Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T11:54:26.905697Z
Paper Citation Record · LEDGER
Stress-Testing ML Pipelines with Adversarial Data Corruption
As of 18 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 0 inbound Pith citation observations for arXiv:2506.01230.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
62 of 62 outbound references displayed
- verified exact4
- verified fuzzy7
- unresolved51
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation e5c411fd-f829-4795-87ae-bfd77cdcfb36 · outbound
This paper cites Regulation (EU) 2024/1689 of the European Parliament and of the Council on Artificial Intelligence.
Stress-Testing ML Pipelines with Adversarial Data Corruption Regulation (EU) 2024/1689 of the European Parliament and of the Council on Artificial Intelligence
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:54:36.959385Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 289fcb5a-68cf-4d68-98db-2396acc6d96c · outbound
This paper cites Codebase for SAVAGE.
Stress-Testing ML Pipelines with Adversarial Data Corruption Codebase for SAVAGE
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:54:36.732874Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 375bf85c-60aa-4101-84e4-d755a8aafc37 · outbound
This paper cites REIN: A Comprehensive Benchmark Framework for Data Cleaning Methods in ML Pipelines.
Stress-Testing ML Pipelines with Adversarial Data Corruption REIN: A Comprehensive Benchmark Framework for Data Cleaning Methods in ML Pipelines
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:54:21.211346Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a75c299c-6891-44fa-a638-7685f1705a28 · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:54:21.296666Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c9835f2e-ddf2-4894-9435-b214b3da8e9c · outbound
This paper cites Poisoning Attacks against Support Vector Machines.
Stress-Testing ML Pipelines with Adversarial Data Corruption Poisoning Attacks against Support Vector Machines
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:54:21.392684Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6b6bd40b-762b-4cc5-a8b2-4772ec229415 · outbound
This paper cites The Effects of Data Quality on Machine Learning Performance on Tabular Data.
Stress-Testing ML Pipelines with Adversarial Data Corruption The Effects of Data Quality on Machine Learning Performance on Tabular Data
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:54:21.476615Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5a4608b7-2e91-4bbb-888b-6ddd477da902 · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:54:21.537098Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8e439b08-07ae-4794-bd05-c98393280e0a · outbound
This paper cites 2016.Practical machine learning with H2O: powerful, scalable techniques for deep learning and AI.
Stress-Testing ML Pipelines with Adversarial Data Corruption 2016.Practical machine learning with H2O: powerful, scalable techniques for deep learning and AI
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:54:36.465021Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation a6069149-44a2-4774-a194-5cd0a267a034 · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 9
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:36.139167Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation b4b8d264-78f8-4143-a744-e1105e7c31ae · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:54:21.827657Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 96d56041-2d33-407b-a619-15c7a5e6ca36 · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 11
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:35.676814Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 3be4e40d-a078-48f5-8b77-e7cf236e015b · outbound
This paper cites Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning.
Stress-Testing ML Pipelines with Adversarial Data Corruption Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:54:22.040946Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2a8a111e-c6ac-4cca-bb0a-ad9328b37b71 · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 13
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:35.413008Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 4af52504-d53c-4323-9802-e7a01224bf4e · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 14
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:35.195925Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 4aee2b02-ebc8-48e1-aa10-4a8d13677b6e · outbound
This paper cites 2012.Missing data: Analysis and design.
Stress-Testing ML Pipelines with Adversarial Data Corruption 2012.Missing data: Analysis and design
Reference 15
- Resolution
- verified exact
- doi, observed 2026-08-07T11:54:27.082333Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 469d4eef-7875-4575-823e-a573763ca07f · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 16
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:34.997247Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 5312fe1f-b66f-4822-afe0-6982eead7a39 · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 17
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:34.732803Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation a82e45a5-19cc-46e5-bea7-2a0dfccd07c4 · outbound
This paper cites Investigating Labeler Bias in Face Annotation for Machine Learning.
Stress-Testing ML Pipelines with Adversarial Data Corruption Investigating Labeler Bias in Face Annotation for Machine Learning
Reference 18
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T11:54:27.735763Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 39448dcd-1f1b-42ad-858d-111ee1ea4628 · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:54:22.878365Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9b3492b7-f21f-4d70-a9d1-3c35ed76e2c7 · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 20
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:34.508527Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 01876e31-e8c6-4dbf-ad48-a7e9fe71da6d · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 21
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:34.300923Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 35a3d42b-1796-47e7-a5ae-cad350bfc579 · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:54:23.217217Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation be7b83f5-df58-4724-9c85-2b256fd0337a · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 23
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:34.033389Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation ccf76ebf-a75e-4f99-8da8-657f372d11e0 · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 24
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:33.809839Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation a991c2ab-e9bc-40a8-8e86-092159b8576f · outbound
This paper cites BoostClean: Automated Error Detection and Repair for Machine Learning.
Stress-Testing ML Pipelines with Adversarial Data Corruption BoostClean: Automated Error Detection and Repair for Machine Learning
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:54:23.663962Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b4f3595d-033f-48c7-a501-b00bbb6a3eb3 · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 26
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:33.615948Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation c227212b-1754-45ef-a0e4-f091d330168c · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 27
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:33.400316Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 48b5821f-0355-4a12-9c5b-d8a9efe62765 · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 28
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:33.006356Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 618aae0f-be31-4f01-b735-ba1b38267783 · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 29
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:32.769115Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 802bfda8-c9ad-4523-8e8d-ed42977495a5 · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 30
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:32.541713Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation e13f4f7b-a2c4-4b1b-9d8c-638dcafa24b5 · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 31
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:32.318453Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation b3cffc80-bd46-4ed8-b01f-a1d76c3efa0b · outbound
This paper cites Indiscriminate Data Poisoning Attacks on Neural Networks.
Stress-Testing ML Pipelines with Adversarial Data Corruption Indiscriminate Data Poisoning Attacks on Neural Networks
Reference 32
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T11:54:27.296290Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation ed3ec94b-3471-4d52-bbda-a59a77cf0beb · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 33
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:32.085731Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 34e83cd5-0512-4609-a503-6ee3c4f6edf4 · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 34
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:31.888485Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 109aa4d3-d6ce-41e0-9b66-fe3911154cb9 · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 35
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:54:24.756304Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c7e807a7-43ac-4c88-b534-c2e07360514c · outbound
This paper cites 2024.Artificial Intelligence Risk Management Framework (1.0) – Generative AI Profile.
Stress-Testing ML Pipelines with Adversarial Data Corruption 2024.Artificial Intelligence Risk Management Framework (1.0) – Generative AI Profile
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:54:31.432206Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation acb152da-3e8b-43de-af7f-d87774a9646a · outbound
This paper cites 2009.Causality.
Stress-Testing ML Pipelines with Adversarial Data Corruption 2009.Causality
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:54:24.973293Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d1d6b7a9-7f15-4128-aa4f-e75347d8fe6b · outbound
This paper cites Pedregosa, G.
Stress-Testing ML Pipelines with Adversarial Data Corruption Pedregosa, G
Reference 38
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:54:25.061771Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bb66c0c1-47d5-4f34-93a6-7ecb9a7e110f · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 39
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:31.246334Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 1320b36a-645c-4231-b64b-51033c5f232d · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 40
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:30.864413Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 23b1d840-25d7-41c6-9557-44fc2e70580c · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 41
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:30.668898Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 2b50507f-6b2c-45b0-99e0-3b93ba3dd0f5 · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 42
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:30.469340Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 0eef91ae-40f3-4ac1-bfbd-21df52516244 · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 43
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:30.225751Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 2685127d-3f9c-4039-b1ae-6d3f1af60241 · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 44
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:30.020291Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation cf762c32-cfd5-4ad5-b17c-f5c20a74b3b7 · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 45
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:54:25.784286Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a64b94dd-39a3-4b0e-8a97-6069245ab1a1 · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 46
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:29.782478Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 8f10eb71-12e3-439d-8813-6e49073a4f15 · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 47
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:29.555863Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 7f3ae5b3-bd4d-4f24-b07d-7b14476e6c19 · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 48
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:29.346598Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation f7f610b5-00ef-4c16-a333-84c4fafef418 · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 49
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:29.153189Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation efa966b4-a9fc-4428-9389-278c86a29987 · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 50
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:28.968339Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation e0629252-0aca-49d4-8f86-e289d3c1e870 · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 51
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:28.765142Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation ec50611d-fad3-4cf1-8797-da537cbb9f8b · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 52
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:28.585714Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation c4e73516-7489-4295-bbc3-02ce4bca83ee · outbound
This paper cites Zemel, Yu Wu, Kevin Swersky, Toniann Pitassi, and Cynthia Dwork.
Stress-Testing ML Pipelines with Adversarial Data Corruption Zemel, Yu Wu, Kevin Swersky, Toniann Pitassi, and Cynthia Dwork
Reference 53
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:54:26.577984Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f181a355-7ea0-4e3b-aff9-8ee2ad1a0cbd · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 54
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:28.208567Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation d7aa7107-8553-4536-bcdc-42c2f23a5fcf · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 55
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:27.979173Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation b440acd8-a1d4-4349-ae0c-a3e56209d1dd · outbound
This paper cites InICML (3) (JMLR Workshop and Conference Proceedings), Vol.
Stress-Testing ML Pipelines with Adversarial Data Corruption InICML (3) (JMLR Workshop and Conference Proceedings), Vol
Reference 2013
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:54:28.421970Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 4ca936c6-dfac-4853-82c8-1ca36b97dd70 · outbound
This paper cites unknown.
Stress-Testing ML Pipelines with Adversarial Data Corruption unknown
Reference 2017
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:54:31.641593Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 5f9cd1b7-239b-48db-82ae-e3ae84574ec9 · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 2018
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:33.194885Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 8c63412e-f0e9-4aad-9fdb-8eab27dd23de · outbound
This paper cites Explaining Inference Queries with Bayesian Optimization.
Stress-Testing ML Pipelines with Adversarial Data Corruption Explaining Inference Queries with Bayesian Optimization
Reference 2021
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T11:54:27.498156Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation f146a1e5-510a-489d-b325-ce2f12fd02c1 · outbound
This paper cites InNeurIPS ML Safety Workshop.
Stress-Testing ML Pipelines with Adversarial Data Corruption InNeurIPS ML Safety Workshop
Reference 2022
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:54:35.941835Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation e8405f72-c5b4-4196-87e2-d6512dc04b0b · outbound
This paper cites an unresolved cited work.
Stress-Testing ML Pipelines with Adversarial Data Corruption Unresolved cited work
Reference 2023
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:54:31.047313Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 2eb47ec1-52a4-415d-a94f-f794c9a6cea7 · outbound
This paper cites Still More Shades of Null: An Evaluation Suite for Responsible Missing Value Imputation.
Stress-Testing ML Pipelines with Adversarial Data Corruption Still More Shades of Null: An Evaluation Suite for Responsible Missing Value Imputation
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:54:23.561978Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
No inbound Pith citation observations are available.