136f325d0fde514d994f0c06986d6885db077541b44bc5573f6

Observation 0ae8c58d-d6e2-4639-8eb1-1c8a0d792bd6 · outbound

This paper cites Training instances are shown in light red (for ) and blue color (for ).

From Search To Sampling: Generative Models For Robust Algorithmic Recourse Training instances are shown in light red (for ) and blue color (for )

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:24:46.107117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T22:24:45.661930Z digest=sha256:9f20dfff541166a94bfe06ad5f8dc1a0078f9d233e34d4c1533a1357134efad1

Pith citing papers

Observation 71a3d70f-308b-4d54-bed7-0d4e9317cae7 · inbound

TabChange: Precise Attribute Changes in Tabular Data cites this paper.

TabChange: Precise Attribute Changes in Tabular Data From Search To Sampling: Generative Models For Robust Algorithmic Recourse

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-06-28T19:12:34.991125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-28T19:05:28.806009Z digest=sha256:add1db68c3c4a37295e8ba3e74c045f54d4d781fc910c05ca074dd399ce4628f