Pith. sign in

Paper Citation Record · LEDGER

SoftPipe: A Soft-Guided Reinforcement Learning Framework for Automated Data Preparation

As of 8 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2507.13710.

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

pith.paper-citation-record.v1
2507.13710 v2

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:25:31.425452Z

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 exact1
  • verified fuzzy9
  • unresolved20
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9ccdc93b-d4b5-421a-be09-2cd05d704729 · outbound

This paper cites Data preparation for machine learning.

SoftPipe: A Soft-Guided Reinforcement Learning Framework for Automated Data Preparation Data preparation for machine learning

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T16:25:31.190442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:25:31.190442Z digest=sha256:6f8b0b506e0851143b1613ebd8340f346d3256f33235c2f6bc0c22ede76857d9

Observation 09ee7bdd-1eef-45bd-9a5f-0ecbed99da74 · outbound

This paper cites What are the challenges of implementing automl? https://milvus.io/ai-quick-reference/ what-are-the-challenges-of-implementing-automl// , 2025.

SoftPipe: A Soft-Guided Reinforcement Learning Framework for Automated Data Preparation What are the challenges of implementing automl? https://milvus.io/ai-quick-reference/ what-are-the-challenges-of-implementing-automl// , 2025

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:25:31.919069Z

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.

source=pdf_text observed=2026-08-06T16:25:31.323225Z digest=sha256:0b10e5bccf107c19b66a9e4b4f4465401ae048e2cd6ee5ca661e71edb5e43523

Observation d9f1f86b-e888-4524-b405-348eb29b4087 · outbound

This paper cites Agile data preparation & exploration for cloud machine learning.

SoftPipe: A Soft-Guided Reinforcement Learning Framework for Automated Data Preparation Agile data preparation & exploration for cloud machine learning

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-06T16:25:31.326651Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:25:31.326651Z digest=sha256:f21853f7e19adab4705d39d798aea1842028ea316ca67998a31102a909a640d3

Observation 0e277ac6-cc79-46bb-9d52-de2e5ed1556f · outbound

This paper cites Learn2clean: Optimizing the sequence of tasks for web data preparation.

SoftPipe: A Soft-Guided Reinforcement Learning Framework for Automated Data Preparation Learn2clean: Optimizing the sequence of tasks for web data preparation

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T16:25:31.330336Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:25:31.330336Z digest=sha256:02593596e7964d3783f94886c1f14853cf1397e604cbca90998f39e39bee0d77

Observation 4b5c1efb-6c01-4725-84f8-e1477ab52d2f · outbound

This paper cites Deepline: Automl tool for pipelines generation using deep reinforcement learning and hierarchical actions filtering.

SoftPipe: A Soft-Guided Reinforcement Learning Framework for Automated Data Preparation Deepline: Automl tool for pipelines generation using deep reinforcement learning and hierarchical actions filtering

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-06T16:25:31.333668Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:25:31.333668Z digest=sha256:bce36c73ebbe388542ee78882cf7da9bcb7b2ac791b65a958b680cbc171eb253

Observation a3d67bfa-c221-408b-b1e4-0e32f392a64c · outbound

This paper cites Democratizing data science through interactive curation of ml pipelines.

SoftPipe: A Soft-Guided Reinforcement Learning Framework for Automated Data Preparation Democratizing data science through interactive curation of ml pipelines

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T16:25:31.337217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:25:31.337217Z digest=sha256:abe8d470c403654fa5e3012b3d6e2d4e60aad52e1f1df56141037cba8416461a

Observation e05fea61-dc8a-499f-93af-1dfc4562ea8a · outbound

This paper cites Auto-Pipeline: Synthesizing Complex Data Pipelines By-Target Using Reinforcement Learning and Search.

SoftPipe: A Soft-Guided Reinforcement Learning Framework for Automated Data Preparation Auto-Pipeline: Synthesizing Complex Data Pipelines By-Target Using Reinforcement Learning and Search

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-06T16:25:31.340666Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:25:31.340666Z digest=sha256:f3bd9439b611571e1fa307b411585812085f044b59719830829a0968caf55000

Observation 4f040510-444b-4f7f-b7be-bcd2a2209fb5 · outbound

This paper cites CleanSurvival: Automated data preprocessing for time-to-event models using reinforcement learning.

SoftPipe: A Soft-Guided Reinforcement Learning Framework for Automated Data Preparation CleanSurvival: Automated data preprocessing for time-to-event models using reinforcement learning

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T16:25:31.343527Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:25:31.343527Z digest=sha256:22136409a8287c8a50fcf5a279928d217fec724ee0b6a3b1363b25ec99273b45

Observation 947edcfd-2730-48e6-b88d-f6b9cb647bb0 · outbound

This paper cites Advancing multimodal reasoning: From optimized cold start to staged reinforcement learning.

SoftPipe: A Soft-Guided Reinforcement Learning Framework for Automated Data Preparation Advancing multimodal reasoning: From optimized cold start to staged reinforcement learning

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-06T16:25:31.346376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:25:31.346376Z digest=sha256:dc61846f75b002ba7bd115ba8fb55e3785a9051a06730079a64b8c5255d77bd7

Observation 2a8b208d-4725-4e10-8c24-d62196afaa75 · outbound

This paper cites Ctxpipe: Context-aware data preparation pipeline construction for machine learning.

SoftPipe: A Soft-Guided Reinforcement Learning Framework for Automated Data Preparation Ctxpipe: Context-aware data preparation pipeline construction for machine learning

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:25:31.878808Z

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.

source=pdf_text observed=2026-08-06T16:25:31.349610Z digest=sha256:a9567293a8c78b6e9e289f6737de80896809b8e2d164d5e70c64d6302fc4d262

Observation 2f2ddaca-bf8d-4d10-ab8a-bc20987fac26 · outbound

This paper cites Haipipe: Combining human-generated and machine-generated pipelines for data preparation.

SoftPipe: A Soft-Guided Reinforcement Learning Framework for Automated Data Preparation Haipipe: Combining human-generated and machine-generated pipelines for data preparation

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T16:25:31.352407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:25:31.352407Z digest=sha256:7f6b40d123c63132061a70e5b033249d1f7d2e0c29ec0dae09250c7f38d70d6b

Observation 26be04c6-b5c9-4b87-8738-de879a12c918 · outbound

This paper cites Evaluation of a tree-based pipeline optimization tool for automating data science.

SoftPipe: A Soft-Guided Reinforcement Learning Framework for Automated Data Preparation Evaluation of a tree-based pipeline optimization tool for automating data science

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T16:25:31.355495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:25:31.355495Z digest=sha256:0525f96425d8e0ed6e83a0cd2f7ef2f94a6f7948da29d0e6ded8a615a8a6fe7c

Observation c07e849e-0978-4948-aabd-c6bdf17ad146 · outbound

This paper cites Efficient and robust automated machine learning.

SoftPipe: A Soft-Guided Reinforcement Learning Framework for Automated Data Preparation Efficient and robust automated machine learning

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:25:31.853731Z

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.

source=pdf_text observed=2026-08-06T16:25:31.358691Z digest=sha256:4c1a2a3b05db1a25521afb048d57372b7a703101d3c41c85e2936c9f2fcbb757

Observation 668e55cf-fc5e-442f-a2cf-fa6f6a884792 · outbound

This paper cites Data civilizer 2.0: A holistic framework for data preparation and analytics.

SoftPipe: A Soft-Guided Reinforcement Learning Framework for Automated Data Preparation Data civilizer 2.0: A holistic framework for data preparation and analytics

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:25:31.843046Z

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.

source=pdf_text observed=2026-08-06T16:25:31.361581Z digest=sha256:f0a52f1ef47d28a0e502381b54183e0276c3337972cd658f7184c9debe5e265d

Observation ce5ff606-eb86-46e3-9431-b08b122dd26c · outbound

This paper cites Dynaml: a scala & jvm machine learning toolbox for research, education & industry., 2021.

SoftPipe: A Soft-Guided Reinforcement Learning Framework for Automated Data Preparation Dynaml: a scala & jvm machine learning toolbox for research, education & industry., 2021

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:25:31.831714Z

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.

source=pdf_text observed=2026-08-06T16:25:31.365035Z digest=sha256:43f782308191acbb50cf46d55eb9ab449ccb424149ec09ebdca1fcf5e2a5612d

Observation 9e186650-f2d5-40c2-bda4-c91dc968891c · outbound

This paper cites Deep Learning with H2O, 3 2025.

SoftPipe: A Soft-Guided Reinforcement Learning Framework for Automated Data Preparation Deep Learning with H2O, 3 2025

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:25:31.820757Z

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.

source=pdf_text observed=2026-08-06T16:25:31.367906Z digest=sha256:39dde77b7538882b4dad8c526e5f629a12c6a488bf6ab2f547e6aafafd32e6ca

Observation ed53ff61-3358-490b-9ce0-54ef7fb264a4 · outbound

This paper cites CausalCOMRL: Context-Based Offline Meta-Reinforcement Learning with Causal Representation.

SoftPipe: A Soft-Guided Reinforcement Learning Framework for Automated Data Preparation CausalCOMRL: Context-Based Offline Meta-Reinforcement Learning with Causal Representation

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-06T16:25:31.371167Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:25:31.371167Z digest=sha256:92b09e97ee00abbe01598561b1ee727d4e6fd81de6576e8ccd1de8636ab0fa45

Observation 208d4a9d-4168-412a-8321-cc94d79a2112 · outbound

This paper cites Towards sample efficient reinforcement learning.

SoftPipe: A Soft-Guided Reinforcement Learning Framework for Automated Data Preparation Towards sample efficient reinforcement learning

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-06T16:25:31.374452Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:25:31.374452Z digest=sha256:64810b64dc8418ba97eb3c4c6a8b4098383cb26f82b902232192bc9d6614aaee

Observation c72e551e-f451-4c3e-8bec-cebd0e4444a1 · outbound

This paper cites Feature engineering for predictive modeling using reinforcement learning.

SoftPipe: A Soft-Guided Reinforcement Learning Framework for Automated Data Preparation Feature engineering for predictive modeling using reinforcement learning

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-06T16:25:31.377461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:25:31.377461Z digest=sha256:4bd73f61ebeff805fbf1ae6ab18cb73887db1cee0a4218ccae6a774b0426f10f

Observation 87826f4e-ab5a-4b37-aea6-979d03b243d6 · outbound

This paper cites Metaprep: Data preparation pipelines recommen- dation via meta-learning.

SoftPipe: A Soft-Guided Reinforcement Learning Framework for Automated Data Preparation Metaprep: Data preparation pipelines recommen- dation via meta-learning

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:25:31.794987Z

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.

source=pdf_text observed=2026-08-06T16:25:31.380836Z digest=sha256:5bf62487343db724b23ea45cfa494db0000912aa0250ddd3dd28b40bd5ac9501

Observation 00da15c6-4e88-49c0-8af6-98bad6e5b422 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

SoftPipe: A Soft-Guided Reinforcement Learning Framework for Automated Data Preparation Evaluating Large Language Models Trained on Code

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-06T16:25:31.384009Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:25:31.384009Z digest=sha256:330f212b40c5c785b5694bf7293752a19a107a3e9dc4a352f460ab0e17f0b696

Observation c5dcefbd-bfa0-4d3e-8850-72028a32b79c · outbound

This paper cites Generalizable Two-Branch Framework for Image Class-Incremental Learning.

SoftPipe: A Soft-Guided Reinforcement Learning Framework for Automated Data Preparation Generalizable Two-Branch Framework for Image Class-Incremental Learning

Reference 22

Resolution
metadata mismatch
local_arxiv, observed 2026-08-06T16:25:31.537442Z

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.

source=pdf_text observed=2026-08-06T16:25:31.387429Z digest=sha256:e5b106d868a0fddf151d6c4bad358bcbaba703246e79e6da261394b74bd2a0d9

Observation 87c95bda-2158-4dde-b0ed-918c05984f04 · outbound

This paper cites Borodin-Kostochka conjecture and Partitioning a graph into classes with no clique of specified size.

SoftPipe: A Soft-Guided Reinforcement Learning Framework for Automated Data Preparation Borodin-Kostochka conjecture and Partitioning a graph into classes with no clique of specified size

Reference 23

Resolution
metadata mismatch
local_arxiv, observed 2026-08-06T16:25:31.522988Z

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.

source=pdf_text observed=2026-08-06T16:25:31.390897Z digest=sha256:fb893b5991923ac03794a9a9ed1a4e895329d09c1f8cef823074a884dfb43591

Observation fcae1e76-f45e-46cf-9fb3-b39ab4503c61 · outbound

This paper cites Finer: Investigating and Enhancing Fine-Grained Visual Concept Recognition in Large Vision Language Models.

SoftPipe: A Soft-Guided Reinforcement Learning Framework for Automated Data Preparation Finer: Investigating and Enhancing Fine-Grained Visual Concept Recognition in Large Vision Language Models

Reference 24

Resolution
verified exact
local_arxiv, observed 2026-08-06T16:25:31.507449Z

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.

source=pdf_text observed=2026-08-06T16:25:31.394641Z digest=sha256:2035dd551cffb9c9d9013be5136b215a4e7961864550b8cd00967b1d0c71af05

Observation 17a198e6-0765-46c1-a092-bde4172d6800 · outbound

This paper cites Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review.

SoftPipe: A Soft-Guided Reinforcement Learning Framework for Automated Data Preparation Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-06T16:25:31.398340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:25:31.398340Z digest=sha256:e111b5ec28a3041eb1f9cfa93d5094fa3953e9a87526a956968deee18bad740e

Observation e5ca89d1-ba9e-4663-a01c-b7cb4da6519f · outbound

This paper cites Efficient reinforcement learning with large language model priors.

SoftPipe: A Soft-Guided Reinforcement Learning Framework for Automated Data Preparation Efficient reinforcement learning with large language model priors

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:25:31.784036Z

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.

source=pdf_text observed=2026-08-06T16:25:31.401716Z digest=sha256:c182374dd3c252d0c6192122393cdbf64333eaca230f8c2c9ea67c577e3e6f61

Observation 59d7ab0f-ba63-4ca1-95c2-3b0b4eed7626 · outbound

This paper cites Direct Preference Optimization: Your Language Model is Secretly a Reward Model.

SoftPipe: A Soft-Guided Reinforcement Learning Framework for Automated Data Preparation Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-06T16:25:31.405087Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:25:31.405087Z digest=sha256:44bc67a3d02b314ba2bd60b7d28e3cfd998dc5b6d6c74b01396934e9fe0fe7f2

Observation 66e70f4e-bd49-4bbe-9cbb-6cc9342f5ee3 · outbound

This paper cites Openml: networked science in machine learning.

SoftPipe: A Soft-Guided Reinforcement Learning Framework for Automated Data Preparation Openml: networked science in machine learning

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-06T16:25:31.408975Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:25:31.408975Z digest=sha256:f3e1428ec395dcac6696abd909795fba3bb176ff323bf2d3e0a0c58a995e6dd9

Observation c96d88b1-0935-4903-a6bd-b5c63fb875d3 · outbound

This paper cites Diffprep: Differentiable data preprocessing pipeline search for learning over tabular data.

SoftPipe: A Soft-Guided Reinforcement Learning Framework for Automated Data Preparation Diffprep: Differentiable data preprocessing pipeline search for learning over tabular data

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-06T16:25:31.412463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:25:31.412463Z digest=sha256:ccfab5c12417f1b7bc7672f8df175c7086961de01acf5c98622f453216dcccf2

Observation d0ccc8db-56fd-4711-850b-e2e0da97e2ec · outbound

This paper cites Cleanml: A study for evaluating the impact of data cleaning on ml classification tasks.

SoftPipe: A Soft-Guided Reinforcement Learning Framework for Automated Data Preparation Cleanml: A study for evaluating the impact of data cleaning on ml classification tasks

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:25:31.758679Z

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.

source=pdf_text observed=2026-08-06T16:25:31.415916Z digest=sha256:5ea1d2b543b38f3f0365d4da18c8945ce847312cd2a48e295c1ff3cc86d90eac

Observation bdce52e1-9935-4170-bed3-575e7dad493c · outbound

This paper cites H2o automl: Scalable automatic machine learning.

SoftPipe: A Soft-Guided Reinforcement Learning Framework for Automated Data Preparation H2o automl: Scalable automatic machine learning

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-06T16:25:31.419445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:25:31.419445Z digest=sha256:ff30c21f196021941c81e6e415d9e4be9edd49c459c81da9d4621ed034c2abc3

Observation 4262c6a2-2708-4a3f-b493-2abe98b827fd · outbound

This paper cites Qwen3 Technical Report.

SoftPipe: A Soft-Guided Reinforcement Learning Framework for Automated Data Preparation Qwen3 Technical Report

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-06T16:25:31.422187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:25:31.422187Z digest=sha256:a062b5201f868906f3db6b2b2f11255e5ab9af7bb49b0eaf13baef9cd98fe068

Observation 8716c998-4bca-41ba-9d00-a4ba29746241 · outbound

This paper cites LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models.

SoftPipe: A Soft-Guided Reinforcement Learning Framework for Automated Data Preparation LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models

Reference 33

Resolution
malformed identifier
no resolver link, observed 2026-08-06T16:25:31.425452Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:25:31.425452Z digest=sha256:b4e72d489aed9f36fc5c0abed07279d977710caf887835de68502050d6d88d10

Pith citing papers

No inbound Pith citation observations are available.