Paper Citation Record · LEDGER

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models

As of 20 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 1 inbound Pith citation observation for arXiv:2606.04485.

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

pith.paper-citation-record.v1
2606.04485 v2

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-28T07:00:24.074608Z

measured 35 of 35 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-14T00:36:05.289408Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

34 of 34 outbound references displayed

verified exact2
verified fuzzy0
unresolved27
parse uncertain0
malformed identifier0
metadata mismatch5

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 29747d11-78ab-42dd-b60a-aef6b9080609 · outbound

This paper cites Scaling Learning Algorithms Towards.

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models Scaling Learning Algorithms Towards

Reference 1

Resolution: unresolved; no resolver link, observed 2026-06-28T07:00:24.074608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9893eb70-43f5-445c-87f1-42316a91cf2f · outbound

This paper cites Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics , pages =.

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics , pages =

Reference 2

Resolution: unresolved; no resolver link, observed 2026-06-28T07:00:24.074608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 526a075c-d7b0-4b97-8271-47eae6317dac · outbound

This paper cites Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification , year=.

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification , year=

Reference 3

Resolution: unresolved; no resolver link, observed 2026-06-28T07:00:24.074608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00ddbe27-d5cb-4665-b79f-f0062819057b · outbound

This paper cites and Osindero, Simon and Teh, Yee Whye , journal =.

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models and Osindero, Simon and Teh, Yee Whye , journal =

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-28T07:00:24.074608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 324608df-75d4-4676-b7db-3f32b116244a · outbound

This paper cites 2016 , publisher=.

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models 2016 , publisher=

Reference 5

Resolution: unresolved; no resolver link, observed 2026-06-28T07:00:24.074608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 526a76f7-8aad-4475-83fa-3fac2d09ee1d · outbound

This paper cites Nature , volume =.

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models Nature , volume =

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-28T07:00:24.074608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c6999a53-dfb4-48d8-b02b-b4fe537a5650 · outbound

This paper cites TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second.

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second

Reference 7

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T07:16:45.166866Z

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 b533bb8c-6763-4aef-b9cd-2aa0f4925e26 · outbound

This paper cites Proceedings of the 42nd International Conference on Machine Learning (ICML) , year =.

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models Proceedings of the 42nd International Conference on Machine Learning (ICML) , year =

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-28T07:00:24.074608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65c55225-5e19-4b0c-9c5b-f0ee03c5a301 · outbound

This paper cites 2016 , doi =.

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models 2016 , doi =

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-28T07:00:24.074608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e00c8f44-ae83-45ac-ada7-eba9920027f0 · outbound

This paper cites Advances in Neural Information Processing Systems 30 (NeurIPS) , pages =.

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models Advances in Neural Information Processing Systems 30 (NeurIPS) , pages =

Reference 10

Resolution: unresolved; no resolver link, observed 2026-06-28T07:00:24.074608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6bb993a8-aa6e-411d-9d0a-d50ca89b6a5d · outbound

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

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models Advances in neural information processing systems , volume=

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-28T07:00:24.074608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e20cc773-ad62-4442-996d-00a9aa8bee89 · outbound

This paper cites Why do tree-based models still outperform deep learning on tabular data?.

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models Why do tree-based models still outperform deep learning on tabular data?

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-07-02T07:16:45.153013Z

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 517ed565-4884-4b80-a8df-83f67b11fa0c · outbound

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

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models TabTransformer: Tabular Data Modeling Using Contextual Embeddings

Reference 13

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T07:16:45.156148Z

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 ff1732b0-f965-44ca-8986-5e8781053a14 · outbound

This paper cites Advances in Neural Information Processing Systems 34 (NeurIPS) , year =.

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models Advances in Neural Information Processing Systems 34 (NeurIPS) , year =

Reference 14

Resolution: unresolved; no resolver link, observed 2026-06-28T07:00:24.074608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5be998e2-f76f-42da-a5d8-6c66e9b7f547 · outbound

This paper cites Advances in Neural Information Processing Systems 35 (NeurIPS) , pages =.

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models Advances in Neural Information Processing Systems 35 (NeurIPS) , pages =

Reference 15

Resolution: unresolved; no resolver link, observed 2026-06-28T07:00:24.074608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d8e9ada6-9198-4f01-97c5-2a627bcc1418 · outbound

This paper cites Complex Systems , volume =.

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models Complex Systems , volume =

Reference 16

Resolution: unresolved; no resolver link, observed 2026-06-28T07:00:24.074608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95055eb8-fa72-421a-88f2-68f9f4e2dbfc · outbound

This paper cites Neural Computation , volume =.

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models Neural Computation , volume =

Reference 17

Resolution: unresolved; no resolver link, observed 2026-06-28T07:00:24.074608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 614eb770-eb9d-4573-9eda-29f995dccac5 · outbound

This paper cites 2018 , publisher=.

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models 2018 , publisher=

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-28T07:00:24.074608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8746fdb-69f7-463d-9979-3c25444c769f · outbound

This paper cites 2006 , publisher =.

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models 2006 , publisher =

Reference 19

Resolution: unresolved; no resolver link, observed 2026-06-28T07:00:24.074608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0d3d9ef-298e-4608-a132-1d14c2e4e8cb · outbound

This paper cites Advances in Neural Information Processing Systems 20 (NeurIPS) , pages =.

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models Advances in Neural Information Processing Systems 20 (NeurIPS) , pages =

Reference 20

Resolution: unresolved; no resolver link, observed 2026-06-28T07:00:24.074608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7878d60c-4124-48d5-b06b-e2075d339414 · outbound

This paper cites an unresolved cited work.

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models Unresolved cited work

Reference 21

Resolution: unresolved; no resolver link, observed 2026-06-28T07:00:24.074608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 70418ba7-dfff-43f2-a789-4dfe1f5738ff · outbound

This paper cites MET: Masked Encoding for Tabular Data.

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models MET: Masked Encoding for Tabular Data

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-07-02T07:16:45.159892Z

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 d2626001-2939-43e6-90de-92194bcebf28 · outbound

This paper cites Advances in Neural Information Processing Systems 33 (NeurIPS) , year =.

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models Advances in Neural Information Processing Systems 33 (NeurIPS) , year =

Reference 23

Resolution: unresolved; no resolver link, observed 2026-06-28T07:00:24.074608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3b5797a0-2e26-4017-89c4-e70062bd0d4d · outbound

This paper cites Limix: Unleashing structured- data modeling capability for generalist intelligence.

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models Limix: Unleashing structured- data modeling capability for generalist intelligence

Reference 24

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T07:16:45.135757Z

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 3eb2166d-81e1-467c-891f-a6a3062aaf08 · outbound

This paper cites Bayan and Goldstein, Tom , journal=.

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models Bayan and Goldstein, Tom , journal=

Reference 25

Resolution: unresolved; no resolver link, observed 2026-06-28T07:00:24.074608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation afa1bb8f-184c-41ad-991f-652b8193b164 · outbound

This paper cites Proceedings of the AAAI Conference on Artificial Intelligence , year=.

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models Proceedings of the AAAI Conference on Artificial Intelligence , year=

Reference 26

Resolution: unresolved; no resolver link, observed 2026-06-28T07:00:24.074608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40d2e5f6-66d3-4414-aaa6-b9f741300303 · outbound

This paper cites 2019 , eprint=.

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models 2019 , eprint=

Reference 27

Resolution: unresolved; no resolver link, observed 2026-06-28T07:00:24.074608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ac848e0-0b66-4854-89f7-13789d1650d1 · outbound

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

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models Advances in neural information processing systems , volume=

Reference 28

Resolution: unresolved; no resolver link, observed 2026-06-28T07:00:24.074608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b04a2056-488e-4f4c-8f09-79eca14edc49 · outbound

This paper cites 2026 , eprint=.

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models 2026 , eprint=

Reference 29

Resolution: unresolved; no resolver link, observed 2026-06-28T07:00:24.074608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 78a99176-4826-46b7-b457-d389527eed0e · outbound

This paper cites arXiv e-prints , pages=.

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models arXiv e-prints , pages=

Reference 30

Resolution: unresolved; no resolver link, observed 2026-06-28T07:00:24.074608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 388c6986-2ae6-4a97-9b3c-1241e8fe9476 · outbound

This paper cites OpenML Benchmarking Suites.

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models OpenML Benchmarking Suites

Reference 31

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T07:16:45.138956Z

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 e11f4e01-455d-45d7-9cb5-82215a327f97 · outbound

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

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models Advances in Neural Information Processing Systems , volume=

Reference 32

Resolution: unresolved; no resolver link, observed 2026-06-28T07:00:24.074608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ae0c36f-2b83-4289-9243-bcc12513bb96 · outbound

This paper cites TabArena: A Living Benchmark for Machine Learning on Tabular Data.

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models TabArena: A Living Benchmark for Machine Learning on Tabular Data

Reference 33

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T07:16:45.144519Z

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 11fb1301-b5e0-4dfa-a2bb-3637430f8034 · outbound

This paper cites AutoML Conference 2023 (Workshop) , year=.

LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models AutoML Conference 2023 (Workshop) , year=

Reference 34

Resolution: unresolved; no resolver link, observed 2026-06-28T07:00:24.074608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 9829726b-630c-442f-9867-18341e69d44e · inbound

TabLoRA: Parameter-Efficient Low-Rank Ensemble Learning for Large-Scale Tabular Data cites this paper.

TabLoRA: Parameter-Efficient Low-Rank Ensemble Learning for Large-Scale Tabular Data LimiX-2M: Mitigating Low-Rank Collapse and Attention Bottlenecks in Tabular Foundation Models

Reference 43

Resolution: unresolved; no resolver link, observed 2026-07-14T00:36:05.289408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.