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Paper Citation Record · LEDGER

TopoFE: topology-aware LLM-guided Automated Feature Engineering

As of 20 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 2026-08-20T06:33:59.587034+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:d049c884db24b0ef1943463f7dfd0a20e3bc854c91643cc86c1668d35ed6b428

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=sha256:528dde4cb8bfe29d7c27741480d247ca4d078921712b26db362fec86f0f3b7fd

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=sha256:040432432b9d2edea3e15b897348ac7dad13a37776cfc6acaecde60bfebf638d

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=sha256:12631629eb211470db0f2b7fa74dd78877dd40dbd2745b5769855f9c69ca5b54

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=sha256:3e9ebe3d83b06d16ae5942ae49184acc95bf76aae8ea4380530eeb126c125a4f

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=sha256:2726eab02815b46072267c1f26eb698382aacfaba0476d5d0836f938ea35e113

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=sha256:26242bc7a6c4a5d83f11c44271b5e805bc05614afb5f881dd679202d653a1a34

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=sha256:6a0a32cf08b1de4f49fa67c6c6ba5ede2acc6451d1779a9bbf328b8e8a8cadec

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=sha256:883802691b7d81a494c3c2a889763bffd4cb2d1ae64ab0cc573a31da9c18f919

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:b2a741c28ec20a3bf2110b48500200389f1261b1508b69507052d786d05e53fa

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=sha256:6b527ead82ab96d1bc42d50b7ca0409eb304f7149f91d740d7e4efe243a221a2

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=sha256:8ea5310b66529fd96ed592a6fa89b67383b5f0e971cf92385681c9e1f50f910f

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=sha256:95f82dafef2a7cb4fc99e58a2bba7e89e5e38131113e5e52c590e4a0fec2abcd

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=sha256:15c108e787f15f25b02c03dd7c47367d0a2aa5b2f8f760f377a892a933e53e16

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=sha256:6449e97b517e09348b4d5e816c5afc1275f623916aec2acd30df3a54c6d89e3f

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:d6f82b022d29263cc113ba8e6273a09f7eeacc0d72d389aeca1cd7859cf3bf01

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=sha256:017226eadc7773c9fdb7dc39b07507186355fe264b470059d480a12fe94a77a3

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=sha256:8f489ee5878ad47d58ae5f1d66fef3328746d5a0b958a5a6475c719d42d187d4

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:e702c836717e451beca8d2facf5a70b41aa1f41c1204c13f04030056b1c53917

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:d532c6f91712c79cc4d30cdad7c0d42fbb65bb3e03476769d5a65d18f8ee3788

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=sha256:9291a5b90ea070efef0a6af2da5262bbb4d8d3952bd2c5067498fe655e8027c4

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:d24eb5aa91a3a4796d55ed846cff3f390d390c2c58beede75dd855c5e43328d3

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=sha256:7d2f6a5e86e5e31654afbe53c802bb92206ebb2fc43198e8587d8b5cc0e7c04b

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=sha256:9c2217032a6b45e6e3d8a7cedbaca33776f1bfd16d3d45c6c3b4bc8911c13ca2

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=sha256:0cf3070f339439d9e683acc455d8c050be77c4c872c0b7c3e679791bf03a6ada

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:d3fc04decb835268d451a50a288a54656b42aba3b9fb121c26bb50dede2bc7a6

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:eb10f612af32d043380dd647d528581759ebdb7ac962b5d8be13de0952cc3f52

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=sha256:6d57e3997ed73ae7de62d30faa94eb61f5afa507449bf0b7a2545bd15cd61f48

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=sha256:3a06151c36bf7799ac53b1594009a4fd3c2e5af103400b5da341841da0c2bc0b

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=sha256:2a12c74e3203afd227a5ed07ca2975a8ce1ac79558441bbf967b28eb7017380b

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:e73f180afac84024ae3928e249fcbc55355e3dd59b0306bf14663284c83dd314

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=sha256:68b50ac8134265ed88b128ac9b5c0b6e76099a626afe37c2b18559d897ba330c

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=sha256:21186a3536db6d0cdb2e9b11776989d76eb190e75b4cfad3fc5d979b2bed9a77

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=sha256:401ae14ee26d63c989e80ee4c7c9aa7720d8f22e3412a116b389548bb5f7b5f7

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=sha256:7c243a17b02f33763d894a7d1c6bdc4b2215d2f68d5d3677436276706c906b3a

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=sha256:627b88d0702726b7d79fd540cfb6096be29440a5ba98336572d8b9f1130f8248

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=sha256:0078f59b7d5c899ba2543ab8b08989d0ed55d7bb1a832a03f007cce575eb4951

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:d5c4b686ff30528c3e99d26c35f2982f551b36f4c557b5428a956f1c9a15d060

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=sha256:337532e8cd473b6ec647997bb0763bae6fe8b4f393a49922727c2cb98e4c381e

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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no resolver link, observed 2026-07-31T23:58:32.279673Z

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source=arxiv_source observed=2026-07-31T23:58:32.279673Z digest=sha256:b96ca5d91d38f5e31899bbdb8d82e73f40d681e645eb2d084a2fb0c43fc9c3c5

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:32.424794Z digest=sha256:16f6c9c758e1fac62b4f6e3dcdcc361db647c9f4e0ce6c4426d310765692c8b5

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=sha256:4773711f443714bb880ba3e4be3632547ed4c4dcf72624f5cf991941c9f731bd

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-reported events for the cited work

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source=arxiv_source observed=2026-07-31T23:58:32.723287Z digest=sha256:5b54d70386c39af505f518cafc8c431a22f353da7f8f63f6ad131524d469b9c4

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=sha256:41840252b7ece90ec63c22966f0720dd50996a32505ef4551bf415ebb302ed07

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=sha256:46ea285db628be78d12969c233dea7c3e724cd912e9c298b7d7a56989aa5ab60

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=sha256:15e73de51dd83d4a0b26666e2af88a6f3505bfa5eaf7bbf7de7fa47ef29ecf16

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=sha256:026d1b0a08d5205e27ba0039b5b4eb48eaeb2d644ec69adf02b60c62bb4a4779

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-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:33.351116Z digest=sha256:9b5a4d13775e42f9c6429a3631d70cce63c28b9a12dd9dac210cce4928f85a49

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:33.494458Z digest=sha256:f8222d2e27d39960828b8f44c3952dcd21fa3699ae616fb94d87acb4eb05e441

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

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:33.622159Z digest=sha256:85eeb57cf5477565f2877e6c9f43d148a7532dc476410c393dea6dbeaaab22f1

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-reported events for the cited work

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source=arxiv_source observed=2026-07-31T23:58:33.740936Z digest=sha256:0a6d2f0531de483ebe325444d530d8abc594df87a72a5980ee3a13dc3096cbe2

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=sha256:0338555516e5c8bf0740a417285a2add0d96f7451500ee8b4bdd45d705c9c0ba

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:a2583ffcc1f8b9651f5b6f9860502d110ee02645b25c7b01d33921e6a53d6dd7

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=sha256:2414d10f4560f45b0d142f518706b42d675320cdc323a52a8de35ba912fcdc71

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=sha256:588d7cddc5dcc88629b9843735ce2f8aac3e66bc96c84bee3a7edbd722cf84bc

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=sha256:2da3ba00190b77426d26ec6fedd852533f398a051cc670960be3ea94f9dc21de

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:c975cd4c58c3d3b1dbfe265e74f12573315a37cac6969f5f89b67c232c00679b

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:da04897bff8cacc73a60d9dd5097b91436a532b368fb48973a8e98d84e48928f

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-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:34.385077Z digest=sha256:c78ea447f27db72e105fae779478ad4fcccfd9a754d1c2ef18132bcd783e0169

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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no resolver link, observed 2026-07-31T23:58:34.438559Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:34.438559Z digest=sha256:0d8adb287e3051694510e3d3b02fe9cd3424819b89b44784a240361ff0d76124

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:34.509226Z digest=sha256:788e0ab04da46920be79d344c1251553e602112bffc2bf99e902ece7fa9fc513

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:34.586735Z digest=sha256:cc48276ccb18e66a5d65e7537c3dc655eb50000f5700835462d689946d1f2a2e

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:b39f15c690acaa1546b7838402bc8c39c3fb99962146d38d0cdda356d7241d40

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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no resolver link, observed 2026-07-31T23:58:34.732416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:34.732416Z digest=sha256:9533c97c89575f557732a2feff6901495ce0245820425d19c0cb8c25a62e9bfa

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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no resolver link, observed 2026-07-31T23:58:34.810781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:34.810781Z digest=sha256:9b150bd1cf8e8fe44f7c3c0de981bb5e036673708768d448056e200eba652b19

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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no resolver link, observed 2026-07-31T23:58:34.864287Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:34.864287Z digest=sha256:a6c03735b6d16e4ad968bb313efefa8a63988084b6468c2dc6024536339e6d1c

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:34.946931Z digest=sha256:cdbba2a8874afcbb8478b59999558874a79b68e3be836d3f99c132e8513e75ae

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:34.995892Z digest=sha256:e385c43e6bbe4527b25ff27fe801354cc1d1452c19e8496ada2f46f1c97f63cb

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:35.036935Z digest=sha256:0a58f47d0e2071895458a7cc0950a8292a52a80c8f2bf2a463cc7d4bcd0f0445

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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source=arxiv_source observed=2026-07-31T23:58:35.114209Z digest=sha256:5f6dc58a58f0eba828ee294934f4e15ccd698906cc96a8229ccab4e1e470dcae

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=sha256:8659b1a3eb6260213a8c40f0dee9faae7b08e7ebf0a68b4fadab6f5e56f668ae

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:ce10333e3463cf1e077d3899b802e71cb8d05de09403c76ba6fc9787c3bf9c11

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:35.278450Z digest=sha256:3b4f9e327829ed354bd5dcf26b7012ed166f94a445af3c82e47cce1e8cc282e7

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=sha256:80f327dea351d87fd0e1b1c2b9f120568fb98e6f6a0136d5e02bb65dec093a4e

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=sha256:4ba707895ddf91b2cf73734f1b6215e4fcb6e69c9220a8d06c669abc5031bf05

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=sha256:1bfc29750093ffd9b09fd41179a5582d6af7678f69735028179fe085f4d08071

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-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:35.470651Z digest=sha256:955797059851fa9b5457e76ca5f232e8574c57c7da7cea722e3dd14627c30e2f

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=sha256:776119f4311372ba0c847a4063b66633a4c3e4dbdbffa263c0fa678ffc2e44e3

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=sha256:459172da8e81181b2c1ce4f414c6c0db604e003bb4bf4e656e7137a2eb312f15

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

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source=arxiv_source observed=2026-07-31T23:58:35.643072Z digest=sha256:d2055228319824ad99e505a4a97e56e789921289ad714b280d1e5680adb405b5

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=sha256:753f65c061da1126d326edf9a34803db01217693640d7c89c5abb2f97f7fe2af

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:a9e657740fa3bb4187b72276df992fe48d27d60aac67812dc882e2a2706d8f7f

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=sha256:39b11ba2845128f08f5b7d36ae9f3f3848d34afab03199e527f02ea3f664b9c1

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:a447f6bf3f6b8d22fa6d26906c5c685345e0ace9b81573178735d9bb4a55608d

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=sha256:8446649fa25ffb18e8d3d125056421a56d87aba6655781bd958ad15e55dd4384

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=sha256:68f19da67478d4bf437cc16463729fac857d55a22598dde3c128f0af9cb4d87e

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:be62b17eb9b2ef944f9baea64dd5a5154ac7286b88919a881a4c84157cdf4232

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:a53241ff28842828c76bc05d1ed726009e3eef89ab10624cfb6a61bb520b59d5

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:ef25c3a84f8bd04bbb7dabf9af8b0c20c2275ddda86746c124d19034f0f40807

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:b86246c0cee76b54feca71524ab9601e891f667abf7ab3394e91abe91d0c215b

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

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source=arxiv_source observed=2026-07-31T23:58:36.376148Z digest=sha256:3ff61cef17f7c30d1ac23d49a16400b22021f50f88ad224fc2b4e38d404ee3e7

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

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source=arxiv_source observed=2026-07-31T23:58:36.432257Z digest=sha256:adc8a86ff2281e43fc182695ab78a37b8b821a345639bc0e166c4b9458ad86c6

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

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source=arxiv_source observed=2026-07-31T23:58:36.514015Z digest=sha256:02fd6fc9df374678f6da1dd51d1ed6125b96e218f7e524e934f08d2a568fc717

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=sha256:988b878cb6cdf3d30612aba927d7d3f7bf68ec8370fba9d3a8395e8f1c0f980d

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:cb442b74bf84a8c2afa0ac0d202b9697936718a366979bc042ebe49b72b7b9cc

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=sha256:178d1397faba1b09b5a2356646fe353ced6a8e61fceb9721e7abecd59f8e48c8

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:58:36.854489Z digest=sha256:57205cda91804fd57905d8fe0a77d0a068b799dd4c0ff27ea098569572cbb703

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

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source=arxiv_source observed=2026-07-31T23:58:36.944096Z digest=sha256:870f113da5a0ffae80c66154c633e9317c792ecbca06bbe0477b9097698b777a

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=sha256:608adee1a0f8135c86bda549e859266ee115c1eb568dd27b57b2d898e1c6dc44

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

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source=arxiv_source observed=2026-07-31T23:58:37.065472Z digest=sha256:1b4ae767cc2ffb05dc873a4d90ea2cbe00c64850fb1394ccb9188c4d17e36473

Pith citing papers

No inbound Pith citation observations are available.