Paper Citation Record · LEDGER

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification

As of 20 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2505.05744.

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

pith.paper-citation-record.v1
2505.05744 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:05:12.287778Z

measured 38 of 38 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

38 of 38 outbound references displayed

verified exact0
verified fuzzy14
unresolved24
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 80398edc-3bc6-4a0c-a52e-0fefbe6aa4cd · outbound

This paper cites In: Pro- ceedings of the AAAI conference on artificial intelligence.

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification In: Pro- ceedings of the AAAI conference on artificial intelligence

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-15T23:05:12.154573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0cc1370-c6d5-4a67-abcf-35ae8fcb75c0 · outbound

This paper cites an unresolved cited work.

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-15T23:05:12.717762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 46e7633b-e16e-474f-a5cf-151eaa18f22b · outbound

This paper cites Gradient Boosting Neural Networks: GrowNet.

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification Gradient Boosting Neural Networks: GrowNet

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-15T23:05:12.162543Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e413310a-96cf-4ded-b1cb-4081128a93d7 · outbound

This paper cites SCARF: Self-Supervised Contrastive Learning using Random Feature Corruption.

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification SCARF: Self-Supervised Contrastive Learning using Random Feature Corruption

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-15T23:05:12.166859Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf87a1f0-2018-400e-a3d1-f23d0c21d362 · outbound

This paper cites In: International Conference on Learning Representations (2022).

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification In: International Conference on Learning Representations (2022)

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:05:12.707255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5a3e273b-c96f-43e7-aa68-e40e4eba4ead · outbound

This paper cites Machine learning45, 5–32 (2001).

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification Machine learning45, 5–32 (2001)

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T23:05:12.175277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 009ab8e7-177f-4960-a917-f06ccf35b1ad · outbound

This paper cites ReConTab: Regularized Contrastive Representation Learning for Tabular Data.

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification ReConTab: Regularized Contrastive Representation Learning for Tabular Data

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T23:05:12.179172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 277e6c10-cea5-4410-8b27-805d07bd1ec2 · outbound

This paper cites In: Proceedings of the 22nd acm sigkdd international conference on knowledge discovery and data mining.

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification In: Proceedings of the 22nd acm sigkdd international conference on knowledge discovery and data mining

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-15T23:05:12.182914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef7ee1ca-c06d-4d66-a0f2-23a6313f0ba0 · outbound

This paper cites Advances in Neural Information Processing Systems35, 11763–11784 (2022).

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification Advances in Neural Information Processing Systems35, 11763–11784 (2022)

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-15T23:05:12.186276Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c940a281-9a7d-401e-a0ed-cc2b2728803c · outbound

This paper cites In: 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE).

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification In: 2023 IEEE/ACM 45th International Conference on Software Engineering (ICSE)

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:05:12.680917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d907030e-5ccf-4d1a-af65-277d905a2f8d · outbound

This paper cites In: Proceedings of the 24th Meeting of the Special Interest Group on Discourse and Dialogue.

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification In: Proceedings of the 24th Meeting of the Special Interest Group on Discourse and Dialogue

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:05:12.671200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 826fdd27-b529-435b-a54e-dc7df25d4ad3 · outbound

This paper cites Advances in Neural Information Processing Systems34, 18932–18943 (2021).

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification Advances in Neural Information Processing Systems34, 18932–18943 (2021)

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T23:05:12.195101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c3fb2ae-b222-4faf-b6e3-0f7fdf9436d4 · outbound

This paper cites In: Statistical models in S, pp.

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification In: Statistical models in S, pp

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:05:12.656819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c7a01d9a-932a-4647-9454-8f5125cb8de2 · outbound

This paper cites In: Proceedings of 3rd international conference on document analysis and recognition.

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification In: Proceedings of 3rd international conference on document analysis and recognition

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:05:12.648004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0a9a9c3e-95b3-476c-b7e1-4717d53db1d8 · outbound

This paper cites In: The Eleventh International Conference on Learning Representations (2023).

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification In: The Eleventh International Conference on Learning Representations (2023)

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-15T23:05:12.205220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3583c11-91ac-4a48-9910-0f573ef2107a · outbound

This paper cites TabTransformer: Tabular Data Modeling Using Contextual Embeddings.

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification TabTransformer: Tabular Data Modeling Using Contextual Embeddings

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-15T23:05:12.208538Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f618998-70fb-4eef-bed0-6ab5436e37ff · outbound

This paper cites Advances in neural information processing systems34, 23928– 23941 (2021).

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification Advances in neural information processing systems34, 23928– 23941 (2021)

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:05:12.632934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8e69f24c-86f0-46f6-a9b0-209f55987b77 · outbound

This paper cites Advances in neural information processing systems30 (2017).

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification Advances in neural information processing systems30 (2017)

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:05:12.621937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7f7c5e3a-3b26-4514-9843-2852ea31c757 · outbound

This paper cites In: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining.

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification In: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:05:12.611861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b01ea2b0-e8ed-4e6a-8f30-e55819e941c3 · outbound

This paper cites an unresolved cited work.

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification Unresolved cited work

Reference 20

Resolution: unresolved; raw_fallback, observed 2026-08-15T23:05:12.601973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1b229efa-a193-4f07-ac06-f63862ffc518 · outbound

This paper cites Advances in neural information processing systems30 (2017).

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification Advances in neural information processing systems30 (2017)

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-15T23:05:12.225744Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9751436c-f539-4b99-824d-4a7fcd1160ca · outbound

This paper cites Circulation117(18), 2395–2399 (2008).

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification Circulation117(18), 2395–2399 (2008)

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T23:05:12.228786Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9c276bd-1e73-44c2-b3d7-eddc22e54d78 · outbound

This paper cites ACM Computing Surveys55(9), 1–35 (2023).

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification ACM Computing Surveys55(9), 1–35 (2023)

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-15T23:05:12.233192Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6569874-facf-41b6-b4fb-263ac1dc9546 · outbound

This paper cites an unresolved cited work.

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification Unresolved cited work

Reference 24

Resolution: unresolved; raw_fallback, observed 2026-08-15T23:05:12.577161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 396ea0b8-c739-46f9-a982-bb5aadbf9352 · outbound

This paper cites Decision Support Systems62, 22–31 (2014).

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification Decision Support Systems62, 22–31 (2014)

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-15T23:05:12.241421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3fd26ce7-7d79-4496-b5c5-dbabe4866240 · outbound

This paper cites In: Work- shop on Efficient Systems for Foundation Models@ ICML2023 (2023).

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification In: Work- shop on Efficient Systems for Foundation Models@ ICML2023 (2023)

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:05:12.561924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 00bf646d-86e0-4b8a-be80-ae8be46516d6 · outbound

This paper cites In: The Eleventh International Conference on Learning Representations (2023).

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification In: The Eleventh International Conference on Learning Representations (2023)

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:05:12.551777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0c196b53-a872-4966-b942-253d6aa74bed · outbound

This paper cites Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data.

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-15T23:05:12.253122Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c380513-b694-4787-997d-5bbe8720b5d7 · outbound

This paper cites Advances in neural information pro- cessing systems 31 (2018).

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification Advances in neural information pro- cessing systems 31 (2018)

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:05:12.439495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f07e8cc2-4cf2-4e81-bb22-e176743ed9ae · outbound

This paper cites TABLET: Learning From Instructions For Tabular Data.

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification TABLET: Learning From Instructions For Tabular Data

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-15T23:05:12.259874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6889b666-9840-4a95-b411-e32ca13b362e · outbound

This paper cites SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training.

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-15T23:05:12.263923Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd5e2f08-9016-40a6-8b12-515ea4f6b590 · outbound

This paper cites In: Pro- ceedings of the 28th ACM international conference on information and knowledge management.

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification In: Pro- ceedings of the 28th ACM international conference on information and knowledge management

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:05:12.429389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 53420d68-6932-494c-8bc7-35ce66fa5b46 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification LLaMA: Open and Efficient Foundation Language Models

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-15T23:05:12.271495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c318395-c856-42fd-a6e8-f8e9e6e4a2f8 · outbound

This paper cites In: Proceedings of the web conference 2021.

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification In: Proceedings of the web conference 2021

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-15T23:05:12.274666Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d03ae013-4273-4432-b3a0-b07e1b203a68 · outbound

This paper cites Emergent Abilities of Large Language Models.

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification Emergent Abilities of Large Language Models

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-15T23:05:12.277709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa4da3fe-7969-40aa-90b4-534fc983a5bd · outbound

This paper cites Advances in Neural Information Processing Systems35, 24824–24837 (2022).

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification Advances in Neural Information Processing Systems35, 24824–24837 (2022)

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-15T23:05:12.280813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1da77939-98a5-4481-8588-fd904658f092 · outbound

This paper cites Advances in Neural Information Processing Systems33, 11033–11043 (2020).

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification Advances in Neural Information Processing Systems33, 11033–11043 (2020)

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:05:12.408305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 903bcfa3-2c28-4b55-b9d2-98f09a724b16 · outbound

This paper cites In: The Eleventh International Conference on Learning Representations.

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification In: The Eleventh International Conference on Learning Representations

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:05:12.397000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

No inbound Pith citation observations are available.