Paper Citation Record · LEDGER

Basis Transformers for Multi-Task Tabular Regression

As of 8 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 0 inbound Pith citation observations for arXiv:2506.06926.

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

pith.paper-citation-record.v1
2506.06926 v1

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:50:18.897807Z

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

48 of 48 outbound references displayed

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verified fuzzy21
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7f75b3d3-7802-4555-ae60-590359047d20 · outbound

This paper cites Tabnet: Attentive interpretable tabular learning.

Basis Transformers for Multi-Task Tabular Regression Tabnet: Attentive interpretable tabular learning

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:50:19.237918Z

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Observation d6759820-e339-4320-bd3b-df640947fc44 · outbound

This paper cites Task clustering and gating for bayesian multitask learning.

Basis Transformers for Multi-Task Tabular Regression Task clustering and gating for bayesian multitask learning

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:50:19.229491Z

Source-reported events for the cited work

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Observation 4d3320d8-fafc-485c-8af5-5154ef2c1ce6 · outbound

This paper cites Applying natural language processing and hierarchical machine learning approaches to text difficulty classification.

Basis Transformers for Multi-Task Tabular Regression Applying natural language processing and hierarchical machine learning approaches to text difficulty classification

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:50:19.220520Z

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Observation 4ac66474-4e89-493d-982c-0089eb14b2d8 · outbound

This paper cites Pythia: A suite for analyzing large language models across training and scaling.

Basis Transformers for Multi-Task Tabular Regression Pythia: A suite for analyzing large language models across training and scaling

Reference 4

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Observation c831ace1-c5f2-479f-a7c4-4c91ff61e3a2 · outbound

This paper cites Bayesian Hierarchical Mixtures of Experts.

Basis Transformers for Multi-Task Tabular Regression Bayesian Hierarchical Mixtures of Experts

Reference 5

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Observation 2b3bee5d-3955-4a61-bbcf-176ebbdb3312 · outbound

This paper cites Revisiting multimodal transformers for tabular data with text fields.

Basis Transformers for Multi-Task Tabular Regression Revisiting multimodal transformers for tabular data with text fields

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:50:19.208481Z

Source-reported events for the cited work

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Observation cbe81b6b-866f-4611-bf8e-d9bcb675f5a6 · outbound

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

Basis Transformers for Multi-Task Tabular Regression Deep neural networks and tabular data: A survey

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T05:50:18.777936Z

Source-reported events for the cited work

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Observation 8b19ce41-df85-4f44-8068-6c1c1277ec47 · outbound

This paper cites A comprehensive review on data preprocessing techniques in data analysis.

Basis Transformers for Multi-Task Tabular Regression A comprehensive review on data preprocessing techniques in data analysis

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:50:19.196857Z

Source-reported events for the cited work

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Observation 34bc99ba-4dd5-4ab7-9c8a-af99740f837d · outbound

This paper cites Xgboost: A scalable tree boosting system.

Basis Transformers for Multi-Task Tabular Regression Xgboost: A scalable tree boosting system

Reference 9

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Source-reported events for the cited work

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Observation 6b98f1c0-54a4-433f-a264-ff056db75e85 · outbound

This paper cites Scaling instruction-finetuned language models.

Basis Transformers for Multi-Task Tabular Regression Scaling instruction-finetuned language models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T05:50:18.785542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 60fbd060-ce22-40ea-b4ae-371f76c15814 · outbound

This paper cites Bayesian Multitask Learning with Latent Hierarchies.

Basis Transformers for Multi-Task Tabular Regression Bayesian Multitask Learning with Latent Hierarchies

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-08-07T05:50:19.024531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 26b26f4c-b9cb-41e1-8c1c-9b03d0ba945b · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Basis Transformers for Multi-Task Tabular Regression BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 12

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Observation 7b19a67a-b969-4e9b-bd05-f3e374efaaa7 · outbound

This paper cites Cerebras-GPT: Open Compute-Optimal Language Models Trained on the Cerebras Wafer-Scale Cluster.

Basis Transformers for Multi-Task Tabular Regression Cerebras-GPT: Open Compute-Optimal Language Models Trained on the Cerebras Wafer-Scale Cluster

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T05:50:18.794719Z

Source-reported events for the cited work

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Observation 51b3ca11-b280-4285-be86-b4c122573aaf · outbound

This paper cites How Numerical Precision Affects Arithmetical Reasoning Capabilities of LLMs.

Basis Transformers for Multi-Task Tabular Regression How Numerical Precision Affects Arithmetical Reasoning Capabilities of LLMs

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T05:50:18.797479Z

Source-reported events for the cited work

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Observation 457bb6fd-331c-410b-8f98-d8f84794f077 · outbound

This paper cites Openml-ctr23–a curated tabular regression benchmarking suite.

Basis Transformers for Multi-Task Tabular Regression Openml-ctr23–a curated tabular regression benchmarking suite

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:50:19.180150Z

Source-reported events for the cited work

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Observation c914291c-6b5d-4338-bf8a-b556f118e4c3 · outbound

This paper cites TabKANet: Tabular Data Modeling with Kolmogorov-Arnold Network and Transformer.

Basis Transformers for Multi-Task Tabular Regression TabKANet: Tabular Data Modeling with Kolmogorov-Arnold Network and Transformer

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-08-07T05:50:18.994892Z

Source-reported events for the cited work

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Observation b954d388-e421-4442-94ac-36bd8407dbe4 · outbound

This paper cites Large Scale Transfer Learning for Tabular Data via Language Modeling.

Basis Transformers for Multi-Task Tabular Regression Large Scale Transfer Learning for Tabular Data via Language Modeling

Reference 17

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Observation 3b79f7a0-78fe-4933-bb39-d8da236612b9 · outbound

This paper cites What every computer scientist should know about floating-point arithmetic.

Basis Transformers for Multi-Task Tabular Regression What every computer scientist should know about floating-point arithmetic

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:50:19.171697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a119ae0f-82e4-4761-91d0-6e20a9bbb62b · outbound

This paper cites Revisiting deep learning models for tabular data.

Basis Transformers for Multi-Task Tabular Regression Revisiting deep learning models for tabular data

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:50:19.164558Z

Source-reported events for the cited work

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Observation d28e05d7-973c-4eab-ac54-aa77c6784b5d · outbound

This paper cites The Llama 3 Herd of Models.

Basis Transformers for Multi-Task Tabular Regression The Llama 3 Herd of Models

Reference 20

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Source-reported events for the cited work

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Observation 80dbb32e-52dc-4db6-859e-267cc46457c7 · outbound

This paper cites On typical range, sensitivity, and normalization of mean squared error and nash-sutcliffe efficiency type metrics.

Basis Transformers for Multi-Task Tabular Regression On typical range, sensitivity, and normalization of mean squared error and nash-sutcliffe efficiency type metrics

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:50:19.155556Z

Source-reported events for the cited work

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Observation 8f592924-04d8-4e60-99dc-824fecd963c2 · outbound

This paper cites The coefficient of determination exposed.

Basis Transformers for Multi-Task Tabular Regression The coefficient of determination exposed

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:50:19.147224Z

Source-reported events for the cited work

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Observation d5882811-d113-4e70-9e2d-124fd905648f · outbound

This paper cites Tabllm: Few-shot classification of tabular data with large language models.

Basis Transformers for Multi-Task Tabular Regression Tabllm: Few-shot classification of tabular data with large language models

Reference 23

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Observation 116aa3f1-113a-465d-b29b-14ba0c128bd7 · outbound

This paper cites Tabpfn: A transformer that solves small tabular classification problems in a second.

Basis Transformers for Multi-Task Tabular Regression Tabpfn: A transformer that solves small tabular classification problems in a second

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:50:19.135204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 79853408-5823-43b0-ae2b-497335cced11 · outbound

This paper cites TabTransformer: Tabular Data Modeling Using Contextual Embeddings.

Basis Transformers for Multi-Task Tabular Regression TabTransformer: Tabular Data Modeling Using Contextual Embeddings

Reference 25

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Observation fbd35fbf-840d-45eb-94d5-4ac0608194dd · outbound

This paper cites Carte: pretraining and transfer for tabular learning.

Basis Transformers for Multi-Task Tabular Regression Carte: pretraining and transfer for tabular learning

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:50:19.127828Z

Source-reported events for the cited work

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Observation a15b52ed-d8e0-4e35-980a-32c8a74221fc · outbound

This paper cites The Stack: 3 TB of permissively licensed source code.

Basis Transformers for Multi-Task Tabular Regression The Stack: 3 TB of permissively licensed source code

Reference 27

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Source-reported events for the cited work

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Observation e44819ae-5970-4724-a42c-ac7684d227ae · outbound

This paper cites A comprehen- sive analysis of deep regression.IEEE transactions on pattern analysis and machine intelligence, 42(9):2065–2081, 2019.

Basis Transformers for Multi-Task Tabular Regression A comprehen- sive analysis of deep regression.IEEE transactions on pattern analysis and machine intelligence, 42(9):2065–2081, 2019

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:50:19.118688Z

Source-reported events for the cited work

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Observation 585d7bca-070c-4433-8e90-ad11d238eefd · outbound

This paper cites Set transformer: A framework for attention-based permutation-invariant neural networks.

Basis Transformers for Multi-Task Tabular Regression Set transformer: A framework for attention-based permutation-invariant neural networks

Reference 29

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Observation f5aca38f-2696-4e16-86c6-174b7e01bf88 · outbound

This paper cites Bart: Denoising sequence-to-sequence pre- training for natural language generation, translation, and comprehension.

Basis Transformers for Multi-Task Tabular Regression Bart: Denoising sequence-to-sequence pre- training for natural language generation, translation, and comprehension

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:50:19.107028Z

Source-reported events for the cited work

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Observation 97a6a168-f96a-41a4-9757-8fa28cd57283 · outbound

This paper cites One Transformer for All Time Series: Representing and Training with Time-Dependent Heterogeneous Tabular Data.

Basis Transformers for Multi-Task Tabular Regression One Transformer for All Time Series: Representing and Training with Time-Dependent Heterogeneous Tabular Data

Reference 31

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Observation 90a11b4b-602f-473e-be14-af5c4e78084c · outbound

This paper cites A bounded version of the nash-sutcliffe criterion for better model assessment on large sets of basins.

Basis Transformers for Multi-Task Tabular Regression A bounded version of the nash-sutcliffe criterion for better model assessment on large sets of basins

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:50:19.097990Z

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Observation 9565d871-2027-4c08-9556-55ed35b50f52 · outbound

This paper cites A survey of sensor fusion methods in wearable robotics.

Basis Transformers for Multi-Task Tabular Regression A survey of sensor fusion methods in wearable robotics

Reference 33

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Observation b519f37f-6cb1-4bd2-a891-d20416c36a95 · outbound

This paper cites Tabular transformers for modeling multivariate time series.

Basis Transformers for Multi-Task Tabular Regression Tabular transformers for modeling multivariate time series

Reference 34

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Observation e266b9b7-a82d-45ec-8a1c-80eefc7e6f4c · outbound

This paper cites Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data.

Basis Transformers for Multi-Task Tabular Regression Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data

Reference 35

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Observation 76a0ecf0-0053-4d43-9e36-6452af9bc13f · outbound

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Basis Transformers for Multi-Task Tabular Regression The statistical measurement of agreement

Reference 36

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Observation ae30319f-e2aa-4f29-bd0d-e4bff9964b0e · outbound

This paper cites Saint: Improved neural networks for tabular data via row attention and contrastive pre-training.

Basis Transformers for Multi-Task Tabular Regression Saint: Improved neural networks for tabular data via row attention and contrastive pre-training

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:50:19.070931Z

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Observation 63dece68-caf3-43cb-8b7e-d6ccff5f6fb1 · outbound

This paper cites Multi-task bayesian optimization.

Basis Transformers for Multi-Task Tabular Regression Multi-task bayesian optimization

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:50:19.062841Z

Source-reported events for the cited work

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Observation 45c3ebdf-44e2-4bb3-8b52-ab475807b07d · outbound

This paper cites Well-Read Students Learn Better: On the Importance of Pre-training Compact Models.

Basis Transformers for Multi-Task Tabular Regression Well-Read Students Learn Better: On the Importance of Pre-training Compact Models

Reference 39

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Observation 291a9551-a4cc-4ddd-9e91-5fdb68027ec1 · outbound

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

Basis Transformers for Multi-Task Tabular Regression Why Tabular Foundation Models Should Be a Research Priority

Reference 40

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Observation a372c969-0b0c-44de-982f-8c69129f7098 · outbound

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Basis Transformers for Multi-Task Tabular Regression Attention is all you need

Reference 41

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Source-reported events for the cited work

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Observation e03b4885-eb5b-4950-b22b-5d05354b0024 · outbound

This paper cites UniPredict: Large Language Models are Universal Tabular Classifiers.

Basis Transformers for Multi-Task Tabular Regression UniPredict: Large Language Models are Universal Tabular Classifiers

Reference 42

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Source-reported events for the cited work

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Observation 7e038fde-84bc-423e-a7e7-10199cc0dd7f · outbound

This paper cites Multi-task reinforcement learning: a hierarchical bayesian approach.

Basis Transformers for Multi-Task Tabular Regression Multi-task reinforcement learning: a hierarchical bayesian approach

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:50:19.051804Z

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This paper cites HuggingFace's Transformers: State-of-the-art Natural Language Processing.

Basis Transformers for Multi-Task Tabular Regression HuggingFace's Transformers: State-of-the-art Natural Language Processing

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-07T05:50:18.886505Z

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Observation e9d2cba1-a216-46d9-a2fd-a686e0d738a0 · outbound

This paper cites LaMini-LM: A Diverse Herd of Distilled Models from Large-Scale Instructions.

Basis Transformers for Multi-Task Tabular Regression LaMini-LM: A Diverse Herd of Distilled Models from Large-Scale Instructions

Reference 45

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Observation 32907dcb-d867-4348-a5cd-0853b88c5486 · outbound

This paper cites On layer normalization in the transformer architecture.

Basis Transformers for Multi-Task Tabular Regression On layer normalization in the transformer architecture

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:50:19.043510Z

Source-reported events for the cited work

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Observation cef2ec7e-cbdf-46a1-b90d-11c842925633 · outbound

This paper cites Qwen2.5 Technical Report.

Basis Transformers for Multi-Task Tabular Regression Qwen2.5 Technical Report

Reference 47

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Observation 5cbe5483-540a-4405-bae5-0c9a6eeeb744 · outbound

This paper cites TinyLlama: An Open-Source Small Language Model.

Basis Transformers for Multi-Task Tabular Regression TinyLlama: An Open-Source Small Language Model

Reference 48

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Pith citing papers

No inbound Pith citation observations are available.