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Paper Citation Record · LEDGER

Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data

As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2412.16243.

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

pith.paper-citation-record.v1
2412.16243 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T06:59:14.626274Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T07:04:21.532153Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation b6e713f0-8d1b-4438-a016-38e5aa82f808 · inbound

MultiModalPFN: Extending Prior-Data Fitted Networks for Multimodal Tabular Learning cites this paper.

MultiModalPFN: Extending Prior-Data Fitted Networks for Multimodal Tabular Learning Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data

Reference 58

Resolution
verified exact
arxiv_id, observed 2026-05-15T20:11:34.282727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T20:11:22.146641Z digest=sha256:d3533065c028803ffcc70071d7f247e86c923e3594028260d6367f7503ca1160

Observation 6399dd01-cfb0-4982-9ea6-b316869f8382 · inbound

VT-Bench: A Unified Benchmark for Visual-Tabular Multi-Modal Learning cites this paper.

VT-Bench: A Unified Benchmark for Visual-Tabular Multi-Modal Learning Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:56:27.032029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=arxiv_source observed=2026-05-12T01:31:52.536354Z digest=sha256:2c4e9b227d1c5a09bde8758d125b7fd96e469fa68ced9722fe1a4066dd1ff83e

Observation 29358c85-fa39-46ff-bc69-c403ceca74f2 · inbound

VT-Bench: A Unified Benchmark for Visual-Tabular Multi-Modal Learning cites this paper.

VT-Bench: A Unified Benchmark for Visual-Tabular Multi-Modal Learning Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-05-21T00:33:52.793869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=arxiv_source observed=2026-05-21T00:31:07.580063Z digest=sha256:75a9f8875ef255b5892f897fefbe4ef43cde07ed039cb6e523be869003d6da1b

Observation 00bc0266-ace6-4ef3-9f9a-0f193817ce35 · inbound

MulTaBench: Benchmarking Multimodal Tabular Learning with Text and Image cites this paper.

MulTaBench: Benchmarking Multimodal Tabular Learning with Text and Image Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data

Reference 98

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T05:51:24.761694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T04:53:40.505699Z digest=sha256:915c890272ed6fcacf06b197cca50762d5442cf53d13ade8c2451cfe354be448

Observation 4b6447a8-0f1d-4304-b2c6-a18ccbe7be48 · inbound

Beyond IID: How General Are Tabular Foundation Models, Really? cites this paper.

Beyond IID: How General Are Tabular Foundation Models, Really? Bag of Tricks for Multimodal AutoML with Image, Text, and Tabular Data

Reference 117

Resolution
verified exact
arxiv_id, observed 2026-06-30T07:04:21.534599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-30T06:59:14.626274Z digest=sha256:73b38f8d87ded1247e00cd191f30a77eb5a831e642407ac24072b08bc4ffea27