Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data | Paper Citation Record

Observation ff3fdae1-ea52-4ff2-a0e8-1385a4a27ac0 · outbound

This paper cites Causal discovery in heterogeneous environments under the sparse mechanism shift hypothesis.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Causal discovery in heterogeneous environments under the sparse mechanism shift hypothesis

Reference 1

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Observation 594c3ca8-e596-4895-bba0-f9c6de87d881 · outbound

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Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Unresolved cited work

Reference 2

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Observation 27ce36b9-5354-4271-9c0c-b86c573c892c · outbound

This paper cites Deep neural networks and tabular data: A survey.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Deep neural networks and tabular data: A survey

Reference 3

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Observation d7e5f621-6d6d-4e4f-9dc6-59a715d21b1a · outbound

This paper cites Why Tabular Foundation Models Should Be a Research Priority.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Why Tabular Foundation Models Should Be a Research Priority

Reference 4

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Observation b9667d4b-9ab9-4494-9207-00e1308321bc · outbound

This paper cites Empirical evaluation of performance degradation of machine learning-based predictive models–a case study in healthcare information systems.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Empirical evaluation of performance degradation of machine learning-based predictive models–a case study in healthcare information systems

Reference 5

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Observation 74763026-97d9-4ac6-97ab-f4868820ee3e · outbound

This paper cites Temporal shifts in clinical presen- tation and underlying mechanisms of atherosclerotic disease.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Temporal shifts in clinical presen- tation and underlying mechanisms of atherosclerotic disease

Reference 6

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Observation 3b6e4a25-4f90-49a3-94f6-47512bb4ec1d · outbound

This paper cites Mortality prediction of covid-19 patients at intensive care unit admission.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Mortality prediction of covid-19 patients at intensive care unit admission

Reference 7

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Observation 5b7683e3-10f3-4ba5-a75e-5e33da62b089 · outbound

This paper cites Climate-invariant machine learning.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Climate-invariant machine learning

Reference 8

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Observation ea2f7d73-786b-423c-875b-77c9dd4bd180 · outbound

This paper cites Dataset shift quantification for credit card fraud detection.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Dataset shift quantification for credit card fraud detection

Reference 9

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Observation f6374141-50c4-4b60-a0f8-ee6d3da9b0cf · outbound

This paper cites Hidden risks of machine learning applied to healthcare: Unintended feedback loops between models and future data causing model degradation.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Hidden risks of machine learning applied to healthcare: Unintended feedback loops between models and future data causing model degradation

Reference 10

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Observation de5a87e8-dc49-4bec-9094-03d11d4547ae · outbound

This paper cites Wild-time: A benchmark of in-the-wild distribution shift over time.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Wild-time: A benchmark of in-the-wild distribution shift over time

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-12T19:33:25.675414Z

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Observation 0285530f-251d-4d9e-975e-3cb8384f5cb8 · outbound

This paper cites Temporal domain generalization with drift-aware dynamic neural networks.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Temporal domain generalization with drift-aware dynamic neural networks

Reference 12

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Observation caa25ab8-a7b7-4e5e-b457-b18be6dc45fb · outbound

This paper cites Training for the future: A simple gradient interpolation loss to generalize along time.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Training for the future: A simple gradient interpolation loss to generalize along time

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-12T19:33:25.799834Z

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Observation a4e2280d-2b4c-4324-87eb-439bc2b22317 · outbound

This paper cites Benchmarking distribution shift in tabular data with tableshift.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Benchmarking distribution shift in tabular data with tableshift

Reference 14

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Observation 5d9f10ad-e02c-4833-b094-95853bbb8b3f · outbound

This paper cites Revisiting deep learning models for tabular data.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Revisiting deep learning models for tabular data

Reference 15

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Observation 98737137-85d4-4888-8da6-70bbf49344a3 · outbound

This paper cites Tabular data: Deep learning is not all you need.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Tabular data: Deep learning is not all you need

Reference 16

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Observation 6fdb45cd-624a-4945-9b78-fb20a8f8f60c · outbound

This paper cites Why do tree-based models still outperform deep learning on typical tabular data? In Alice H.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Why do tree-based models still outperform deep learning on typical tabular data? In Alice H

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-12T19:33:25.898054Z

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Observation f99c0e9c-234f-4e18-b5a4-43005afdb498 · outbound

This paper cites Müller, N.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Müller, N

Reference 18

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Observation 32f11b0d-07d1-4c51-965b-a34e9fe876d4 · outbound

This paper cites Hollmann, S.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Hollmann, S

Reference 19

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Observation 37e1cf91-1f75-4dfd-8787-89dd0004bd7b · outbound

This paper cites Causality.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Causality

Reference 20

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Observation aef39098-c4c9-4baa-bcae-f74db8f87ece · outbound

This paper cites Peters, D.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Peters, D

Reference 21

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Observation 08e8536e-83fc-4242-bdec-17bef582dbcf · outbound

This paper cites Time2vec: Learning a vector representation of time, 2020.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Time2vec: Learning a vector representation of time, 2020

Reference 22

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Observation 0132240f-ee05-4ac8-8d8c-29ba4535afa0 · outbound

This paper cites Chen and C.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Chen and C

Reference 23

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Observation f9abc6af-95f3-40fe-803a-c7fb2faec365 · outbound

This paper cites Prokhorenkova, G.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Prokhorenkova, G

Reference 24

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Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Unresolved cited work

Reference 25

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Observation 2d8dbbb9-d32e-4163-9332-9baa57d8311f · outbound

This paper cites Continuously indexed domain adaptation.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Continuously indexed domain adaptation

Reference 26

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Observation 56615ff2-9eb8-416c-a886-02240d624482 · outbound

This paper cites Selçuk Candan, Adrienne Raglin, and Huan Liu.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Selçuk Candan, Adrienne Raglin, and Huan Liu

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-12T19:33:26.135948Z

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Observation b6736780-2672-459e-816c-10d579d579eb · outbound

This paper cites Domain generalization via invariant feature representation.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Domain generalization via invariant feature representation

Reference 28

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Observation 6cbcf79c-1e56-491c-bce7-ecf12d6c9fc6 · outbound

This paper cites Metareg: Towards domain generalization using meta-regularization.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Metareg: Towards domain generalization using meta-regularization

Reference 29

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Observation 36d8c157-98ab-464f-bc32-2cf717fe44fd · outbound

This paper cites Unified deep supervised domain adaptation and generalization.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Unified deep supervised domain adaptation and generalization

Reference 30

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Observation 34797a80-248c-4abe-bf39-47cbfa082100 · outbound

This paper cites Invariant risk mini- mization, 2020.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Invariant risk mini- mization, 2020

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:31.842010Z

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Observation c96facbc-46e1-4f99-ae95-db152703f25e · outbound

This paper cites Hashimoto, and Percy Liang.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Hashimoto, and Percy Liang

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:31.692456Z

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Observation a702ad57-dfd0-41fc-9dd8-7a32126a4614 · outbound

This paper cites Dauphin, and David Lopez-Paz.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Dauphin, and David Lopez-Paz

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:31.663693Z

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Observation 410de60b-bf62-44e6-ad68-1a0107f68c17 · outbound

This paper cites Improving out-of-distribution robustness via selective augmentation, 2022.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Improving out-of-distribution robustness via selective augmentation, 2022

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:31.626238Z

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Observation 2f3b4bf8-b911-4cbe-985d-bef3582a24b3 · outbound

This paper cites Deep coral: Correlation alignment for deep domain adaptation.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Deep coral: Correlation alignment for deep domain adaptation

Reference 35

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Observation ee1f4627-a9bd-4d80-9ac1-5fa7ab5ec8f8 · outbound

This paper cites Domain-adversarial training of neural networks.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Domain-adversarial training of neural networks

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:31.500124Z

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Observation 40e6d0c6-fe6b-4b6a-8f72-ad6727c62c0e · outbound

This paper cites Out-of-distribution generalization via risk extrapo- lation (rex).

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Out-of-distribution generalization via risk extrapo- lation (rex)

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:31.372664Z

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Observation a287624f-06f2-4afa-9728-e9a71c39cd71 · outbound

This paper cites Pappas, and Bernhard Schölkopf.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Pappas, and Bernhard Schölkopf

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:31.350990Z

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Observation 2bb3e851-8787-4e75-86e2-748250d6b86b · outbound

This paper cites Shifts: A Dataset of Real Distributional Shift Across Multiple Large-Scale Tasks.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Shifts: A Dataset of Real Distributional Shift Across Multiple Large-Scale Tasks

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-12T19:33:26.356287Z

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Observation c83ff9e9-6db1-495c-8e5a-ca2e867021e8 · outbound

This paper cites Shifts 2.0: Extending The Dataset of Real Distributional Shifts.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Shifts 2.0: Extending The Dataset of Real Distributional Shifts

Reference 40

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Observation fde7f298-c396-4247-b972-0ffbd0e36ef6 · outbound

This paper cites On the need for a language describing distribution shifts: Illustrations on tabular datasets.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data On the need for a language describing distribution shifts: Illustrations on tabular datasets

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-12T19:33:26.407525Z

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Observation 76324576-359a-4181-9419-0a6dd8b32322 · outbound

This paper cites Retiring adult: New datasets for fair machine learning.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Retiring adult: New datasets for fair machine learning

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:31.314668Z

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Observation 68134b1c-2809-49a3-8903-dfeaa7e2cf2c · outbound

This paper cites Wild-Tab: A Benchmark For Out-Of-Distribution Generalization In Tabular Regression.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Wild-Tab: A Benchmark For Out-Of-Distribution Generalization In Tabular Regression

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-12T19:33:26.418326Z

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Observation 8618bc55-3502-4246-9db4-4b4375ff7467 · outbound

This paper cites In search of lost domain generalization.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data In search of lost domain generalization

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:31.275374Z

Source-reported events for the cited work

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Observation de7b3495-06cf-481b-9778-0f9ff929fa10 · outbound

This paper cites an unresolved cited work.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Unresolved cited work

Reference 45

Resolution: unresolved; raw_fallback, observed 2026-08-12T19:33:31.158582Z

Source-reported events for the cited work

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Observation 9b267a98-c5f6-49d8-b674-2a07506cbd75 · outbound

This paper cites Averaging weights leads to wider optima and better generalization.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Averaging weights leads to wider optima and better generalization

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:31.136718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 569a8512-e1e9-45c3-97a7-7f9dad59bc35 · outbound

This paper cites Task agnostic continual learning via meta learning.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Task agnostic continual learning via meta learning

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:31.052994Z

Source-reported events for the cited work

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Observation b9b2cccc-bd3e-4737-b01d-fb70d2511806 · outbound

This paper cites In-Context Data Distillation with TabPFN.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data In-Context Data Distillation with TabPFN

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-12T19:33:26.552104Z

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Observation 71fc548f-8c50-471b-a41c-9e681d0d0f6a · outbound

This paper cites TuneTables: Context Optimization for Scalable Prior-Data Fitted Networks.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data TuneTables: Context Optimization for Scalable Prior-Data Fitted Networks

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-12T19:33:26.563098Z

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Observation 2f63f2bb-efcf-40ae-baea-6ea1ce26ebaa · outbound

This paper cites Forecastpfn: Synthetically-trained zero-shot forecasting.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Forecastpfn: Synthetically-trained zero-shot forecasting

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:31.003478Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4ca4882a-b3b7-4f2a-8f79-365ad44b4e2e · outbound

This paper cites Moreno-Torres, Troy Raeder, Rocío Alaiz-Rodríguez, Nitesh V.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Moreno-Torres, Troy Raeder, Rocío Alaiz-Rodríguez, Nitesh V

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-12T19:33:26.684172Z

Source-reported events for the cited work

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Observation a40f8e2f-8f63-4820-bf29-21aa5791f5f2 · outbound

This paper cites Patterns of dataset shift.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Patterns of dataset shift

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:30.912392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 71765255-0bb3-4425-a0d2-eb692b67b360 · outbound

This paper cites Vanschoren, J.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Vanschoren, J

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:30.720844Z

Source-reported events for the cited work

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Observation 91f81c9a-26ee-43fb-927c-c51410118465 · outbound

This paper cites Individual comparisons by ranking methods.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Individual comparisons by ranking methods

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-12T19:33:26.703510Z

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Observation 0d358dd5-e01a-4d04-99ad-0dbc703b95c9 · outbound

This paper cites A simple sequentially rejective multiple test procedure.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data A simple sequentially rejective multiple test procedure

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:30.680972Z

Source-reported events for the cited work

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Observation df7c2d50-d777-42ac-8430-dc4e5ecaf90c · outbound

This paper cites statistical comparisons of classifiers over multiple data sets.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data statistical comparisons of classifiers over multiple data sets

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:30.604842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3fba7415-2604-47e4-9bb2-f57077412303 · outbound

This paper cites Deep learning for time series classification: a review.Data Mining and Knowledge Discovery, 33(4):917–963, 2019.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Deep learning for time series classification: a review.Data Mining and Knowledge Discovery, 33(4):917–963, 2019

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-12T19:33:26.724924Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e857def-dfbf-4828-87fd-6be879f6cecb · outbound

This paper cites Overcoming catastrophic forgetting in neural networks.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Overcoming catastrophic forgetting in neural networks

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-12T19:33:26.729890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 25199db8-45bb-434f-9043-0777a0ceea60 · outbound

This paper cites Continual learning through synaptic intelligence.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Continual learning through synaptic intelligence

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:30.468937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 785a0d0d-d696-44fd-9deb-99ae4f88ec59 · outbound

This paper cites Efficient lifelong learning with A-GEM.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Efficient lifelong learning with A-GEM

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:30.442780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ae9c9b25-4441-4d14-b900-3285ff6eb350 · outbound

This paper cites A simple framework for contrastive learning of visual representations.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data A simple framework for contrastive learning of visual representations

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:30.418341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6be977cf-6e72-4021-9fda-dcdd04c0eb7f · outbound

This paper cites Unsupervised learning of visual features by contrasting cluster assignments.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Unsupervised learning of visual features by contrasting cluster assignments

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:30.324727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f9e3671d-4c21-4c9e-a21d-70f9bd83c79e · outbound

This paper cites Venkateswarlu.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Venkateswarlu

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:30.301034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c9a3ae9f-b6c3-4ac5-b0df-73a5fe59f3de · outbound

This paper cites Istanbul Stock Exchange.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Istanbul Stock Exchange

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:30.260727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2f4295b0-5f5e-4d6a-a21a-9f00c4049d03 · outbound

This paper cites DeShazo, Chris Gennings, Juan L.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data DeShazo, Chris Gennings, Juan L

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-12T19:33:26.879594Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c4a79ce-c30f-4982-9a5c-4022885199e0 · outbound

This paper cites Data Expo competition.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Data Expo competition

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:30.169530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 73485a16-8993-4701-a5fd-fa53c9731b55 · outbound

This paper cites Everhart, W.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Everhart, W

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:30.091550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e0036112-5bfa-467a-bad2-89eb899360a7 · outbound

This paper cites an unresolved cited work.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Unresolved cited work

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-12T19:33:27.051773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8c19647-0600-4f20-9b8a-016e1ff7e5dc · outbound

This paper cites Occupancy Detection.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Occupancy Detection

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:30.063238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 78d84628-888c-4748-b829-6392d188ac55 · outbound

This paper cites Behavior of the urban traffic of the city of Sao Paulo in Brazil.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Behavior of the urban traffic of the city of Sao Paulo in Brazil

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:30.005629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d322f2f9-fa96-4ab4-85eb-5b52546af695 · outbound

This paper cites Scikit-multiflow: A multi- output streaming framework.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Scikit-multiflow: A multi- output streaming framework

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:29.894462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2cdf0348-d978-4ad4-a666-451daa02067a · outbound

This paper cites Use of nonclonal serum immunoglobulin free light chains to predict overall survival in the general population.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Use of nonclonal serum immunoglobulin free light chains to predict overall survival in the general population

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-12T19:33:27.170828Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 79212911-8d47-4a1a-ad29-ac631420de4f · outbound

This paper cites Prevalence of monoclonal gammopathy of undetermined significance.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Prevalence of monoclonal gammopathy of undetermined significance

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-12T19:33:27.181462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d4ceaf94-25dc-470f-992a-232a2fc77630 · outbound

This paper cites Splice-2 comparative evaluation: Electricity Pricing.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Splice-2 comparative evaluation: Electricity Pricing

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:29.873540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 71fb7712-c532-42df-b1ab-5b86613f55d7 · outbound

This paper cites Learning with drift detection.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Learning with drift detection

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-12T19:33:27.192986Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6bd39cd-c909-4e63-ab37-bd1c66cd2177 · outbound

This paper cites Absenteeism at work.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Absenteeism at work

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:29.852222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d2394b2a-2327-48a9-9de0-30a2f82e6dda · outbound

This paper cites Heart Disease.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Heart Disease

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:29.831523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1359f3fc-0b19-4ab0-8fce-3f0f4786feda · outbound

This paper cites Parking Birmingham.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Parking Birmingham

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:29.810006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9b792511-5342-4c1f-9f39-f1ea3802d6f9 · outbound

This paper cites Ames, iowa: Alternative to the boston housing data as an end of semester regression project.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Ames, iowa: Alternative to the boston housing data as an end of semester regression project

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-12T19:33:27.392153Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47f734dd-4f80-4036-bbb1-c9b923861a0a · outbound

This paper cites Combining similarity in time and space for training set formation under concept drift.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Combining similarity in time and space for training set formation under concept drift

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:29.777064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a0bb2b86-9129-4396-b1ef-cbfe339751aa · outbound

This paper cites A Closer Look at In-Context Learning under Distribution Shifts.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data A Closer Look at In-Context Learning under Distribution Shifts

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-12T19:33:27.456551Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f83d5219-a0f9-494d-b357-3814def7f3d4 · outbound

This paper cites In healthcare, this can ensure diagnostic and prognostic models remain reliable as data shifts over time.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data In healthcare, this can ensure diagnostic and prognostic models remain reliable as data shifts over time

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:29.688331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9b8ba75d-4fa7-4a57-8120-a067c88cf691 · outbound

This paper cites Our Bayesian approach for tackling distribution shift provides a new perspective that can spur further methodological innovations.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Our Bayesian approach for tackling distribution shift provides a new perspective that can spur further methodological innovations

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:29.554985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation aa6c1a6e-cf7e-4425-990e-d32afe18348a · outbound

This paper cites an unresolved cited work.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Unresolved cited work

Reference 86

Resolution: unresolved; raw_fallback, observed 2026-08-12T19:33:29.527602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5aa0ef8b-beb3-4cba-9758-5a59240ae8f8 · outbound

This paper cites However, we note that these costs are one-time, while the resulting model can be applied with minimal energy usage.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data However, we note that these costs are one-time, while the resulting model can be applied with minimal energy usage

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:29.504162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 864b2f7f-8f88-41bc-8de7-c205558ba0a9 · outbound

This paper cites an unresolved cited work.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Unresolved cited work

Reference 88

Resolution: unresolved; raw_fallback, observed 2026-08-12T19:33:29.481256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 105c4e6f-2799-4f98-a4b7-b21487ea37ac · outbound

This paper cites an unresolved cited work.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Unresolved cited work

Reference 89

Resolution: unresolved; raw_fallback, observed 2026-08-12T19:33:29.429833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7371968e-a09f-4ea3-ac8a-4d8aa50c969b · outbound

This paper cites an unresolved cited work.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Unresolved cited work

Reference 90

Resolution: unresolved; raw_fallback, observed 2026-08-12T19:33:29.265035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 279e387b-6b11-4eb2-8783-cb23bb4a6d6d · outbound

This paper cites Both TabPFN-base and Drift-Resilient TabPFN underwent preprocessing optimization that utilized 8 CPUs, 1 GPU, and 62.5 GB RAM across 300 runs, each lasting between 0.5 to 1 hour.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Both TabPFN-base and Drift-Resilient TabPFN underwent preprocessing optimization that utilized 8 CPUs, 1 GPU, and 62.5 GB RAM across 300 runs, each lasting between 0.5 to 1 hour

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:29.170751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 78f3127a-2f8e-4086-9a86-fd957411ab57 · outbound

This paper cites Slowness in traffic (%).

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Slowness in traffic (%)

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:29.148832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 900c2ac6-e4ed-48e7-9676-07dd049905e8 · outbound

This paper cites Comprehensive evaluations across 18 synthetic and real-world datasets.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Comprehensive evaluations across 18 synthetic and real-world datasets

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:29.131984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1d996789-4471-4a8d-b05d-2d3ebc5e6640 · outbound

This paper cites Conclusions and Limitations.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Conclusions and Limitations

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:29.114842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 30954458-05e8-4e91-9432-cc717ea9bd7c · outbound

This paper cites an unresolved cited work.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Unresolved cited work

Reference 95

Resolution: unresolved; raw_fallback, observed 2026-08-12T19:33:29.095538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1eabdb3d-75b6-4d42-a9ed-efa986d0cfc4 · outbound

This paper cites Reproducibility.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Reproducibility

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:29.069849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 57ca138a-a260-4241-a294-6ea39632a71b · outbound

This paper cites Reproducibility.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Reproducibility

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:28.923479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ac32025f-c888-4457-8fa7-b3371bf84703 · outbound

This paper cites Reproducibility.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Reproducibility

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:28.903439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9a46ee45-3113-4560-a637-944838b1d9d5 · outbound

This paper cites We report 95% Confidence Intervals in all our quantitative results and mark this appropriately in the paper.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data We report 95% Confidence Intervals in all our quantitative results and mark this appropriately in the paper

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:28.883505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 625c03f4-d3ba-402d-8d86-59589763991a · outbound

This paper cites See Section A.3 for details.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data See Section A.3 for details

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:28.860031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e8885fb7-df4a-49c7-b235-7a380178b1c6 · outbound

This paper cites an unresolved cited work.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Unresolved cited work

Reference 101

Resolution: unresolved; no resolver link, observed 2026-08-12T19:33:27.945426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb54159e-dcd9-4179-9623-80e16b10c2ae · outbound

This paper cites Please see Section A.2 for details.

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data Please see Section A.2 for details

Reference 102

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:33:28.820935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers