Paper Citation Record · LEDGER

Two-Stage Feature Generation with Transformer and Reinforcement Learning

As of 8 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2505.21978.

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

pith.paper-citation-record.v1
2505.21978 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:23:15.676895Z

measured 33 of 33 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

33 of 33 outbound references displayed

verified exact0
verified fuzzy25
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a507094f-3acc-4e83-8b19-0381b977b039 · outbound

This paper cites Neural Machine Translation by Jointly Learning to Align and Translate.

Two-Stage Feature Generation with Transformer and Reinforcement Learning Neural Machine Translation by Jointly Learning to Align and Translate

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a028456d-5c5d-417e-bf61-74c157999bee · outbound

This paper cites On calibration of modern neural net- works.

Two-Stage Feature Generation with Transformer and Reinforcement Learning On calibration of modern neural net- works

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:23:20.576893Z

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Observation 6fd04372-7b22-4ab7-af26-80704fe9cf17 · outbound

This paper cites Kingma and Jimmy Ba.

Two-Stage Feature Generation with Transformer and Reinforcement Learning Kingma and Jimmy Ba

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:23:19.416861Z

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Observation 1aba5f18-5d00-44cc-91fd-b9df28e0940a · outbound

This paper cites Hyperopt-sklearn: Automatic hyperpa- rameter configuration for scikit-learn.

Two-Stage Feature Generation with Transformer and Reinforcement Learning Hyperopt-sklearn: Automatic hyperpa- rameter configuration for scikit-learn

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:23:19.216370Z

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Observation 4e47c6d6-f902-4d60-9269-b92778840684 · outbound

This paper cites Deep learning.

Two-Stage Feature Generation with Transformer and Reinforcement Learning Deep learning

Reference 17

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Observation d3ef9588-02e0-4c06-b867-b4361cde3291 · outbound

This paper cites Multi-label feature selection with high-sparse personalized and low-redundancy shared common features.Information Processing & Management, 61(3):103633,.

Two-Stage Feature Generation with Transformer and Reinforcement Learning Multi-label feature selection with high-sparse personalized and low-redundancy shared common features.Information Processing & Management, 61(3):103633,

Reference 18

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Source-reported events for the cited work

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Observation 53ec5406-d94a-442c-ae3b-99adc22cee74 · outbound

This paper cites Libsvm dataset download.

Two-Stage Feature Generation with Transformer and Reinforcement Learning Libsvm dataset download

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:23:18.667137Z

Source-reported events for the cited work

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Observation b547e634-b3d2-4c73-96cb-b8902f2f04e5 · outbound

This paper cites [Liu et al., 2019] Kunpeng Liu, Yanjie Fu, Pengfei Wang, Le Wu, Rui Bo, and Xiaolin Li.

Two-Stage Feature Generation with Transformer and Reinforcement Learning [Liu et al., 2019] Kunpeng Liu, Yanjie Fu, Pengfei Wang, Le Wu, Rui Bo, and Xiaolin Li

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:23:18.397541Z

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Observation 51996c40-d559-442f-9d84-b2ed6fce9e0b · outbound

This paper cites Body mass index (bmi).

Two-Stage Feature Generation with Transformer and Reinforcement Learning Body mass index (bmi)

Reference 22

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Source-reported events for the cited work

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Observation eccc61fc-94a7-476d-b2a4-3fd4abf3f4bc · outbound

This paper cites [Public, 2024b] Public.

Two-Stage Feature Generation with Transformer and Reinforcement Learning [Public, 2024b] Public

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:23:17.614663Z

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 47c97e7e-e0ef-42f3-9599-3f9b6ee4e910 · outbound

This paper cites [Raffel et al., 2020] Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu.

Two-Stage Feature Generation with Transformer and Reinforcement Learning [Raffel et al., 2020] Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:23:17.317297Z

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 66f11acc-838a-4932-8154-cb807fcd47e3 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Two-Stage Feature Generation with Transformer and Reinforcement Learning Proximal Policy Optimization Algorithms

Reference 25

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Source-reported events for the cited work

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Observation db834ff7-5534-4ce7-b1e7-d0b5045f91d3 · outbound

This paper cites Sequence to Sequence Learning with Neural Networks.

Two-Stage Feature Generation with Transformer and Reinforcement Learning Sequence to Sequence Learning with Neural Networks

Reference 26

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Observation 36c2a957-0dc9-47c1-b339-61924a1c9e33 · outbound

This paper cites Gomez, Lukasz Kaiser, and Illia Polosukhin.

Two-Stage Feature Generation with Transformer and Reinforcement Learning Gomez, Lukasz Kaiser, and Illia Polosukhin

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:23:17.147929Z

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Observation 0308cf53-6940-4fbf-a2bb-4a673c5db1d1 · outbound

This paper cites Generative partial multi-view clustering with adaptive fusion and cy- cle consistency.

Two-Stage Feature Generation with Transformer and Reinforcement Learning Generative partial multi-view clustering with adaptive fusion and cy- cle consistency

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:23:16.883034Z

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Observation 02977f1a-5b4b-4c64-85c8-167afc0ec5c8 · outbound

This paper cites Group-wise reinforcement feature generation for optimal and explainable representa- tion space reconstruction.

Two-Stage Feature Generation with Transformer and Reinforcement Learning Group-wise reinforcement feature generation for optimal and explainable representa- tion space reconstruction

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:23:16.626398Z

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 8f16ce90-aef3-4116-a220-c3140a61b423 · outbound

This paper cites A conditional-weight joint relevance metric for feature relevancy term.

Two-Stage Feature Generation with Transformer and Reinforcement Learning A conditional-weight joint relevance metric for feature relevancy term

Reference 31

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Source-reported events for the cited work

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Observation 509ab230-6069-4fe9-9727-69224f2f4716 · outbound

This paper cites Openfe: automated feature generation with expert-level performance.

Two-Stage Feature Generation with Transformer and Reinforcement Learning Openfe: automated feature generation with expert-level performance

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:23:16.386136Z

Source-reported events for the cited work

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Observation 75c41d74-4bfd-43b1-9be8-9b595ad90a1b · outbound

This paper cites Feature engineering for machine learning: principles and techniques for data scientists.

Two-Stage Feature Generation with Transformer and Reinforcement Learning Feature engineering for machine learning: principles and techniques for data scientists

Reference 33

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Observation 52fd222d-22b6-46b9-b91b-b33212ef395a · outbound

This paper cites Difer: differentiable automated feature engineering.

Two-Stage Feature Generation with Transformer and Reinforcement Learning Difer: differentiable automated feature engineering

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:23:15.954267Z

Source-reported events for the cited work

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Observation 05461ff4-a1b5-4c33-aa03-fbcb3519d531 · outbound

This paper cites Feature engineering for machine learning and data analytics.

Two-Stage Feature Generation with Transformer and Reinforcement Learning Feature engineering for machine learning and data analytics

Reference 2012

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:23:20.866848Z

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Observation e4863182-3899-4036-b4c0-2b40ba2d40aa · outbound

This paper cites Generating Sequences With Recurrent Neural Networks.

Two-Stage Feature Generation with Transformer and Reinforcement Learning Generating Sequences With Recurrent Neural Networks

Reference 2013

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Observation 336889fb-caf9-4dda-a33e-cc7d9cceb89a · outbound

This paper cites A survey on deep reinforcement learning for data processing and ana- lytics.

Two-Stage Feature Generation with Transformer and Reinforcement Learning A survey on deep reinforcement learning for data processing and ana- lytics

Reference 2014

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:23:21.193510Z

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 05803332-b790-425f-8719-95893225b275 · outbound

This paper cites Explorekit: Automatic feature generation and selection.

Two-Stage Feature Generation with Transformer and Reinforcement Learning Explorekit: Automatic feature generation and selection

Reference 2015

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Observation 5e4afad8-2f8e-4f97-824f-1b75125a4a21 · outbound

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Two-Stage Feature Generation with Transformer and Reinforcement Learning Unresolved cited work

Reference 2016

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

Observation 3dcdd0c5-3ac9-47fa-9269-a7bf1ed79a3e · outbound

This paper cites Automl: A survey of the state-of-the-art.

Two-Stage Feature Generation with Transformer and Reinforcement Learning Automl: A survey of the state-of-the-art

Reference 2017

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:23:20.422811Z

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Observation f607a81c-e1fc-4fef-89df-8b1d9c087394 · outbound

This paper cites Strength- ening learning algorithms by feature discovery.

Two-Stage Feature Generation with Transformer and Reinforcement Learning Strength- ening learning algorithms by feature discovery

Reference 2018

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:23:20.727351Z

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

Observation dcb2c63f-d87e-4568-8a3b-7f28f7670b6e · outbound

This paper cites Autocross: Automatic feature cross- ing for tabular data in real-world applications.

Two-Stage Feature Generation with Transformer and Reinforcement Learning Autocross: Automatic feature cross- ing for tabular data in real-world applications

Reference 2019

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:23:18.145780Z

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Observation 88e89c46-a091-4c7d-83b2-5c61562bb760 · outbound

This paper cites Kaggle dataset download.

Two-Stage Feature Generation with Transformer and Reinforcement Learning Kaggle dataset download

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:23:20.166619Z

Source-reported events for the cited work

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Observation c3858485-b73e-417d-bcaa-782fe468f67d · outbound

This paper cites The autofeat python library for automated feature engineering and selection.

Two-Stage Feature Generation with Transformer and Reinforcement Learning The autofeat python library for automated feature engineering and selection

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:23:20.294546Z

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Observation fd8bd7e4-7501-484b-8346-4397cc83deee · outbound

This paper cites Feature relevance term variation for multi-label feature selection.

Two-Stage Feature Generation with Transformer and Reinforcement Learning Feature relevance term variation for multi-label feature selection

Reference 2022

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Observation f3816996-5b16-49d9-9b35-2a4e7643d13d · outbound

This paper cites A few useful things to know about machine learning.

Two-Stage Feature Generation with Transformer and Reinforcement Learning A few useful things to know about machine learning

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:23:21.047130Z

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 7e8e5386-4b4d-4621-8bcf-e47982bebb6c · outbound

This paper cites [Kanter and Veeramachaneni, 2015] James Max Kanter and Kalyan Veeramachaneni.

Two-Stage Feature Generation with Transformer and Reinforcement Learning [Kanter and Veeramachaneni, 2015] James Max Kanter and Kalyan Veeramachaneni

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:23:20.062489Z

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.

Pith citing papers

No inbound Pith citation observations are available.