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Paper Citation Record · LEDGER

TopoFE: topology-aware LLM-guided Automated Feature Engineering

As of 8 August 2026, this Paper Citation Record lists 100 of 101 outbound references and 0 inbound Pith citation observations for arXiv:2607.23286.

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

pith.paper-citation-record.v1
2607.23286 v1

Coverage vector

measured 100 of 101 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-31T23:58:37.065472Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

100 of 101 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved100
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5977d01f-0bea-43a2-a1d4-88dcfc3e54cd · outbound

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

TopoFE: topology-aware LLM-guided Automated Feature Engineering Feature engineering for machine learning and data analytics

Reference 1

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source=arxiv_source observed=2026-07-31T23:58:27.145466Z digest=sha256:25c20b29f249a07793ca23c4e706026743d5012db437c7e37250290fbb5114d7

Observation 90c3a2a9-d615-4794-802f-c1e50b7772d0 · outbound

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

TopoFE: topology-aware LLM-guided Automated Feature Engineering Openfe: Automated feature generation with expert-level performance

Reference 2

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source=arxiv_source observed=2026-07-31T23:58:27.246384Z digest=sha256:ca9079c939f144ceb61eb4762912762dc31d54eb316ed39cecce88dde4a4e96f

Observation 4fbe7cf5-fa8f-4bfc-9d21-20ab244e2f55 · outbound

This paper cites Large language models for automated data science: Introducing caafe for context-aware automated feature engineering.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Large language models for automated data science: Introducing caafe for context-aware automated feature engineering

Reference 3

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source=arxiv_source observed=2026-07-31T23:58:27.378767Z digest=sha256:de410b093b091a932327e3005b2ca4286f13b4a042c60b326ff3a76d3ffe078c

Observation 360325be-9f06-4543-8d9c-ffb5c0c731fd · outbound

This paper cites Tpot: A tree-based pipeline optimization tool for automating machine learning.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Tpot: A tree-based pipeline optimization tool for automating machine learning

Reference 4

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source=arxiv_source observed=2026-07-31T23:58:27.561532Z digest=sha256:cea046f15311ae82371924ae460cff0a9fe132370130b4981510e3e834a00f42

Observation a95417e2-c4d0-42df-ab58-d4943a183b55 · outbound

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

TopoFE: topology-aware LLM-guided Automated Feature Engineering The autofeat python library for automated feature engineering and selection

Reference 5

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source=arxiv_source observed=2026-07-31T23:58:27.646761Z digest=sha256:81fbda32d6702dcf1ddd1e2a890e0568cfd38e48a92547f793b254036e540f0f

Observation 69d76dba-37e6-4667-9cfc-45038bea3d9a · outbound

This paper cites Large language models can automatically engineer features for few-shot tabular learning.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Large language models can automatically engineer features for few-shot tabular learning

Reference 6

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source=arxiv_source observed=2026-07-31T23:58:27.779932Z digest=sha256:cca3bed9895e834d96f3777e1e3b74291a357a16065db79fee1c1bfb4cfff1fd

Observation 0f3ef9ca-1977-4231-b139-819b8247a917 · outbound

This paper cites Evolutionary large language model for automated feature transformation.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Evolutionary large language model for automated feature transformation

Reference 8

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source=arxiv_source observed=2026-07-31T23:58:28.104586Z digest=sha256:2ca7f3350f37b85c3609aac225fdf42d2a4dc9ad8281bc66eace38c296666b49

Observation 8fa0baf1-02b5-43df-a40d-2462d081caf4 · outbound

This paper cites Uci machine learning repository, 2007.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Uci machine learning repository, 2007

Reference 9

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source=arxiv_source observed=2026-07-31T23:58:28.166246Z digest=sha256:258f54b44aac8fed3cfc0f4e22b9124c4b2f06278bec77cf2b38dfe28f948198

Observation be23aebb-6778-46c7-a4ea-6bca7c27a596 · outbound

This paper cites Openml: networked science in machine learning.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Openml: networked science in machine learning

Reference 10

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source=arxiv_source observed=2026-07-31T23:58:28.249449Z digest=sha256:f4c6ac6f0b56a5368b186fa2ba95766c05bd78b15dda405b8e65f40455cab64f

Observation 349317a3-12af-4433-8e13-11efaca5e22e · outbound

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

TopoFE: topology-aware LLM-guided Automated Feature Engineering Tabpfn: A transformer that solves small tabular classification problems in a second

Reference 11

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source=arxiv_source observed=2026-07-31T23:58:28.383967Z digest=sha256:07bb41a4eff6115d2e481f526643fa3b58529c9180feb28e02e41630109fbadd

Observation d191a7b4-6161-4f85-b730-fedb6d12619f · outbound

This paper cites Optimized feature generation for tabular data via llms with decision tree reasoning.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Optimized feature generation for tabular data via llms with decision tree reasoning

Reference 12

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source=arxiv_source observed=2026-07-31T23:58:28.509016Z digest=sha256:87cf5b8adfe66d1f79435bf587d54568320ec4d560d878fd267f25f2d4e300a7

Observation 6ef7f05e-933d-4f43-8404-410e4db897e7 · outbound

This paper cites Lift: Language-interfaced fine-tuning for non-language machine learning tasks.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Lift: Language-interfaced fine-tuning for non-language machine learning tasks

Reference 16

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source=arxiv_source observed=2026-07-31T23:58:28.912841Z digest=sha256:83e28318308658aec502e8b8e3b2e77f39df8eb64b91a5ced9ae391b2e4428ec

Observation e49e1668-1025-4af0-bbfa-0ec2dbe26c3c · outbound

This paper cites Catboost: unbiased boosting with categorical features.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Catboost: unbiased boosting with categorical features

Reference 17

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source=arxiv_source observed=2026-07-31T23:58:29.017585Z digest=sha256:1c66bada3974e0b6eb734961d13a4bbe3f8962203ada1db1f18bdb91ac8030e9

Observation 0aa60d35-bcc8-4a9f-ad19-3baae158c2ee · outbound

This paper cites In Geomatic approaches for modeling land change scenarios, pages 451--455.

TopoFE: topology-aware LLM-guided Automated Feature Engineering In Geomatic approaches for modeling land change scenarios, pages 451--455

Reference 18

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source=arxiv_source observed=2026-07-31T23:58:29.105738Z digest=sha256:1f829d5a2108f559ce8bdc68300510b3a5befa1039c9e7cb8040abfa2222718d

Observation 32cf6ae0-28ba-4d72-80dd-202d223cc5fa · outbound

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

TopoFE: topology-aware LLM-guided Automated Feature Engineering Tabpfn: A transformer that solves small tabular classification problems in a second

Reference 19

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source=arxiv_source observed=2026-07-31T23:58:29.185279Z digest=sha256:bc459d650606da9c68427c64c5ac2793d5292caaf1e98386b68e30609ed8047c

Observation 0e284e69-eb4e-4f20-9329-33b70c25426b · outbound

This paper cites Batch normalization: Accelerating deep network training by reducing internal covariate shift.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Batch normalization: Accelerating deep network training by reducing internal covariate shift

Reference 20

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source=arxiv_source observed=2026-07-31T23:58:29.246523Z digest=sha256:5d620b7b4eaefcaba0e2ae8251ad2025074f800731aab36fa75eafae8496e17b

Observation 010d2c18-38ab-4e3d-b5a4-004169723bd5 · outbound

This paper cites Ferg-llm: Feature engineering by reason generation large language models.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Ferg-llm: Feature engineering by reason generation large language models

Reference 21

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source=arxiv_source observed=2026-07-31T23:58:29.328807Z digest=sha256:260c2c885a25943d711d8b1d5bb750f3f92cc4e7ad0a5748fd2681d002b3f92d

Observation 1a2e014c-369b-4f8b-89d2-13d35e1f17c9 · outbound

This paper cites Dynamic and adaptive feature generation with llm.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Dynamic and adaptive feature generation with llm

Reference 22

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source=arxiv_source observed=2026-07-31T23:58:29.424911Z digest=sha256:8f60bb0e9483f4841c7ce259f435cde28b45c364cee3515e9ff98cb85a845fa2

Observation e757ddc6-3ce6-4e46-ac43-3d9ca3e3be7f · outbound

This paper cites Large scale transfer learning for tabular data via language modeling.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Large scale transfer learning for tabular data via language modeling

Reference 27

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source=arxiv_source observed=2026-07-31T23:58:29.901488Z digest=sha256:a00af5494ea6357d6522487aecad4fdaa7057efee80fd82ae6a8f504bfdc322f

Observation 47cc6cc4-7d78-41bd-a077-45c38355610a · outbound

This paper cites Tab STAR : A tabular foundation model for tabular data with text fields.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Tab STAR : A tabular foundation model for tabular data with text fields

Reference 28

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source=arxiv_source observed=2026-07-31T23:58:29.987108Z digest=sha256:9873da63085fbc8497d5d09417d91a8ee96c560cc57058289b22bb3b801c7ef0

Observation 5cc3ccdf-5ec0-40d8-a7cc-3cad4343ec3e · outbound

This paper cites u ller, Ga \.

TopoFE: topology-aware LLM-guided Automated Feature Engineering u ller, Ga \

Reference 29

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source=arxiv_source observed=2026-07-31T23:58:30.068283Z digest=sha256:4ed957ffe5f68ecf80a40594ee708d4897df35883695aa0112fab156b872e72d

Observation 2de5c9cb-ebd5-4942-b0d9-f0f3dc621f1f · outbound

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

TopoFE: topology-aware LLM-guided Automated Feature Engineering Cresswell, Keyvan Golestan, Guangwei Yu, Anthony L

Reference 30

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source=arxiv_source observed=2026-07-31T23:58:30.144437Z digest=sha256:75d2f5f5fb1e964aa3524c766944295f5ab531ce9555f8d7450f91d24282f845

Observation b61c4dc5-effa-468e-8f19-c615bd23d9cd · outbound

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

TopoFE: topology-aware LLM-guided Automated Feature Engineering Tabllm: Few-shot classification of tabular data with large language models

Reference 31

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source=arxiv_source observed=2026-07-31T23:58:30.226984Z digest=sha256:4e04005abf7efb5057c5118a1034d5c14d37989af524ae08832bc6bb3f4fd411

Observation f091808e-534b-466e-988e-43a6db7dfd22 · outbound

This paper cites Towards cross-table masked pretraining for web data mining.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Towards cross-table masked pretraining for web data mining

Reference 32

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source=arxiv_source observed=2026-07-31T23:58:30.313333Z digest=sha256:fa35c93d9e6f6cfc82998f90222dccda9231f77f22ba63e8f1e50de444b6cf9f

Observation 12d92266-064d-4cd2-819b-4987a8267dc2 · outbound

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

TopoFE: topology-aware LLM-guided Automated Feature Engineering Carte: Pretraining and transfer for tabular learning

Reference 33

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source=arxiv_source observed=2026-07-31T23:58:30.393847Z digest=sha256:5e8b41640eeefd182ec2b7f61f2851211a59695549d59f2043cdf23f5af0b7eb

Observation ef1dd3de-2d6c-4805-9669-4657fb1f4040 · outbound

This paper cites Making pre-trained language models great on tabular prediction.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Making pre-trained language models great on tabular prediction

Reference 34

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source=arxiv_source observed=2026-07-31T23:58:30.460880Z digest=sha256:85e01885a3fdf81b38fc6fb171b773ef79bf4e19e57ab5cafc1d33f24bda33b1

Observation 14d5bffa-49d8-482a-b69b-288903339004 · outbound

This paper cites Generative table pre-training empowers models for tabular prediction.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Generative table pre-training empowers models for tabular prediction

Reference 35

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source=arxiv_source observed=2026-07-31T23:58:30.541916Z digest=sha256:22b1cdbc460864d90153ccc88e0c8dba3bb3baefb2eb7b2c4f783c00be22e773

Observation e7aee460-629b-428d-81b6-35ccd7a205da · outbound

This paper cites Language models are realistic tabular data generators.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Language models are realistic tabular data generators

Reference 36

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source=arxiv_source observed=2026-07-31T23:58:30.651575Z digest=sha256:160a3412bb4208e9068ccbff8e9bd98d4f7d73c9d4e0cacf380d414cd220ccf5

Observation 98367569-43da-44f4-a612-44642cdfb6e2 · outbound

This paper cites Exploring llm agents for cleaning tabular machine learning datasets.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Exploring llm agents for cleaning tabular machine learning datasets

Reference 37

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source=arxiv_source observed=2026-07-31T23:58:30.727766Z digest=sha256:37589f78536c6ae4f2bdf3869479cd3fa94a637c5f5721eda48e22b49b0af8e8

Observation 99a5cb92-9ecb-4b09-859a-044f469e128c · outbound

This paper cites Evoprompt: Connecting llms with evolutionary algorithms yields powerful prompt optimizers.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Evoprompt: Connecting llms with evolutionary algorithms yields powerful prompt optimizers

Reference 38

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source=arxiv_source observed=2026-07-31T23:58:30.802356Z digest=sha256:62d17f94c4ec2db6a2b158701565c22bc22ecda5787fd72958db34b20bc7c9c2

Observation 09e9ee14-6110-43ea-be27-2a96469bce89 · outbound

This paper cites Promptbreeder: Self-referential self-improvement via prompt evolution.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Promptbreeder: Self-referential self-improvement via prompt evolution

Reference 39

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source=arxiv_source observed=2026-07-31T23:58:30.888873Z digest=sha256:636e531d3fda5d055d673215826e5bc309b1ef678eefeae4ece52ba54a48d2c4

Observation 80b94a28-776b-43fc-bbdc-8fa6cdf4b925 · outbound

This paper cites Dynamic cheatsheet: Test-time learning with adaptive memory.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Dynamic cheatsheet: Test-time learning with adaptive memory

Reference 40

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source=arxiv_source observed=2026-07-31T23:58:30.949636Z digest=sha256:3dc8f726e53aca25c72760e28767cbe03d0d275956e2f57597cc6e6e33f610c8

Observation 93b3a6b8-5367-4731-937f-e002f65eb05b · outbound

This paper cites Gepa: Reflective prompt evolution can outperform reinforcement learning.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Gepa: Reflective prompt evolution can outperform reinforcement learning

Reference 41

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source=arxiv_source observed=2026-07-31T23:58:31.121996Z digest=sha256:c8cf86f3605af3f38b9911d3891d5ba31fe55ccd9db25261191e27e9f3c4af23

Observation b5df8935-f1fd-4510-8219-51de504682b8 · outbound

This paper cites Algorithm discovery with llms: Evolutionary search meets reinforcement learning.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Algorithm discovery with llms: Evolutionary search meets reinforcement learning

Reference 42

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source=arxiv_source observed=2026-07-31T23:58:31.217939Z digest=sha256:9fe152e40c4a15085a04971975e7600310ad054e193546246657e8bc031daa2d

Observation 81093b91-28b1-4cb0-b242-751bf2f98db7 · outbound

This paper cites Openevolve: an open-source evolutionary coding agent, 2025.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Openevolve: an open-source evolutionary coding agent, 2025

Reference 45

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source=arxiv_source observed=2026-07-31T23:58:31.510376Z digest=sha256:8e9b3adeacc2f23cb5012037a3f2358c90b9d2834570df688424cda074b074df

Observation 7c97f309-b478-4bfe-8fc9-18160dbff9e1 · outbound

This paper cites Llm-sr: Scientific equation discovery via programming with large language models.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Llm-sr: Scientific equation discovery via programming with large language models

Reference 47

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source=arxiv_source observed=2026-07-31T23:58:31.724552Z digest=sha256:ab48211a66d675d01aa79aa6268250e921d23e7d115300b0c0c9995dacda0298

Observation 803dfd79-6507-4026-8c1f-f81023a42141 · outbound

This paper cites an unresolved cited work.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Unresolved cited work

Reference 50

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source=arxiv_source observed=2026-07-31T23:58:31.962424Z digest=sha256:2de1bc82bdc37b07fffa1ccedd410de8a261f0f9bd69a87fe14979424db406fe

Observation c947f4f9-9bc8-480e-a38b-86c086448575 · outbound

This paper cites Evolution of heuristics: Towards efficient automatic algorithm design using large language model.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Evolution of heuristics: Towards efficient automatic algorithm design using large language model

Reference 51

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source=arxiv_source observed=2026-07-31T23:58:32.077633Z digest=sha256:757c05cef42df473c259576eebabaafa4dd6af07b23a35a397bd3326665aa134

Observation 6ec57d2f-fb52-4c29-8438-cea772c9f346 · outbound

This paper cites Reevo: Large language models as hyper-heuristics with reflective evolution.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Reevo: Large language models as hyper-heuristics with reflective evolution

Reference 52

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source=arxiv_source observed=2026-07-31T23:58:32.189438Z digest=sha256:73d29bce1fa60fc892475351ea54aff9d5a3fa3c7778bd43bfb31f9f711922f4

Observation 4bd83af4-b7f5-416c-b381-c96cf7185147 · outbound

This paper cites Evoagent: Towards automatic multi-agent generation via evolutionary algorithms.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Evoagent: Towards automatic multi-agent generation via evolutionary algorithms

Reference 53

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source=arxiv_source observed=2026-07-31T23:58:32.279673Z digest=sha256:44de03efae2dc35da0047fc535aa7c803f59f19305f4225953d75dcaccae2064

Observation 1d02f0fe-c9ad-4719-b07a-5e6dbea37912 · outbound

This paper cites Agentsquare: Automatic llm agent search in modular design space.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Agentsquare: Automatic llm agent search in modular design space

Reference 54

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source=arxiv_source observed=2026-07-31T23:58:32.424794Z digest=sha256:8e5014b443bef7af1460750badeb893c859e9ba27e4945a34cb82258ffb1b1a5

Observation 6ee197cf-e18c-41f1-afd3-391abda955e4 · outbound

This paper cites Findings of the Association for Computational Linguistics: NAACL 2025 , pages=.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Findings of the Association for Computational Linguistics: NAACL 2025 , pages=

Reference 55

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source=arxiv_source observed=2026-07-31T23:58:32.601979Z digest=sha256:0f25c690475aa6e49a944aabee90034fdcf1ca30376e03585b8de4ce7cd9ea39

Observation a5a46778-bbd0-4b29-bf78-2edc427e6352 · outbound

This paper cites International Conference on Learning Representations 2023 , year=.

TopoFE: topology-aware LLM-guided Automated Feature Engineering International Conference on Learning Representations 2023 , year=

Reference 56

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source=arxiv_source observed=2026-07-31T23:58:32.723287Z digest=sha256:c428f1a465878b50cf42c0945de8c42c0440e02df23f4091e2d0653267b767f6

Observation bab7016b-ef4f-4c47-9511-6610a9ba2a15 · outbound

This paper cites 2025 , eprint=.

TopoFE: topology-aware LLM-guided Automated Feature Engineering 2025 , eprint=

Reference 57

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source=arxiv_source observed=2026-07-31T23:58:32.843589Z digest=sha256:0487a0601144e6bc7551ca3fa021be3295244c48723b3aa6955afd9aca72b1e2

Observation d592a207-be01-4400-88c7-ffa4809919d3 · outbound

This paper cites an unresolved cited work.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Unresolved cited work

Reference 58

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source=arxiv_source observed=2026-07-31T23:58:32.979875Z digest=sha256:8999cff8d73fc1d7103270853ed3c9d76a9e47ec0799a2b08b0c0e3dc88ef803

Observation 4b1645b1-8d76-4b13-9f56-632f06a50a7d · outbound

This paper cites Joint European Conference on Machine Learning and Knowledge Discovery in Databases , pages=.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Joint European Conference on Machine Learning and Knowledge Discovery in Databases , pages=

Reference 59

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source=arxiv_source observed=2026-07-31T23:58:33.125998Z digest=sha256:48eed532a168ca0f004ef4bf9610376e24bbdc784f4dc26ae45df82f1f9b9c8f

Observation a1cb7a9c-218d-4b12-924b-f321a5b0bc31 · outbound

This paper cites Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence , pages=.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence , pages=

Reference 60

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no resolver link, observed 2026-07-31T23:58:33.252678Z

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source=arxiv_source observed=2026-07-31T23:58:33.252678Z digest=sha256:3d59b8d414ad807f2bfd86b11ab14762e5c4dcb4be93c634ef4fbdf7053edcb6

Observation 16da7cad-5e5f-45af-a40e-899434bf3d9b · outbound

This paper cites Qwen Technical Report.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Qwen Technical Report

Reference 61

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source=arxiv_source observed=2026-07-31T23:58:33.351116Z digest=sha256:8fffc2d0155ff441c07fdf0cbd134ba091bd0c7708d239d1bfa878915a5997f6

Observation 19ef3d47-ed79-410c-883d-e6bc17d54147 · outbound

This paper cites Proceedings of the AAAI conference on artificial intelligence , volume=.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Proceedings of the AAAI conference on artificial intelligence , volume=

Reference 62

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source=arxiv_source observed=2026-07-31T23:58:33.494458Z digest=sha256:627ba2ef9615ad2c69e8191f4aecfda5a9d9fc0e50b92825edb676250df4e27f

Observation 89e324d8-e4d1-4c39-b4e5-bac320ce57ba · outbound

This paper cites 2018 , publisher=.

TopoFE: topology-aware LLM-guided Automated Feature Engineering 2018 , publisher=

Reference 63

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source=arxiv_source observed=2026-07-31T23:58:33.622159Z digest=sha256:fcb8e5e365a92428560292f52c24868a52208e86e543d9e2d309124a73e1afef

Observation c8d3150b-c971-4f7d-a91d-d79832d62635 · outbound

This paper cites FELA: A Multi-Agent Evolutionary System for Feature Engineering of Industrial Event Log Data.

TopoFE: topology-aware LLM-guided Automated Feature Engineering FELA: A Multi-Agent Evolutionary System for Feature Engineering of Industrial Event Log Data

Reference 64

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source=arxiv_source observed=2026-07-31T23:58:33.740936Z digest=sha256:98263d77e860ccea1b88d7e3a0d5001bcbe2cedb345ee9f0922ad860bcf79952

Observation 98a475b0-17b0-411e-b862-1b9e7500c95e · outbound

This paper cites arXiv preprint arXiv:2602.17641 , year=.

TopoFE: topology-aware LLM-guided Automated Feature Engineering arXiv preprint arXiv:2602.17641 , year=

Reference 65

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source=arxiv_source observed=2026-07-31T23:58:33.837370Z digest=sha256:8ac5323cf3b78a645db00a04b6e92ccaf548c9199964f8525b6d3cea9e77ae7f

Observation f277bedf-6a4d-4e3f-9cc8-ce64b736287f · outbound

This paper cites Workshop on automatic machine learning , pages=.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Workshop on automatic machine learning , pages=

Reference 66

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source=arxiv_source observed=2026-07-31T23:58:33.955696Z digest=sha256:33b6eb23e809c778d5cf30fe70e617dbb528dd95e606f6c64dd3b6c4699cda75

Observation 0ff0b77c-9dfa-4140-8d5c-b6a7259374ce · outbound

This paper cites International Conference on Machine Learning , pages=.

TopoFE: topology-aware LLM-guided Automated Feature Engineering International Conference on Machine Learning , pages=

Reference 67

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source=arxiv_source observed=2026-07-31T23:58:34.057410Z digest=sha256:7f0d7f4d384ec9a6094778fe45f3bce13245d312dd5bc0621bc0387aca23e5c0

Observation 4919c582-b025-496a-98de-c1bd9cef20fe · outbound

This paper cites an unresolved cited work.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Unresolved cited work

Reference 68

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source=arxiv_source observed=2026-07-31T23:58:34.131727Z digest=sha256:df00af9ed823917ce1575cdcd2cf8189e221ffddb2ed5b88e7769e3340b51798

Observation f1c0a90d-2e86-4ba1-b312-d81920f748c4 · outbound

This paper cites an unresolved cited work.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Unresolved cited work

Reference 69

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:34.187330Z digest=sha256:e56d3abab58a86de728ddcbde6c9336a3c954d8cf6d929409dccf73f3c969bcf

Observation ef0168b0-4cf2-4867-9722-1a0f549f0bf7 · outbound

This paper cites Advances in neural information processing systems , volume=.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Advances in neural information processing systems , volume=

Reference 70

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source=arxiv_source observed=2026-07-31T23:58:34.256266Z digest=sha256:16df35c5d8f7b28ba922f9b3390a2b7bc8657178bce029ae20980e0ff40d5dfb

Observation 1f4e53ab-0f04-40a7-a305-1a97dd8203d1 · outbound

This paper cites an unresolved cited work.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Unresolved cited work

Reference 71

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source=arxiv_source observed=2026-07-31T23:58:34.313353Z digest=sha256:7a8cea42f157ec6fcd593c143292567f3491a3c74742deee869904ab5a4a49c9

Observation 3039eb44-66bd-4ba1-abba-be993b747926 · outbound

This paper cites an unresolved cited work.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Unresolved cited work

Reference 72

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source=arxiv_source observed=2026-07-31T23:58:34.385077Z digest=sha256:21b7c25e2678085f9500debc951a0f2d828592ee1b2ab75843e15a4490c96bf5

Observation 7ea5310c-7169-462a-996b-8aa5790b0a29 · outbound

This paper cites CodeEvolve: an open source evolutionary coding agent for algorithmic discovery and optimization.

TopoFE: topology-aware LLM-guided Automated Feature Engineering CodeEvolve: an open source evolutionary coding agent for algorithmic discovery and optimization

Reference 73

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source=arxiv_source observed=2026-07-31T23:58:34.438559Z digest=sha256:780c2bb4c0c3eb27c3daeb2359d04698d73601db4f44e03cc073c561bf621526

Observation fbace66d-bedf-42f6-9400-7febb78e8295 · outbound

This paper cites an unresolved cited work.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Unresolved cited work

Reference 74

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source=arxiv_source observed=2026-07-31T23:58:34.509226Z digest=sha256:4e36eeff0a95eee45c3fb6f33e2a0a8500ba726f10002a501b3cb720afcf3975

Observation 8cdb6f57-03b8-4ab8-a5b2-d774abe97707 · outbound

This paper cites ShinkaEvolve: Towards Open-Ended And Sample-Efficient Program Evolution.

TopoFE: topology-aware LLM-guided Automated Feature Engineering ShinkaEvolve: Towards Open-Ended And Sample-Efficient Program Evolution

Reference 75

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source=arxiv_source observed=2026-07-31T23:58:34.586735Z digest=sha256:c79b106060f3f579594a39be8e989a44c3615852438e258956dc115da8719f85

Observation a9291305-8bd3-4411-ad8d-f0ada764d2e8 · outbound

This paper cites URL https://github.

TopoFE: topology-aware LLM-guided Automated Feature Engineering URL https://github

Reference 76

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source=arxiv_source observed=2026-07-31T23:58:34.660198Z digest=sha256:93678043e30360e53b0946719571da706fa27a853f6feaa0b3ca26e18b9e1ae4

Observation 9f130cca-e981-40e7-b6eb-13e370a737f8 · outbound

This paper cites AlphaEvolve: A coding agent for scientific and algorithmic discovery.

TopoFE: topology-aware LLM-guided Automated Feature Engineering AlphaEvolve: A coding agent for scientific and algorithmic discovery

Reference 77

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source=arxiv_source observed=2026-07-31T23:58:34.732416Z digest=sha256:2c8b459730b80fd09c6bdab08ac8bc96a5ab6ec5a0307f2ed55b8d39b32daa03

Observation c98d0eec-f400-4982-99d2-5b1587c56598 · outbound

This paper cites an unresolved cited work.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Unresolved cited work

Reference 78

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:34.810781Z digest=sha256:e913ada630fcc9d4fd5d44d399d1620961cfca8bbd777b3a77c8de46ece706b4

Observation 40c2ddd6-310d-4b9f-8010-b38bbcc8ae49 · outbound

This paper cites Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

Reference 79

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:34.864287Z digest=sha256:0fb1c4a09d42b2a7a086e143c9c3615f71cf02b45649b544affa2bd49f3b53dc

Observation 22b71019-9753-4cb6-889f-4ff1befa137c · outbound

This paper cites Reddy , booktitle=.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Reddy , booktitle=

Reference 80

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source=arxiv_source observed=2026-07-31T23:58:34.946931Z digest=sha256:8621681bed13b47de05c5ab789d2b8be6330f81474b8f10a7e2440f62555b391

Observation ed80e201-27da-44de-949d-3e3872e8b77b · outbound

This paper cites HeurAgenix: Leveraging LLMs for Solving Complex Combinatorial Optimization Challenges.

TopoFE: topology-aware LLM-guided Automated Feature Engineering HeurAgenix: Leveraging LLMs for Solving Complex Combinatorial Optimization Challenges

Reference 81

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source=arxiv_source observed=2026-07-31T23:58:34.995892Z digest=sha256:e2dde86b73fc7409d6eef31e89b79bcde7406fedbc573342030b0a196c2844b8

Observation 48483ee6-7ad1-4831-b17b-d965ec4f8abb · outbound

This paper cites arXiv preprint arXiv:2603.24382 , year=.

TopoFE: topology-aware LLM-guided Automated Feature Engineering arXiv preprint arXiv:2603.24382 , year=

Reference 82

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source=arxiv_source observed=2026-07-31T23:58:35.036935Z digest=sha256:e14cfb8d28b52ee65a013406f16dd76abe6b9946ce8f85309343e3dac8b3a71d

Observation 44631bab-b995-4fb2-a67f-3a5314a1f123 · outbound

This paper cites Embedding Domain-Specific Knowledge from LLMs into the Feature Engineering Pipeline.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Embedding Domain-Specific Knowledge from LLMs into the Feature Engineering Pipeline

Reference 83

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:35.114209Z digest=sha256:b5594f003b8dcbb4c57220be152f6e345d9e99728880f59d3681060e27beaf23

Observation e13ce95c-7664-4ccb-9421-120cf02416af · outbound

This paper cites arXiv e-prints , pages=.

TopoFE: topology-aware LLM-guided Automated Feature Engineering arXiv e-prints , pages=

Reference 84

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source=arxiv_source observed=2026-07-31T23:58:35.164633Z digest=sha256:ec78dc32f35ee0439d0e9c267da95c933ba9a60afc0fa93f1461ad21fa4d5c15

Observation dc270aa6-c73b-41c4-8899-04cd0ee090ca · outbound

This paper cites an unresolved cited work.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Unresolved cited work

Reference 85

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no resolver link, observed 2026-07-31T23:58:35.219017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:35.219017Z digest=sha256:73f1d921b3edff57ced5ff862e31b3ce00c092a7310974e923ef0b65af47f49b

Observation b5f6a715-9019-4587-a9b2-ff253d579d13 · outbound

This paper cites an unresolved cited work.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Unresolved cited work

Reference 86

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source=arxiv_source observed=2026-07-31T23:58:35.278450Z digest=sha256:f24bfac2ed029f7c365e37063e19653365c1463b9c18cf4ed691803cd91530bd

Observation d8b861c0-e3c6-4307-915e-4f9db43fd669 · outbound

This paper cites International Workshop on Causality, Agents and Large Models , pages=.

TopoFE: topology-aware LLM-guided Automated Feature Engineering International Workshop on Causality, Agents and Large Models , pages=

Reference 87

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source=arxiv_source observed=2026-07-31T23:58:35.328855Z digest=sha256:3e03d26ad59607d79f6989f918edab2d4d9565738ceba8963a3a8f81b3df4d9e

Observation d0e0e316-b14b-4566-940b-1e1c6c8485c7 · outbound

This paper cites International Conference on Machine Learning , pages=.

TopoFE: topology-aware LLM-guided Automated Feature Engineering International Conference on Machine Learning , pages=

Reference 88

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:35.379977Z digest=sha256:1b536d4a156686e23c177542e602acbb929619bcddd55155165627f96ee465f1

Observation a8049222-9833-49c8-af00-c2f0533395b1 · outbound

This paper cites an unresolved cited work.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Unresolved cited work

Reference 89

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:35.439461Z digest=sha256:e7587268ca6d185e456b1160d5c80666b2f1bf67cca3e7f2c584b53778f23f56

Observation 5052276a-9d74-4103-9d40-e170bdba5b0b · outbound

This paper cites REaLTabFormer: Generating Realistic Relational and Tabular Data using Transformers.

TopoFE: topology-aware LLM-guided Automated Feature Engineering REaLTabFormer: Generating Realistic Relational and Tabular Data using Transformers

Reference 90

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source=arxiv_source observed=2026-07-31T23:58:35.470651Z digest=sha256:c76911899be0bc518bfc130f2f442eca48ffc5433577e56f34c6aa3c443e2c5b

Observation fccdaa91-bd7f-45fd-99ce-17b27deb0ebc · outbound

This paper cites an unresolved cited work.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Unresolved cited work

Reference 91

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:35.524073Z digest=sha256:1aed404121066cdf6656e873a9882ab8e44259e6d50a29a6d92ca54f7a2a0fdf

Observation 828eb2be-59f7-46a8-a1ff-e1473d2f343e · outbound

This paper cites an unresolved cited work.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Unresolved cited work

Reference 92

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no resolver link, observed 2026-07-31T23:58:35.589257Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:35.589257Z digest=sha256:7be70f986214456f93a9ee1ffe4f43b55a9100dfdb1f877906e05af5087b6ee8

Observation 8cd3dc74-76ed-4b86-87f9-50121712681c · outbound

This paper cites International Conference on Machine Learning , pages=.

TopoFE: topology-aware LLM-guided Automated Feature Engineering International Conference on Machine Learning , pages=

Reference 93

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no resolver link, observed 2026-07-31T23:58:35.643072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:35.643072Z digest=sha256:71068a1c1cee3d0349a5181e9efbf92a5da752a557489647037393c5c837da59

Observation 7d7ab3b2-ad8e-45ea-b425-6040b1d57aa7 · outbound

This paper cites Proceedings of the ACM Web Conference 2024 , pages=.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Proceedings of the ACM Web Conference 2024 , pages=

Reference 94

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no resolver link, observed 2026-07-31T23:58:35.721558Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:35.721558Z digest=sha256:3d418ac28303b2c59bfbba2b4a757f0774eb9046277b2a536f11444c07f42c6e

Observation f00d742a-b2e3-41dd-96dc-659ead695515 · outbound

This paper cites an unresolved cited work.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Unresolved cited work

Reference 95

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no resolver link, observed 2026-07-31T23:58:35.781226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:35.781226Z digest=sha256:b41f99b619ee23a6ea40db945e5a475ffd8d8d6fe79517b041446578e0b7ea05

Observation 07bc5add-0303-4a1f-a56a-c9db290cc9b2 · outbound

This paper cites Proceedings of the 2023 conference on empirical methods in natural language processing , pages=.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Proceedings of the 2023 conference on empirical methods in natural language processing , pages=

Reference 96

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no resolver link, observed 2026-07-31T23:58:35.842910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:35.842910Z digest=sha256:e47b4ac0c079cd245aaae8ce1887a30d4ae9f95a2ea784f4b24817186d8ad9b9

Observation e2946f4a-e16e-4ac1-8884-03a71b5d4591 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Advances in Neural Information Processing Systems , volume=

Reference 97

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no resolver link, observed 2026-07-31T23:58:35.919158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:35.919158Z digest=sha256:b3ed117a5a973e8fd3c67c7605cda91d1dbe06c53b411889ac8e874380188336

Observation f0fb6bc5-cd5b-4be0-a69b-2c252d8a2626 · outbound

This paper cites an unresolved cited work.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Unresolved cited work

Reference 98

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no resolver link, observed 2026-07-31T23:58:35.994513Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-07-31T23:58:35.994513Z digest=sha256:f84bdcc5cabfa6f178f9a6b35e9dfe1049f2f95263d774decf2e25992bf44f7a

Observation 3145468f-63a3-488a-af53-b928e1600abc · outbound

This paper cites Advances in neural information processing systems , volume=.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Advances in neural information processing systems , volume=

Reference 99

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no resolver link, observed 2026-07-31T23:58:36.045689Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:36.045689Z digest=sha256:8739ac609753a57fd80ac4696a90d17c99cb4829a0efa843fbb4b38af1edfad1

Observation 3eef6cbc-df46-4eed-ac4b-6abfb0231320 · outbound

This paper cites International conference on artificial intelligence and statistics , pages=.

TopoFE: topology-aware LLM-guided Automated Feature Engineering International conference on artificial intelligence and statistics , pages=

Reference 100

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no resolver link, observed 2026-07-31T23:58:36.105184Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:36.105184Z digest=sha256:0050638918f77577398bc84eb80917c735d0ec109e3d18b4946ad4e2e6446d31

Observation 07b60d7f-0442-46ee-a00d-1c09c39cad07 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Advances in Neural Information Processing Systems , volume=

Reference 101

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no resolver link, observed 2026-07-31T23:58:36.173123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:36.173123Z digest=sha256:d87951f678768f7ae1e0e3faccf108784bc4e378784741c1d943c92c6c625b19

Observation 2278658f-55d3-42da-abf6-045b54be1231 · outbound

This paper cites Qwen3 Technical Report.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Qwen3 Technical Report

Reference 102

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no resolver link, observed 2026-07-31T23:58:36.263252Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:36.263252Z digest=sha256:073b223aca239e180784c45320ff57258cdb4a2af5b3fe5da88225647d62fa2c

Observation 2d98b8eb-345d-4614-ad49-1588c13fbaaf · outbound

This paper cites International conference on machine learning , pages=.

TopoFE: topology-aware LLM-guided Automated Feature Engineering International conference on machine learning , pages=

Reference 103

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no resolver link, observed 2026-07-31T23:58:36.331742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:36.331742Z digest=sha256:372fd7f4cef1f350f818118e82a52b55b947f1a2a478f610cdea672c1595ea46

Observation 3d78b905-4fda-43b2-be82-8e11c4662cd9 · outbound

This paper cites 2017 , publisher=.

TopoFE: topology-aware LLM-guided Automated Feature Engineering 2017 , publisher=

Reference 104

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no resolver link, observed 2026-07-31T23:58:36.376148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:36.376148Z digest=sha256:978bef58f3ce662d40daae00a6493fd17cb360503435f1f317f0917b04fa05dd

Observation 3885fc35-a018-4170-be84-ca11ec16f572 · outbound

This paper cites Advances in neural information processing systems , volume=.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Advances in neural information processing systems , volume=

Reference 105

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no resolver link, observed 2026-07-31T23:58:36.432257Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:36.432257Z digest=sha256:e0dc5b9a2ecca34d8a288604b6201403f4f94e8b368c96b01a4cb3d724fb5253

Observation 29ffbe9a-d4d2-4553-87d0-4a2e2fd16f87 · outbound

This paper cites Qwen2.5-Coder Technical Report.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Qwen2.5-Coder Technical Report

Reference 106

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no resolver link, observed 2026-07-31T23:58:36.514015Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:36.514015Z digest=sha256:ba9247179fc995e8d7fcc85321f2b7e467a91072d8d65aaed7b4ca8332e258d9

Observation 3889b747-071d-4ad9-a521-d79cfe475ee3 · outbound

This paper cites GPT-4o System Card.

TopoFE: topology-aware LLM-guided Automated Feature Engineering GPT-4o System Card

Reference 107

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no resolver link, observed 2026-07-31T23:58:36.571134Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:36.571134Z digest=sha256:1d0c66d3973873dd1bc66e121deb21cb46fc612c3bf1ea348ef5d171cd5329e1

Observation a0a603f2-43fe-4917-aedf-287ca1028ed3 · outbound

This paper cites 2007 , publisher=.

TopoFE: topology-aware LLM-guided Automated Feature Engineering 2007 , publisher=

Reference 108

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no resolver link, observed 2026-07-31T23:58:36.669825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:36.669825Z digest=sha256:49a3d01d2bc1ed8b2f31b47388998b830acc910255bdd424714c5089eb574c93

Observation b0f6ed1a-5ee1-4fd6-ad10-98b343f12085 · outbound

This paper cites LLM-FE: Automated Feature Engineering for Tabular Data with LLMs as Evolutionary Optimizers.

TopoFE: topology-aware LLM-guided Automated Feature Engineering LLM-FE: Automated Feature Engineering for Tabular Data with LLMs as Evolutionary Optimizers

Reference 109

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no resolver link, observed 2026-07-31T23:58:36.739384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:36.739384Z digest=sha256:706c8a3f05a7d45e118e4526321ab1d9eb98924457650b45f69eed60fca1ebcf

Observation b3fc30cb-2aa6-48b2-9170-6a1af0fd1516 · outbound

This paper cites ACM SIGKDD Explorations Newsletter , volume=.

TopoFE: topology-aware LLM-guided Automated Feature Engineering ACM SIGKDD Explorations Newsletter , volume=

Reference 110

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no resolver link, observed 2026-07-31T23:58:36.854489Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:36.854489Z digest=sha256:a0167c56e48a5c31fe60c6badc3302dfb23efefb2091c37378f3c2f8958ddbb6

Observation 57d20554-ca82-45e8-9070-05f464a92fe8 · outbound

This paper cites Nature , year=.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Nature , year=

Reference 111

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no resolver link, observed 2026-07-31T23:58:36.944096Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-07-31T23:58:36.944096Z digest=sha256:25bce6a98ba42aecd4d02e28fe6df53f0c6bdef2441e82230ee8cbb31a60ea62

Observation 31a70abe-638a-44b8-ac51-e1f86e8d6c16 · outbound

This paper cites Forty-first International Conference on Machine Learning , year=.

TopoFE: topology-aware LLM-guided Automated Feature Engineering Forty-first International Conference on Machine Learning , year=

Reference 112

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no resolver link, observed 2026-07-31T23:58:37.009397Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:37.009397Z digest=sha256:10fd283585279a6a3700ddbcbd426f47a23c1c6e877230f391e4939ee2edda6f

Observation 3de1fe7a-7a0d-449f-81f7-38c85421306b · outbound

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

TopoFE: topology-aware LLM-guided Automated Feature Engineering Cresswell and Keyvan Golestan and Guangwei Yu and Anthony L

Reference 113

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no resolver link, observed 2026-07-31T23:58:37.065472Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:37.065472Z digest=sha256:66ab6c0e4c232d1c1507800bd7e5c94172bc1176081836026d0019e3b2cd2186

Pith citing papers

No inbound Pith citation observations are available.