Paper Citation Record · LEDGER

TabPFN-3: Technical Report

As of 5 August 2026, this Paper Citation Record lists 100 of 299 outbound references and 19 inbound Pith citation observations for arXiv:2605.13986.

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

pith.paper-citation-record.v1
2605.13986 v2

Coverage vector

measured 100 of 299 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-30T21:37:08.627791Z

measured 119 of 119 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 19 of 19 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T00:36:01.676639Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-07T14:03:48.750353Z

Reference resolution

100 of 299 outbound references displayed

verified exact48
verified fuzzy47
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch5

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4e0ffd9c-89f1-41e4-b2da-c83ab6a0003d · outbound

This paper cites TabArena: A Living Benchmark for Machine Learning on Tabular Data.

TabPFN-3: Technical Report TabArena: A Living Benchmark for Machine Learning on Tabular Data

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-07-01T14:25:46.576647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 447ddd50-230b-4bb3-96a0-57b213e9cd0f · outbound

This paper cites AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data.

TabPFN-3: Technical Report AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-07-01T14:25:46.539747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 4978bc88-1899-47cb-8103-5ae4e1894478 · outbound

This paper cites A targeted real-time early warning score (trewscore) for septic shock.Science translational medicine, 7(299):299ra122–299ra122.

TabPFN-3: Technical Report A targeted real-time early warning score (trewscore) for septic shock.Science translational medicine, 7(299):299ra122–299ra122

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.654404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation b2688a04-41e9-496f-8529-c3ecbd482e9a · outbound

This paper cites Mimic-iii, a freely accessible critical care database.Scientific data, 3(1):1–9.

TabPFN-3: Technical Report Mimic-iii, a freely accessible critical care database.Scientific data, 3(1):1–9

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.638472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation b7f75928-07b7-4278-a068-e0c1e3be04c1 · outbound

This paper cites Deep neural networks detect suicide risk from textual facebook posts.Scientific reports, 10(1):16685.

TabPFN-3: Technical Report Deep neural networks detect suicide risk from textual facebook posts.Scientific reports, 10(1):16685

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.707544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f7934433-15a5-4286-9fef-f2a704801015 · outbound

This paper cites Credit scoring, statistical techniques and evaluation criteria: a review of the literature.Intelligent systems in accounting, finance and management, 18(2-3):59–88.

TabPFN-3: Technical Report Credit scoring, statistical techniques and evaluation criteria: a review of the literature.Intelligent systems in accounting, finance and management, 18(2-3):59–88

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.591000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation dd8cc744-ef8c-4b9d-ab47-bbb1565fc7e2 · outbound

This paper cites Consumer credit-risk models via machine- learning algorithms.Journal of Banking & Finance, 34(11):2767–2787.

TabPFN-3: Technical Report Consumer credit-risk models via machine- learning algorithms.Journal of Banking & Finance, 34(11):2767–2787

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.701819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 40edc03c-853b-4030-bc03-b9e6341c6e29 · outbound

This paper cites Benchmarking state-of- the-art classification algorithms for credit scoring: An update of research.European journal of operational research, 247(1):124–136.

TabPFN-3: Technical Report Benchmarking state-of- the-art classification algorithms for credit scoring: An update of research.European journal of operational research, 247(1):124–136

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.632542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 40e69383-5917-4d97-8bad-c98a41a9d91b · outbound

This paper cites A systematic literature review of machine learning methods applied to predictive maintenance.Computers & industrial engineering, 137:106024.

TabPFN-3: Technical Report A systematic literature review of machine learning methods applied to predictive maintenance.Computers & industrial engineering, 137:106024

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.634529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 6d0d1451-5279-40a4-b877-38e9232e7134 · outbound

This paper cites Machine learning and reasoning for predictive maintenance in industry 4.0: Current status and challenges.Computers in industry, 123:103298.

TabPFN-3: Technical Report Machine learning and reasoning for predictive maintenance in industry 4.0: Current status and challenges.Computers in industry, 123:103298

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.626858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 7d480d19-f47a-4636-a4ee-32cef6d474fa · outbound

This paper cites Searching for exotic particles in high-energy physics with deep learning.Nature communications, 5(1):4308.

TabPFN-3: Technical Report Searching for exotic particles in high-energy physics with deep learning.Nature communications, 5(1):4308

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.611045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 5f8cbf39-7300-4d21-9d00-7a81f9273d5b · outbound

This paper cites Benchmarking materials property prediction methods: the matbench test set and automatminer reference algorithm.npj Computational Materials, 6(1):138.

TabPFN-3: Technical Report Benchmarking materials property prediction methods: the matbench test set and automatminer reference algorithm.npj Computational Materials, 6(1):138

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.613215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 2c77560a-620c-4df8-844d-da5629424d91 · outbound

This paper cites Tabular data: Deep learning is not all you need.Information fusion, 81:84–90.

TabPFN-3: Technical Report Tabular data: Deep learning is not all you need.Information fusion, 81:84–90

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.615408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation c9ba4854-3375-43d5-aade-126f6c272fa3 · outbound

This paper cites Why do tree-based models still outperform deep learning on typical tabular data?Advances in neural information processing systems, 35: 507–520.

TabPFN-3: Technical Report Why do tree-based models still outperform deep learning on typical tabular data?Advances in neural information processing systems, 35: 507–520

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.696192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 7d6a7dcf-235e-4cfa-8940-02f6f7133746 · outbound

This paper cites Tabrepo: A large scale repository of tabular model evaluations and its automl applications.

TabPFN-3: Technical Report Tabrepo: A large scale repository of tabular model evaluations and its automl applications

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.648220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 88717625-1e0c-47a1-8a17-a9c0a8d15845 · outbound

This paper cites TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second.

TabPFN-3: Technical Report TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-07-01T14:25:46.549615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 80a46797-5332-4e44-abbf-9cbb998d7ba2 · outbound

This paper cites Accurate predictions on small data with a tab- ular foundation model.Nature, 637(8045):319–326.

TabPFN-3: Technical Report Accurate predictions on small data with a tab- ular foundation model.Nature, 637(8045):319–326

Reference 17

Resolution: verified exact; doi, observed 2026-06-30T21:45:05.168811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 36357548-2279-4c7d-b6b3-b1466d1c2faf · outbound

This paper cites Tabpfn-2.5: Advancing the state of the art in tabular foundation models, 2025.

TabPFN-3: Technical Report Tabpfn-2.5: Advancing the state of the art in tabular foundation models, 2025

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.630730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 311d750f-220d-43fd-9de4-e36b50f8d463 · outbound

This paper cites The tabular foundation model tabpfn outperforms specialized time series forecasting models based on simple features.

TabPFN-3: Technical Report The tabular foundation model tabpfn outperforms specialized time series forecasting models based on simple features

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.602295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d5cb4e4d-c68b-4b9e-956b-d4caa9c577c8 · outbound

This paper cites Do-pfn: In-context learning for causal effect estimation.

TabPFN-3: Technical Report Do-pfn: In-context learning for causal effect estimation

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:25:46.568408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 3943106a-b1f2-43a6-b634-1a9d5948545b · outbound

This paper cites Cresswell, and Rahul G.

TabPFN-3: Technical Report Cresswell, and Rahul G

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.646347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 0964994b-ab75-41ba-8baf-456465530e25 · outbound

This paper cites Causalpfn: Amortized causal effect estimation via in-context learning.

TabPFN-3: Technical Report Causalpfn: Amortized causal effect estimation via in-context learning

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:25:46.571128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation c6bc4492-6e90-424c-8074-0ed93a4aebc0 · outbound

This paper cites Foundation models for causal inference via prior-data fitted networks.arXiv preprint arXiv:2506.10914.

TabPFN-3: Technical Report Foundation models for causal inference via prior-data fitted networks.arXiv preprint arXiv:2506.10914

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:25:46.443628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 136b98e5-b389-45c4-a3d9-2f87d233beb1 · outbound

This paper cites AceReason-Nemotron: Advancing math and code reasoning through reinforcement learning.

TabPFN-3: Technical Report AceReason-Nemotron: Advancing math and code reasoning through reinforcement learning

Reference 24

Resolution: metadata mismatch; doi, observed 2026-06-30T21:45:05.166459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f8a4bedc-7798-41a2-9b54-912ca3456479 · outbound

This paper cites Bringing graphs to the table: Zero-shot node classification via tabular foundation models.

TabPFN-3: Technical Report Bringing graphs to the table: Zero-shot node classification via tabular foundation models

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-06-30T21:45:05.062858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 55e4284f-f14f-443c-bb4b-a56236496a2c · outbound

This paper cites Turning Tabular Foundation Models into Graph Foundation Models.

TabPFN-3: Technical Report Turning Tabular Foundation Models into Graph Foundation Models

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-07-01T14:25:46.487628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f3b1be38-98cd-4ac1-aee6-3b6470c87cbe · outbound

This paper cites Interpretable machine learning for tabpfn.

TabPFN-3: Technical Report Interpretable machine learning for tabpfn

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.517424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 79247e19-68f6-4d82-9586-a065535037cc · outbound

This paper cites A closer look at tabpfn v2: Understanding its strengths and extending its capabilities.Advances in Neural Information Processing Systems, 38: 135605–135637.

TabPFN-3: Technical Report A closer look at tabpfn v2: Understanding its strengths and extending its capabilities.Advances in Neural Information Processing Systems, 38: 135605–135637

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.636564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation c437cc73-60fe-42b7-9068-49ab338a071a · outbound

This paper cites ICR-RL: Deep Reinforcement Learning via In-Context Regression.

TabPFN-3: Technical Report ICR-RL: Deep Reinforcement Learning via In-Context Regression

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-07-07T02:19:40.488978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation e9b92845-8636-4ed8-8ff4-b1bc96455517 · outbound

This paper cites TabICL: A tabular foundation model for in-context learning on large data.

TabPFN-3: Technical Report TabICL: A tabular foundation model for in-context learning on large data

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.594526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d4e9dc30-efc1-4b8f-bc2a-f15ad9479dc8 · outbound

This paper cites TabICLv2: A better, faster, scalable, and open tabular foundation model.

TabPFN-3: Technical Report TabICLv2: A better, faster, scalable, and open tabular foundation model

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.596213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 45c62d5c-a0b1-49e2-907c-bd68b278b9b6 · outbound

This paper cites Scalable-Softmax Is Superior for Attention.

TabPFN-3: Technical Report Scalable-Softmax Is Superior for Attention

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:25:46.516167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 2e6dab81-04d4-41eb-82b8-51e3997f5422 · outbound

This paper cites EquitabPFN: A target-permutation equivariant prior fitted network.

TabPFN-3: Technical Report EquitabPFN: A target-permutation equivariant prior fitted network

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.679824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f5ce7af8-56a7-4b18-acd6-62b986889ee6 · outbound

This paper cites Towards local- ization via data embedding for tabpfn.

TabPFN-3: Technical Report Towards local- ization via data embedding for tabpfn

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.683725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 8f5644f0-35e1-475d-a766-e2f6a3fa71ba · outbound

This paper cites Better by default: Strong pre-tuned mlps and boosted trees on tabular data.

TabPFN-3: Technical Report Better by default: Strong pre-tuned mlps and boosted trees on tabular data

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.580604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 0e1d4554-1602-4471-9409-aaa1feb28423 · outbound

This paper cites FlashAttention-3: fast and accurate attention with asynchrony and low-precision.

TabPFN-3: Technical Report FlashAttention-3: fast and accurate attention with asynchrony and low-precision

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.681882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 745d6fab-2720-4cdf-8441-3b3999e43d41 · outbound

This paper cites shapiq: Shapley interactions for machine learning.

TabPFN-3: Technical Report shapiq: Shapley interactions for machine learning

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.664933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f8a05b26-a279-4c5a-9983-7a786e50c719 · outbound

This paper cites Dynamic Structural Causal Models.

TabPFN-3: Technical Report Dynamic Structural Causal Models

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-07-21T02:21:14.700558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 5e46b47d-a85d-4c8d-83d0-42a779552f2a · outbound

This paper cites Talent: A tabular analytics and learning toolbox.Journal of Machine Learning Research, 26 (226):1–16.

TabPFN-3: Technical Report Talent: A tabular analytics and learning toolbox.Journal of Machine Learning Research, 26 (226):1–16

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.670387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d05b525a-8125-46fb-b474-c062b8cca904 · outbound

This paper cites TabSTAR: A Tabular Foundation Model for Tabular Data with Text Fields.

TabPFN-3: Technical Report TabSTAR: A Tabular Foundation Model for Tabular Data with Text Fields

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.676013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 15b1072c-6443-4faa-88ed-8102f087c166 · outbound

This paper cites Catboost: unbiased boosting with categorical features.Advances in neural information processing systems, 31.

TabPFN-3: Technical Report Catboost: unbiased boosting with categorical features.Advances in neural information processing systems, 31

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.582844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 6463f9bc-b15f-4b4b-8fcb-575277a09d10 · outbound

This paper cites Lightgbm: A highly efficient gradient boosting decision tree.

TabPFN-3: Technical Report Lightgbm: A highly efficient gradient boosting decision tree

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.649212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 2255d3ae-e4d4-42e1-b3ee-15018565591e · outbound

This paper cites Xgboost: A scalable tree boosting system.

TabPFN-3: Technical Report Xgboost: A scalable tree boosting system

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.643539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 43429292-56d4-4b0f-a628-24ae2bf4f74a · outbound

This paper cites Tabm: Advancing tabular deep learning with parameter-efficient ensembling.

TabPFN-3: Technical Report Tabm: Advancing tabular deep learning with parameter-efficient ensembling

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.699951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation ed6aa85a-0b3c-4490-9434-c0f123c6ec7d · outbound

This paper cites Revisiting nearest neighbor for tabular data: A deep tabular baseline two decades later.

TabPFN-3: Technical Report Revisiting nearest neighbor for tabular data: A deep tabular baseline two decades later

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.698079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 41cc0fa0-74f7-4378-8c6b-45f8e273fa87 · outbound

This paper cites xRFM: Accurate, scalable, and interpretable feature learning models for tabular data.

TabPFN-3: Technical Report xRFM: Accurate, scalable, and interpretable feature learning models for tabular data

Reference 46

Resolution: verified exact; local_arxiv, observed 2026-07-01T14:25:46.573657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 9d64aee4-375e-4aa3-a39d-617f966898bc · outbound

This paper cites Cresswell, Keyvan Golestan, Guangwei Yu, Anthony L.

TabPFN-3: Technical Report Cresswell, Keyvan Golestan, Guangwei Yu, Anthony L

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.703811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 92eac2de-4ee5-4678-a810-91b28fcb40d2 · outbound

This paper cites Limix: Unleashing structured- data modeling capability for generalist intelligence.

TabPFN-3: Technical Report Limix: Unleashing structured- data modeling capability for generalist intelligence

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:25:46.560273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 4e410f18-0ef7-4b5c-8b6f-c46ea4b1dad2 · outbound

This paper cites Maddix, Junming Yin, Nick Erickson, Abdul Fatir Ansari, Boran Han, Shuai Zhang, Leman Akoglu, Christos Faloutsos, Michael W.

TabPFN-3: Technical Report Maddix, Junming Yin, Nick Erickson, Abdul Fatir Ansari, Boran Han, Shuai Zhang, Leman Akoglu, Christos Faloutsos, Michael W

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.705663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation fd8a62bf-d6a7-497c-b1c2-875fa67bf5d1 · outbound

This paper cites Benchmarking Multimodal AutoML for Tabular Data with Text Fields.

TabPFN-3: Technical Report Benchmarking Multimodal AutoML for Tabular Data with Text Fields

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:25:46.581653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation ab4b746b-427d-43a0-8216-f32d821d5c5c · outbound

This paper cites Vectorizing string entries for data processing on tables: when are larger language models better?.

TabPFN-3: Technical Report Vectorizing string entries for data processing on tables: when are larger language models better?

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:25:46.584388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 40ccc56a-727e-4489-b8c5-b71e1c2b8f4a · outbound

This paper cites CARTE: Pretraining and Transfer for Tabular Learning.

TabPFN-3: Technical Report CARTE: Pretraining and Transfer for Tabular Learning

Reference 52

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T14:25:46.569152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 016af418-ff4c-4266-89d1-3bc36a16e6b2 · outbound

This paper cites Regression quantiles.Econometrica, 46(1):33–50.

TabPFN-3: Technical Report Regression quantiles.Econometrica, 46(1):33–50

Reference 53

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:25:46.574151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 085e4565-0dba-4310-a97e-cde710d12d65 · outbound

This paper cites Quantile regression forests.Journal of Machine Learning Research, 7:983–999.

TabPFN-3: Technical Report Quantile regression forests.Journal of Machine Learning Research, 7:983–999

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.622695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 05d1eaef-c0da-4669-a89a-edec007053e7 · outbound

This paper cites fev-bench: A Realistic Benchmark for Time Series Forecasting.

TabPFN-3: Technical Report fev-bench: A Realistic Benchmark for Time Series Forecasting

Reference 55

Resolution: metadata mismatch; local_arxiv, observed 2026-07-01T14:25:46.449399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 8f46dcd8-9a6a-4c41-bec5-cd17ebedfcd4 · outbound

This paper cites Chronos-2: From Univariate to Universal Forecasting.

TabPFN-3: Technical Report Chronos-2: From Univariate to Universal Forecasting

Reference 56

Resolution: metadata mismatch; local_arxiv, observed 2026-07-01T14:25:46.465724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation aedc2131-164a-46c2-af56-5f60ac2ebf51 · outbound

This paper cites Tirex: Zero-shot forecasting across long and short horizons with enhanced in-context learning.

TabPFN-3: Technical Report Tirex: Zero-shot forecasting across long and short horizons with enhanced in-context learning

Reference 57

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:25:46.566439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation c6a3047c-fd1f-4b9e-a636-739c54f90473 · outbound

This paper cites A decoder-only foundation model for time-series forecasting.

TabPFN-3: Technical Report A decoder-only foundation model for time-series forecasting

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.689484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation b92eed98-79b6-4d42-99d4-c4487bf9a1a1 · outbound

This paper cites KumoRFM-2: Scaling Foundation Models for Relational Learning.

TabPFN-3: Technical Report KumoRFM-2: Scaling Foundation Models for Relational Learning

Reference 59

Resolution: verified exact; local_arxiv, observed 2026-07-01T14:25:46.455379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a967a515-a401-43b6-9c2a-cc898985172b · outbound

This paper cites RelGNN: Composite Message Passing for Relational Deep Learning.

TabPFN-3: Technical Report RelGNN: Composite Message Passing for Relational Deep Learning

Reference 60

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:25:46.537797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation dabcfdfe-7430-41b8-a227-e84b1d297ae2 · outbound

This paper cites Inductive Representation Learning on Large Graphs.

TabPFN-3: Technical Report Inductive Representation Learning on Large Graphs

Reference 61

Resolution: verified exact; local_arxiv, observed 2026-07-01T14:25:46.463296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation fdb86908-cbb3-4148-8b74-908fd3f8045f · outbound

This paper cites P., Jaladi, S., Shen, Y., L \'o pez, F., Kanatsoulis, C.

TabPFN-3: Technical Report P., Jaladi, S., Shen, Y., L \'o pez, F., Kanatsoulis, C

Reference 62

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T14:25:46.521623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 6c837d03-a9cb-4da1-a290-b4668dfca929 · outbound

This paper cites Kumorfm: A foundation model for in-context learning on relational data.Kumo.ai, 2025.

TabPFN-3: Technical Report Kumorfm: A foundation model for in-context learning on relational data.Kumo.ai, 2025

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.672008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 1b56163e-5cc4-4c5e-a783-29bb9a79e0d8 · outbound

This paper cites Griffin: Towards a Graph-Centric Relational Database Foundation Model.

TabPFN-3: Technical Report Griffin: Towards a Graph-Centric Relational Database Foundation Model

Reference 64

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:25:46.497905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a2c60e7a-dab1-4351-9210-021f795b61eb · outbound

This paper cites Relational trans- former: Toward zero-shot foundation models for relational data.arXiv preprint arXiv:2510.06377.

TabPFN-3: Technical Report Relational trans- former: Toward zero-shot foundation models for relational data.arXiv preprint arXiv:2510.06377

Reference 65

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:25:46.484883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 3834de53-cd37-4d1d-b1bf-450c87db18d0 · outbound

This paper cites Rdblearn: Simple in-context prediction over relational databases.

TabPFN-3: Technical Report Rdblearn: Simple in-context prediction over relational databases

Reference 66

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:25:46.461063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 58ef6e03-8fd0-4baf-9f5d-045dbcc85660 · outbound

This paper cites Lenssen, Yiwen Yuan, Zecheng Zhang, Xinwei He, and Jure Leskovec.

TabPFN-3: Technical Report Lenssen, Yiwen Yuan, Zecheng Zhang, Xinwei He, and Jure Leskovec

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.673884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 07315d72-d787-4b04-9450-86cf46ddd855 · outbound

This paper cites Künzel, Jasjeet S.

TabPFN-3: Technical Report Künzel, Jasjeet S

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.664040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 2ed5f85b-69b6-4a47-988c-cbeeeb365739 · outbound

This paper cites User guide for uplift modeling and casual inference.https: //www.uplift-modeling.com/en/latest/user_guide/index.html.

TabPFN-3: Technical Report User guide for uplift modeling and casual inference.https: //www.uplift-modeling.com/en/latest/user_guide/index.html

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.666289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation ce632cc4-c91c-4030-9442-f108c6c6a4a6 · outbound

This paper cites RealCause: Realistic Causal Inference Benchmarking.

TabPFN-3: Technical Report RealCause: Realistic Causal Inference Benchmarking

Reference 70

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:25:46.531865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 5c992c5f-3f73-4a67-8f3a-756fceee987f · outbound

This paper cites Xing, and Goreti Marreiros.

TabPFN-3: Technical Report Xing, and Goreti Marreiros

Reference 71

Resolution: verified exact; arxiv_id, observed 2026-06-30T21:45:05.193524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 42ed4662-c5c0-4dd3-a959-190effefda1b · outbound

This paper cites TIME: TabPFN-Integrated Multimodal Engine for Robust Tabular-Image Learning.

TabPFN-3: Technical Report TIME: TabPFN-Integrated Multimodal Engine for Robust Tabular-Image Learning

Reference 72

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:25:46.542172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation e80461f1-c67a-4064-8b3e-2bdbe2f14bf1 · outbound

This paper cites Predictive Maintenance for Rail Networks: Hitachi Rail Case Study.

TabPFN-3: Technical Report Predictive Maintenance for Rail Networks: Hitachi Rail Case Study

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.670169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f1b4d9b7-c2f5-4c7c-bc63-cc1576d12bb5 · outbound

This paper cites Credit Decisioning at Creditplus Bank: Case Study.

TabPFN-3: Technical Report Credit Decisioning at Creditplus Bank: Case Study

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.692323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 108c984b-8492-48ce-8ed8-f99a15e1af20 · outbound

This paper cites Clinical Decision Support with Oxford Cancer Analytics: Case Study.

TabPFN-3: Technical Report Clinical Decision Support with Oxford Cancer Analytics: Case Study

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.571101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 1925201e-910a-462f-be85-775df942ce9f · outbound

This paper cites Statistics and causal inference.Journal of the American Statistical Association, 81(396):945–960.

TabPFN-3: Technical Report Statistics and causal inference.Journal of the American Statistical Association, 81(396):945–960

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.590788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 5b4af53a-e2eb-4d59-80a0-f7ffeb42b6f7 · outbound

This paper cites The proposed uscf rating system, its development, theory, and applications.Chess life, 22(8):242–247.

TabPFN-3: Technical Report The proposed uscf rating system, its development, theory, and applications.Chess life, 22(8):242–247

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.598046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 0c922deb-b580-4c02-8c97-2a35920a829d · outbound

This paper cites Gonzalez, and Ion Stoica.

TabPFN-3: Technical Report Gonzalez, and Ion Stoica

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:33:56.640511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f3f6aed2-c9be-45bb-9745-a5e3593cb47d · outbound

This paper cites Terpilowski.

TabPFN-3: Technical Report Terpilowski

Reference 79

Resolution: verified exact; doi, observed 2026-06-30T21:45:05.200139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 9e7a103e-20f4-4952-8f8f-19045661a8fc · outbound

This paper cites Panmetai - a high performance tabular foundation model for accurate pancreatic cancer diagnosis via nmr metabolomics.Nature Communications, 17.

TabPFN-3: Technical Report Panmetai - a high performance tabular foundation model for accurate pancreatic cancer diagnosis via nmr metabolomics.Nature Communications, 17

Reference 80

Resolution: verified exact; doi, observed 2026-06-30T21:45:05.172797Z

Source-reported events for the cited work

correction dated 2026-04-17. Source: crossref record 10.1038/s41467-026-72208-y->10.1038/s41467-026-69426-9:correction, observed 2026-07-11T03:03:28.176043+00:00. This notice travels one citation hop only.

Observation 4a24b0f6-545d-4af7-b444-b5281b6cf1f5 · outbound

This paper cites Deep learning models enable healthy donor management through prediction of mobilization success.Transplantation and Cellular Therapy, 32:S3.

TabPFN-3: Technical Report Deep learning models enable healthy donor management through prediction of mobilization success.Transplantation and Cellular Therapy, 32:S3

Reference 81

Resolution: verified exact; doi, observed 2026-06-30T21:45:05.174742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 6df1b9a4-c431-4e68-9267-189534cd02c0 · outbound

This paper cites Differentiation between psychotic and non-psychotic major depression by the tabular prior-data fitted network.Journal of Affective Disorders, 403:121454.

TabPFN-3: Technical Report Differentiation between psychotic and non-psychotic major depression by the tabular prior-data fitted network.Journal of Affective Disorders, 403:121454

Reference 82

Resolution: verified exact; arxiv_id, observed 2026-06-30T21:45:05.180721Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 96b853f6-381f-495a-a9a1-583f3a6f6f7b · outbound

This paper cites Machine learning based optimization of fly ash content for improving geopolymer concrete compressive strength.Scientific Reports, 15.

TabPFN-3: Technical Report Machine learning based optimization of fly ash content for improving geopolymer concrete compressive strength.Scientific Reports, 15

Reference 83

Resolution: verified exact; doi, observed 2026-06-30T21:45:05.170840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 9bcfe1e6-dc4c-4fcc-b835-329c6d7ea1e9 · outbound

This paper cites Boosting pre-trained model with silica nanoparticles cellular toxicity prediction.Scientific Reports, 16.

TabPFN-3: Technical Report Boosting pre-trained model with silica nanoparticles cellular toxicity prediction.Scientific Reports, 16

Reference 84

Resolution: verified exact; doi, observed 2026-06-30T21:45:05.164712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 9117f1b9-27fc-4367-8610-731f0ffecf13 · outbound

This paper cites A metabolite-augmented fib-4 machine learning panel achieves superior liver fibrosis staging in chronic liver disease.Cell Reports Medicine, 7(4):102726.

TabPFN-3: Technical Report A metabolite-augmented fib-4 machine learning panel achieves superior liver fibrosis staging in chronic liver disease.Cell Reports Medicine, 7(4):102726

Reference 85

Resolution: verified exact; arxiv_id, observed 2026-06-30T21:45:05.177255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 368d3aa2-a64e-46ad-bb66-62f1bf2bbe0a · outbound

This paper cites Deep learning-aided prediction and mechanistic analysis of reaction kinetics in biochar- catalyzed antibiotic degradation.Biochar, 8.

TabPFN-3: Technical Report Deep learning-aided prediction and mechanistic analysis of reaction kinetics in biochar- catalyzed antibiotic degradation.Biochar, 8

Reference 86

Resolution: verified exact; doi, observed 2026-06-30T21:45:05.187790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 0c99c5e6-70a5-44bf-9547-6f654c12c436 · outbound

This paper cites Lroo rug pull detector: A leakage-resistant framework based on on-chain and osint signals.

TabPFN-3: Technical Report Lroo rug pull detector: A leakage-resistant framework based on on-chain and osint signals

Reference 87

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:25:46.502884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 3d4827ea-0352-4cfa-b285-7a7dd3bdac20 · outbound

This paper cites Meta-learning for return prediction in shifting market regimes.Journal of Financial Markets, page 101042.

TabPFN-3: Technical Report Meta-learning for return prediction in shifting market regimes.Journal of Financial Markets, page 101042

Reference 88

Resolution: verified exact; arxiv_id, observed 2026-06-30T21:45:05.212735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 0ee4be5b-1a8f-4bb7-82d5-acc1b44413a2 · outbound

This paper cites Early fault classification in rotating machinery with limited data using TabPFN.IEEE Sensors Journal, 23 (24):30960–30970.

TabPFN-3: Technical Report Early fault classification in rotating machinery with limited data using TabPFN.IEEE Sensors Journal, 23 (24):30960–30970

Reference 89

Resolution: verified exact; arxiv_id, observed 2026-06-30T21:45:05.151441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 3822239b-a364-4a1d-8890-471ad7a6d96a · outbound

This paper cites Tabular foundation models for in-context prediction of molecular properties.

TabPFN-3: Technical Report Tabular foundation models for in-context prediction of molecular properties

Reference 90

Resolution: verified exact; local_arxiv, observed 2026-07-01T14:25:46.518532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d93fa348-2739-4100-91d2-664079a83e20 · outbound

This paper cites Combining bulkformer and tabpfn to predict post- transplant function from kidney biopsies during machine perfusion or cold storage.

TabPFN-3: Technical Report Combining bulkformer and tabpfn to predict post- transplant function from kidney biopsies during machine perfusion or cold storage

Reference 91

Resolution: verified exact; doi, observed 2026-06-30T21:45:05.156501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation efea231d-774a-4640-9867-d46b9895df12 · outbound

This paper cites Survival In-Context: Amortized Bayesian Survival Analysis via Prior-Fitted Networks.

TabPFN-3: Technical Report Survival In-Context: Amortized Bayesian Survival Analysis via Prior-Fitted Networks

Reference 92

Resolution: verified exact; local_arxiv, observed 2026-07-01T14:25:46.579411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 68b75aa8-872f-4ea6-9eb4-d5b8341a506f · outbound

This paper cites Advancing cardiovascular disease diagnosis with an inter- pretable and responsible ai framework.Scientific Reports.

TabPFN-3: Technical Report Advancing cardiovascular disease diagnosis with an inter- pretable and responsible ai framework.Scientific Reports

Reference 93

Resolution: verified exact; doi, observed 2026-06-30T21:45:05.004455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 929ccf1a-d6ba-4059-9052-7b49c3c31ad7 · outbound

This paper cites an unresolved cited work.

TabPFN-3: Technical Report Unresolved cited work

Reference 94

Resolution: verified exact; doi, observed 2026-06-30T21:45:05.137054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 534b736c-40e9-412a-ba1d-08412b75536d · outbound

This paper cites Villines, R.

TabPFN-3: Technical Report Villines, R

Reference 95

Resolution: verified exact; doi, observed 2026-06-30T21:45:04.924492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation c4e482ca-c6e1-4fcb-ae35-b02d1384e155 · outbound

This paper cites Woodward, Hyun Jun Jung, Frank Hutter, Lukas Westermann, Anna Köttgen, Pascal Schlosser, Michael Köttgen, and Stefan Haug.

TabPFN-3: Technical Report Woodward, Hyun Jun Jung, Frank Hutter, Lukas Westermann, Anna Köttgen, Pascal Schlosser, Michael Köttgen, and Stefan Haug

Reference 96

Resolution: verified exact; doi, observed 2026-06-30T21:45:04.957424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 310c4e7b-cced-4a4a-ba8d-40d67486188a · outbound

This paper cites Silvio Gutkind, Cesare Orlandi, Asuka Inoue, and Raimondi Francesco.

TabPFN-3: Technical Report Silvio Gutkind, Cesare Orlandi, Asuka Inoue, and Raimondi Francesco

Reference 97

Resolution: verified exact; doi, observed 2026-06-30T21:45:05.135192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 3d072205-a19b-4c05-b665-76c1a55b181e · outbound

This paper cites Schwarz, L.

TabPFN-3: Technical Report Schwarz, L

Reference 98

Resolution: verified exact; doi, observed 2026-06-30T21:45:05.139078Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 72aa999e-4f97-4188-9967-2a179f46dd9c · outbound

This paper cites Application of treatment response assessment maps (trams), based on delayed- contrast mri for radiomic characterization of breast lesions.Scientific Reports, 16.

TabPFN-3: Technical Report Application of treatment response assessment maps (trams), based on delayed- contrast mri for radiomic characterization of breast lesions.Scientific Reports, 16

Reference 99

Resolution: verified exact; doi, observed 2026-06-30T21:45:05.144105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 7e285e39-32f2-4474-aa67-8f657633d09a · outbound

This paper cites GitHub - Smallriver2024/STBNet: TabPFN-Based Interpretable Deep Learning Model for Discriminating Spinal Tuberculosis from Pyogenic Spinal Infection — github.com.

TabPFN-3: Technical Report GitHub - Smallriver2024/STBNet: TabPFN-Based Interpretable Deep Learning Model for Discriminating Spinal Tuberculosis from Pyogenic Spinal Infection — github.com

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:43:57.727358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Pith citing papers

Observation a844e10e-e820-4f3a-b1b9-8e3c15d5ffda · inbound

RelPrism: A Multi-Faceted Pre-training Framework with Self-Generated Tasks for Relational Databases cites this paper.

RelPrism: A Multi-Faceted Pre-training Framework with Self-Generated Tasks for Relational Databases TabPFN-3: Technical Report

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:05:22.307436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 2c1b32ac-eeed-4a1b-9c6b-17a6b251e60c · inbound

Transformers Can Learn Posterior Predictive Distributions In-Context cites this paper.

Transformers Can Learn Posterior Predictive Distributions In-Context TabPFN-3: Technical Report

Reference 4

Resolution: metadata mismatch; local_arxiv, observed 2026-06-29T16:13:36.165009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 679e4411-c553-4f5a-9ea2-a46f790ba0b8 · inbound

Trio: Learning Time-Series Forecasting with Temporal-Spatial-Sample Attention and Structural Causal Priors cites this paper.

Trio: Learning Time-Series Forecasting with Temporal-Spatial-Sample Attention and Structural Causal Priors TabPFN-3: Technical Report

Reference 17

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T16:27:09.686529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f44fc06e-6c97-4554-80fa-9747272d1b49 · inbound

In-Context Learning for Latent Space Bayesian Optimization cites this paper.

In-Context Learning for Latent Space Bayesian Optimization TabPFN-3: Technical Report

Reference 8

Resolution: metadata mismatch; local_arxiv, observed 2026-07-03T00:37:30.229561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 055d6813-3474-4c6e-9fe0-28f164032829 · inbound

Parameter-Efficient Adapter Tuning for Tabular-Image Multimodal Learning cites this paper.

Parameter-Efficient Adapter Tuning for Tabular-Image Multimodal Learning TabPFN-3: Technical Report

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-07-03T08:47:50.191962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 48d6468a-cf46-4856-8b21-743c13e7fe1c · inbound

RocketPFN: Accurate Time Series Classification via In-Context Learning cites this paper.

RocketPFN: Accurate Time Series Classification via In-Context Learning TabPFN-3: Technical Report

Reference 43

Resolution: metadata mismatch; local_arxiv, observed 2026-07-04T06:39:38.053696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 0cd7a3f4-23f7-4ec1-9275-f2d1f426616c · inbound

A Fair Evaluation of Graph Foundation Models for Node Property Prediction cites this paper.

A Fair Evaluation of Graph Foundation Models for Node Property Prediction TabPFN-3: Technical Report

Reference 9

Resolution: metadata mismatch; local_arxiv, observed 2026-07-04T16:09:57.536518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 9af9bcf9-30da-4f0e-86f7-65951d8f16b1 · inbound

When Does Small Data Work? Accuracy and Efficiency Trade-offs Between Tabular Foundation Models and Conventional Methods for Crowd-State Classification at Hajj and Umrah cites this paper.

When Does Small Data Work? Accuracy and Efficiency Trade-offs Between Tabular Foundation Models and Conventional Methods for Crowd-State Classification at Hajj and Umrah TabPFN-3: Technical Report

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-11T22:19:31.752438Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a711723-751e-4707-910b-6418560c2c2c · inbound

TabPack: Efficient Hyperparameter Ensembles for Tabular Deep Learning cites this paper.

TabPack: Efficient Hyperparameter Ensembles for Tabular Deep Learning TabPFN-3: Technical Report

Reference 141

Resolution: metadata mismatch; local_arxiv, observed 2026-07-07T14:03:48.751773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 42eb8833-a6ff-4b35-8e9e-e97bd0771d3c · inbound

Parameter-Free Encoders Remain Viable for RDB Foundation Models cites this paper.

Parameter-Free Encoders Remain Viable for RDB Foundation Models TabPFN-3: Technical Report

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-11T11:47:14.742492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c17badf-1d46-455c-a8e3-1d991f855c35 · inbound

Parameter-Free Encoders Remain Viable for RDB Foundation Models cites this paper.

Parameter-Free Encoders Remain Viable for RDB Foundation Models TabPFN-3: Technical Report

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T08:36:02.730967Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e4a3b03-4ca4-4fdd-87b8-cbbb0a935e99 · inbound

TabLoRA: Parameter-Efficient Low-Rank Ensemble Learning for Large-Scale Tabular Data cites this paper.

TabLoRA: Parameter-Efficient Low-Rank Ensemble Learning for Large-Scale Tabular Data TabPFN-3: Technical Report

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-14T00:36:05.289408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 202f31c1-90fb-4746-bff2-902c0bb93a1a · inbound

TabPFN beyond Tabular Data: Calibration and Accuracy on Multimodal Embeddings cites this paper.

TabPFN beyond Tabular Data: Calibration and Accuracy on Multimodal Embeddings TabPFN-3: Technical Report

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-14T07:42:06.462698Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c9b6bdc1-bd10-461b-a521-70993b9b60b3 · inbound

TabPFN beyond Tabular Data: Calibration and Accuracy on Multimodal Embeddings cites this paper.

TabPFN beyond Tabular Data: Calibration and Accuracy on Multimodal Embeddings TabPFN-3: Technical Report

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T07:07:55.504755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation beeac314-7a62-4ec9-8100-35c8f8b22006 · inbound

Topological Signatures of Context-Level Reliability in TabPFN cites this paper.

Topological Signatures of Context-Level Reliability in TabPFN TabPFN-3: Technical Report

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-01T16:37:00.278630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74465366-355d-46d1-8030-b67891c139bb · inbound

In-Context Time Series Classification with Random Convolutional Features cites this paper.

In-Context Time Series Classification with Random Convolutional Features TabPFN-3: Technical Report

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T13:06:48.744755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a883bf9-9879-4385-a1e6-e732b86c312e · inbound

Empirical Evaluation of Out-Of-Distribution Performance of Tabular Foundation Models cites this paper.

Empirical Evaluation of Out-Of-Distribution Performance of Tabular Foundation Models TabPFN-3: Technical Report

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-01T00:54:47.301827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e4fb5666-be2e-4644-8c6f-da05877a9768 · inbound

DoTime: A Synthetic Benchmark Generator for Interventional and Counterfactual Time Series cites this paper.

DoTime: A Synthetic Benchmark Generator for Interventional and Counterfactual Time Series TabPFN-3: Technical Report

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T13:16:11.749233Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f391f58f-281f-4c53-a5df-b90703ee392e · inbound

From field-scale to large-scale spectral libraries: Tabular foundation models in soil spectroscopy cites this paper.

From field-scale to large-scale spectral libraries: Tabular foundation models in soil spectroscopy TabPFN-3: Technical Report

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-05T00:36:01.676639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.