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Paper Citation Record · LEDGER

TopoFE: topology-aware LLM-guided Automated Feature Engineering

As of 10 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 2026-08-10T06:31:04.303077+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=sha256:30d7c70bd5df5e808f9115e77b22c9e7215103074ada93a000cd74e118461e93

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=sha256:77653e8aab35fb9248c66816b8fda8a170e9f62eee6b683315965889feb3a847

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=sha256:1de90e37f9ee1e593b0d9ce6b68b89c0a061b27e0824b951a463806c94400143

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=sha256:03e8ce73128b9602724c168c38b83b553ea7bd7d0d66af8ae0c2b5093b4a4959

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=sha256:58f53c178331d2d7ad9177e78d08ddd7ca245eea7718b68887b2f7a6c5f93ff4

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=sha256:389700f94e0225efc991f1bc8038ca820ebdc0fe6ddd4dec767a4f73cdb64bf3

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=sha256:65f4031d9b65e02416f8998dcea35abc57653a6afcea31ecbd5e6a376e30f307

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:f24a0cda5ec9cc36f7a9703c4bacae950f3b318a3386a52f27413ad4947124d6

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:d0dbee5324ca9741219dd4c498c85b4b2238c89d89d76552a43058b60c9fdf4b

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=sha256:4a6d7213f5c212d23c8dda470cd5950db59ccfa299d83626d2435e48c4429f26

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=sha256:33d97730fb1285ff51279e4d97e76e1c834a67abe644d2d62a74fe545c859412

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=sha256:23e1aa3504c5136616083dddabb81d9e3fcba4ae6d28ba44f4a7e1a3d48d4736

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=sha256:8f489c1abbd4931ee5cc3b3c1d4f44166bc130b287a46bf80badc929664f1819

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:b295819364975897760a42bf8ed530d4ff22fb13464ece2d55103b3acf54fe9c

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=sha256:1ca1c9c1d86f2cc0518fb2cd65b0408ecbe2137b35f6d5701d1d0b29ed0fd5c9

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=sha256:5aafa35216e0a62564376d96357ac4956d034de147cf63536df84c85bd234674

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:eace676dc2d21b47f7bd4510b241e0d905f9aaf3ce3f68f502d5ee746bd26ee1

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=sha256:6b9c2e8966ea25ff8f2854d03506428b4b4fe45eef74e54eefd1426f74ff9942

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=sha256:09f90cc24cd2c5e144b95daf6e739fba7d883fdbe7edade751a40ff9a1a3d319

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=sha256:8e7abd6e15db39089556015a41441f915a197d147618e2f2dcad18e589a9dc69

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:d9952efdf05bef972e8b735310a4d3ef5a889b21369354ae9b415828b064970d

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=sha256:8296812c4ab939cfd5d5ec895c74ef0938102d87ff82cce871ebafa0371459c0

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=sha256:7f299808d092b3831dd9d7ee73136bc16a0a06e95e729e0665b14b508294440d

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=sha256:0cbc4f6910ba2da82ac85370fec94043c7d9f3c86a7be6c32e65e2723518b7c4

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:a61c8e9af29a740e3672b324b51687a44b6f2dd15ab500b45e3f5b8435a15025

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=sha256:23c6cc4de0e20c5a1ea1cf50e0334c90479198e5e49574f98dcffd6e0c1fd467

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:e4689b4d94158c015f62265ad871fb664f5d098b7d9049a9bf348b804a60a73e

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:e943ed83da177ab597e82351480e56bc6880d80ba511a7e53cafdadb69242529

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=sha256:1135845ace9e2b0c37075b94547307e557a73ea2f0c82abc259d06c4c9038463

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=sha256:7b8a1160d48f89370abce30d14e2d522804a9d73af416cc64001439f5cbe9a8d

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=sha256:829999a380e5e95b0d83453d3e55a876b447994a9e3964113931911d9d0ecc64

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=sha256:7c8ac843e23df2db486462ad5ef4d0abf4cfe7c2a2d583b085c3499a4e25d4fc

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=sha256:16c451440b349f871dd7a19c190f4fe15c6d328f521fe4a292b73416205aacf9

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=sha256:6418f0ddfad48b10260bf547af63a1ec551794f9634116b9e3ea153fc51f0e68

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:ce563ecec0e71bc71c7a684af4b641817ad859ef300de2c6d8b824738df254fa

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:a4071449367013d867a7f8db08a0058d61cb19aa1dfe49b5b9a8e5f62c3ca9e4

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:cf0a47f0afc20359e7042ba9f65d8b0750a77fd99392c7151169b65a19f4dc7e

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=sha256:0bc7eec759f2b0b5c1ba9787a54b162716570d7d39990ae909ffff42ac4eef9d

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:d238f0af0d19749f340f9d60556c345760a1467cc18e2543e9230baf89629bff

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:f5c07ad726433101e2f16b31a063a466d6a801ad75277b13add178bd136b4bab

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=sha256:98be0f2657006e2cf197a1c8b6c43563fa35cbbee3d422bde2e033a7f833dc9e

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=sha256:20e2b6ec670ff1db9cf037830a2a1141dde8f20d3ec41ff85905cdeeacecc974

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:fac55ebbb1a1c4cf2d8b99fdbd7ad838063ed639ff596e28a748c73c7c30720a

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=sha256:21c5706f6b8db60f5df726094195462a391308ee44ba24cd196ecdd42a3632d5

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=sha256:1873e853058c558a37d66a28749e01085158944b6cef2cb9a803563e4ec7eec6

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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no resolver link, observed 2026-07-31T23:58:33.125998Z

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source=arxiv_source observed=2026-07-31T23:58:33.125998Z digest=sha256:4a9b53ba2922e0196b4b8eaf43541ffa083c3e96922558cadc70d79aec19c009

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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source=arxiv_source observed=2026-07-31T23:58:33.252678Z digest=sha256:1171ca059b5be93e8d83cc83cd8b6b1e16625cc082d42c85fd68b4e473471da0

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:33.351116Z digest=sha256:f2ea48cc702a561cdf9cf711fb37b759a6fbd3a2c6720d621f48525e68af2a23

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=sha256:6ec98221d69d2802aa782cb767ed3b7c34c13fa9210d8b4e8d6daf133c03208c

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-reported events for the cited work

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source=arxiv_source observed=2026-07-31T23:58:33.622159Z digest=sha256:ceb6e7696fb8bb2fe5ffe40a831ee47f81c4f487a028db737d2861a8a3686088

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:ecfd775b99a6f8fe239f82b45d841205517f15bf3f19aeeafe203f95f47464d5

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:e12249c42f876a10da751d4c6000a04ed6748bc9ef6f8637c3bc0bb6e9f239d6

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=sha256:25cd3845de8c3b1eb56a6f266daace655c57a6233c4042a80ea9f3320a9f453e

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=sha256:2559b8e0c1908ef672cb9c3961688c700e5a8cca5abf246b8fd0dc7f0b2a0106

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=sha256:8dc9ae0881467cd043428eddad04020c7c1a71d8ed838cdc9cc3d78c8d869b75

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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source=arxiv_source observed=2026-07-31T23:58:34.187330Z digest=sha256:09cc1f66085d77976f08681979b97b5c16838f5152b3ac1d2698cd66f7e410b7

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=sha256:8cc006fd6de5fe06e3ebd1f53bfd7b822c16d0d3f6c8d89f2ef5835d7ea507bb

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:34.313353Z digest=sha256:9e44fdc16e5f6d53f5926f99f7e5221a9de61265dda0eb65212ffc0793052e00

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:34.385077Z digest=sha256:7dda59e6d0cc1d6c18af62614e4444c84116cb3fbd3aa6e0d8d658198507b809

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:34.438559Z digest=sha256:34821285b558752284485a2c51f3b1b1efc2f2c0e935302ed3f9ee3695b14696

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:d5563e0d14bb437a5d05246413f31b4b82b68e15b0db83aa740ba0e47bdfb589

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:f228376f9df1cad9d7a1f78227d727af5795698a586d7218b9bc7c30aeb257e1

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:d17d0c77417c187564890f2094324950313e8c40b9437aa6b9b9515e32521afb

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:fa3fe366591282628baa9cf2da77247945c42c018a2e000aababaf24c64b4543

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=sha256:6d5849b3597753614bda440f4aa0fae2cd883d9910819a398bf9e20d62446e2d

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=sha256:5081fe3477f7fdd7e640d11430f9b109a5f9019165510b2120f057b99357cda8

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=sha256:1c4c8b8fecda3ea1a8f5880d540ab43cbb4da21d7af858b7d094e535e6ed67b7

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=sha256:9fbdf0f37dee406797a1cf198cfdaa123ce755baca4f068f431cc642a96c932d

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:d9c4368b5bf42b5bd78dd06e5ed4e119c787ba1b7bff38bef6eb55e519036a63

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=sha256:501d4cb1a4b4088b3f155efed44e2dc5d45561de111e4485b9ad0f9c5546206f

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=sha256:77a5937d810cb64ae5f1a0818101dd4ce3dc8391f86d5c0dc260017796a0f84e

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:35.219017Z digest=sha256:8375d5b5373b8043622ada369984f96fad7e04c853257677b6cc13deabee69da

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=sha256:0ea81d45c02881b689342fd6bca6dfc37bbab84146897bc8b07b8aa4c8076ea4

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=sha256:29d946a32362ea69a3377363621fb84b2fc7f3fb2c3f879c10ad09e670e6e5f4

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=sha256:67939917f042cc3a109d8655234b66a72f401545aa1da41c13e4e7a40aa322e5

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=sha256:485eef0e21f168bb8fb8d96bf8e1da03b282a1fa8ea8327ec25e92b9f33689eb

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=sha256:1ae205c4b0c1a6521952855cd30dec82b5fd466d093976f0c172a23be9bf044c

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=sha256:003c3b993d5055b24c90fd2512106390eed21a525f23d150add9eef83918d6fb

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=sha256:0325c6ea1416c39b033295e0a4c5ae0187175d22880ad1b49c7c434dc4c11007

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=sha256:5a1aaeafb31f0652e75e63e7092f704536778257780cd7f8fe55cf3a086c2fb4

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=sha256:91f2d7f64c8a9d76e8ec1904e74c07857ccb987ab1ccdd6306d870f96beba033

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=sha256:4a2ad505628213e3a05f1ea58efb0a9b6cdda3437ec0b3342d5b543e927fa688

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=sha256:085b86bb234276cbdb683611e7215ef5ad71b909a8b8301e3b12a526855de60b

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:e7727190a45f094e824f2e186a1d91961ce9d666139d2f82e4120deeb6d6c838

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=sha256:8caeea971e9ce1a0d6335e480ddb5060f42f52ecd15ea6d12fbd236f1a5b8be1

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

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source=arxiv_source observed=2026-07-31T23:58:36.045689Z digest=sha256:2e3361cfe63a8768e19d76d124fbd541f948364976dfb1b13abc6aca3a424547

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

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source=arxiv_source observed=2026-07-31T23:58:36.105184Z digest=sha256:7d82b0e4e4100d4e0e15c6aa0a5cf1c9f2c030d44462febf92915b79d806eb2e

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:e7318b6ee105fac329d3fea3e4fcc3963d5b624511cb8d24f8d1b34b44ea8a69

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

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source=arxiv_source observed=2026-07-31T23:58:36.263252Z digest=sha256:02a5a79fdea06b955157710b46036df06895847c78d029f1f54bdab71b7a17c8

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

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source=arxiv_source observed=2026-07-31T23:58:36.331742Z digest=sha256:83d0797f5533f31ead19ee3725abc4b3b1ef57774d6e9fb2c3f15912b65d3199

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=sha256:4f4f1376e12341b4ac13d1ffb590547475641e23f3487a393faf2e34e9d1f4e4

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=sha256:6e3888946b2439ffe965393637713f197afc251699322e74464cfac08d952e7e

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

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source=arxiv_source observed=2026-07-31T23:58:36.514015Z digest=sha256:998b0f752c80a88b958f2d247664cd23dc7d718b86d3f5242ffcfc3795693d06

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

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source=arxiv_source observed=2026-07-31T23:58:36.571134Z digest=sha256:14ddeeb63b88ca1abaa4506d97f3500d5075672056fb3c70af3e45b0fd8e0798

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:cebc9eafabb1bb25d676e9433df533c8a00dfb8e8f0c4faf118b9f786ac8fffc

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

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source=arxiv_source observed=2026-07-31T23:58:36.739384Z digest=sha256:d8a5a6048c1420bdf47fe773d42bf643011b9f25824f0826b7541bf7d26c3124

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:aec0d2fad5602aeed5dea24bd2e2c77b0ce8736595ee0659c7ed41953d5ed13d

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=sha256:4706c17a1cd4ae13228d7e6693ac8b0793c20401d043bd6c77c725cf439327b3

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:b3faf3b46b61925b1e068f89995e645997f87d9f9fff6ba1abe3f9766ba3fdde

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=sha256:350d7229b9fbc69d220f1cb19fccefd331d42274eaba6f3bc41223c71e6fbc8f

Pith citing papers

No inbound Pith citation observations are available.