Paper Citation Record · LEDGER

OpenRFM: Dissecting Relational In-Context Learning

As of 7 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 2 inbound Pith citation observations for arXiv:2606.04320.

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

pith.paper-citation-record.v1
2606.04320 v1

Coverage vector

measured 61 of 61 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-28T07:37:38.063200Z

measured 63 of 63 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T08:36:02.132826Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

61 of 61 outbound references displayed

verified exact14
verified fuzzy0
unresolved42
parse uncertain0
malformed identifier2
metadata mismatch3

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 45b8f57d-9a68-44d8-8bca-c74e3abb698f · outbound

This paper cites What learning algorithm is in-context learning? Investigations with linear models.

OpenRFM: Dissecting Relational In-Context Learning What learning algorithm is in-context learning? Investigations with linear models

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b13f18c1-4e26-4320-8ca8-b320422216a2 · outbound

This paper cites Holographic node representations: Pre-training task-agnostic node embeddings.

OpenRFM: Dissecting Relational In-Context Learning Holographic node representations: Pre-training task-agnostic node embeddings

Reference 2

Resolution: unresolved; no resolver link, observed 2026-06-28T07:37:38.063200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation beca206b-0d37-40f0-8208-8f0cf41f77bc · outbound

This paper cites Data distributional proper- ties drive emergent in-context learning in transformers.

OpenRFM: Dissecting Relational In-Context Learning Data distributional proper- ties drive emergent in-context learning in transformers

Reference 3

Resolution: unresolved; no resolver link, observed 2026-06-28T07:37:38.063200Z

Source-reported events for the cited work

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Observation ba165099-d695-43cf-9997-9de85913e992 · outbound

This paper cites an unresolved cited work.

OpenRFM: Dissecting Relational In-Context Learning Unresolved cited work

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-28T07:37:38.063200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0920b8bb-fdbc-456b-ac10-d4f4c09bbb67 · outbound

This paper cites RelGNN: Composite message passing for relational deep learning.

OpenRFM: Dissecting Relational In-Context Learning RelGNN: Composite message passing for relational deep learning

Reference 5

Resolution: unresolved; no resolver link, observed 2026-06-28T07:37:38.063200Z

Source-reported events for the cited work

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Observation d985fe98-aa56-4abf-bcfa-1702ba97e22d · outbound

This paper cites Chen and C.

OpenRFM: Dissecting Relational In-Context Learning Chen and C

Reference 6

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T07:41:45.394765Z

Source-reported events for the cited work

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Observation 5de70ff5-aa43-4bd5-af0f-26acb1e199d8 · outbound

This paper cites AutoG: Towards automatic graph construction from tabular data.

OpenRFM: Dissecting Relational In-Context Learning AutoG: Towards automatic graph construction from tabular data

Reference 7

Resolution: unresolved; no resolver link, observed 2026-06-28T07:37:38.063200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc8b7ab2-787f-4832-8fc3-624642dd98b0 · outbound

This paper cites Re- latron: Automating relational machine learning over relational databases.

OpenRFM: Dissecting Relational In-Context Learning Re- latron: Automating relational machine learning over relational databases

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-28T07:37:38.063200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9420a7f4-70cf-4c05-a9f1-803f08205300 · outbound

This paper cites On lazy training in differentiable program- ming.

OpenRFM: Dissecting Relational In-Context Learning On lazy training in differentiable program- ming

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-28T07:37:38.063200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation deac794b-7cc7-4f63-9f53-57d9309ac686 · outbound

This paper cites RDB2G-Bench: A comprehensive benchmark for automatic graph modeling of relational databases.

OpenRFM: Dissecting Relational In-Context Learning RDB2G-Bench: A comprehensive benchmark for automatic graph modeling of relational databases

Reference 10

Resolution: unresolved; no resolver link, observed 2026-06-28T07:37:38.063200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0573ff7c-06bc-4816-87fc-f6252d018c04 · outbound

This paper cites Learning posterior predictive distributions for node classification from synthetic graph priors.

OpenRFM: Dissecting Relational In-Context Learning Learning posterior predictive distributions for node classification from synthetic graph priors

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-28T07:37:38.063200Z

Source-reported events for the cited work

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Observation 3ab57ecc-0c06-4ccd-86fa-db9075956acd · outbound

This paper cites Codd , title =.

OpenRFM: Dissecting Relational In-Context Learning Codd , title =

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-06-28T07:41:45.389889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 99af0941-f30e-4a1c-b967-e5497431c6a1 · outbound

This paper cites Kanatsoulis, Rishi Puri, Matthias Fey, and Jure Leskovec.

OpenRFM: Dissecting Relational In-Context Learning Kanatsoulis, Rishi Puri, Matthias Fey, and Jure Leskovec

Reference 13

Resolution: unresolved; no resolver link, observed 2026-06-28T07:37:38.063200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08ae370d-40cd-4ddc-b04a-71a7209755d8 · outbound

This paper cites Turning Tabular Foundation Models into Graph Foundation Models.

OpenRFM: Dissecting Relational In-Context Learning Turning Tabular Foundation Models into Graph Foundation Models

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-07-02T06:06:41.431805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6f0eb500-a235-4d7f-a4df-ce7f1ba74f78 · outbound

This paper cites GraphPFN: A prior-data fitted graph foundation model.

OpenRFM: Dissecting Relational In-Context Learning GraphPFN: A prior-data fitted graph foundation model

Reference 15

Resolution: unresolved; no resolver link, observed 2026-06-28T07:37:38.063200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 90de1ce2-4426-40a7-a69f-314e6a99a247 · outbound

This paper cites Position: Relational deep learning – graph representation learning on relational databases.

OpenRFM: Dissecting Relational In-Context Learning Position: Relational deep learning – graph representation learning on relational databases

Reference 16

Resolution: unresolved; no resolver link, observed 2026-06-28T07:37:38.063200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 78183775-48d9-45d2-8133-991b0784632f · outbound

This paper cites KumoRFM: A foundation model for in-context learning on relational data.

OpenRFM: Dissecting Relational In-Context Learning KumoRFM: A foundation model for in-context learning on relational data

Reference 17

Resolution: unresolved; no resolver link, observed 2026-06-28T07:37:38.063200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31db0d47-b8b6-4d4c-b065-8a8dabe39428 · outbound

This paper cites Towards foun- dation models for knowledge graph reasoning.

OpenRFM: Dissecting Relational In-Context Learning Towards foun- dation models for knowledge graph reasoning

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-28T07:37:38.063200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c0e7b50-3bc4-4488-ad3b-7d11d3566d63 · outbound

This paper cites RelBench v2: A large-scale benchmark and repository for relational data.

OpenRFM: Dissecting Relational In-Context Learning RelBench v2: A large-scale benchmark and repository for relational data

Reference 19

Resolution: unresolved; no resolver link, observed 2026-06-28T07:37:38.063200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9f0c8ce6-303c-436f-a2ef-16da23fb2ccd · outbound

This paper cites Understanding emergent in-context learning from a kernel regression perspective.Transactions on Machine Learning Research (TMLR), 2025.

OpenRFM: Dissecting Relational In-Context Learning Understanding emergent in-context learning from a kernel regression perspective.Transactions on Machine Learning Research (TMLR), 2025

Reference 20

Resolution: unresolved; no resolver link, observed 2026-06-28T07:37:38.063200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84574cb0-79c7-4d59-90fb-780d2d5d3e05 · outbound

This paper cites Understanding in-context learning via supportive pretraining data.

OpenRFM: Dissecting Relational In-Context Learning Understanding in-context learning via supportive pretraining data

Reference 21

Resolution: unresolved; no resolver link, observed 2026-06-28T07:37:38.063200Z

Source-reported events for the cited work

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Observation 26e862e1-a5fa-4469-a506-292033155af6 · outbound

This paper cites Holland, Kathryn Blackmond Laskey, and Samuel Leinhardt.

OpenRFM: Dissecting Relational In-Context Learning Holland, Kathryn Blackmond Laskey, and Samuel Leinhardt

Reference 22

Resolution: verified exact; doi, observed 2026-06-28T07:41:45.402706Z

Source-reported events for the cited work

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Observation 269d310f-707d-4f29-855f-855d562145b3 · outbound

This paper cites Accurate predictions on small data with a tab- ular foundation model.Nature, 637(8045):319–326.

OpenRFM: Dissecting Relational In-Context Learning Accurate predictions on small data with a tab- ular foundation model.Nature, 637(8045):319–326

Reference 23

Resolution: verified exact; doi, observed 2026-06-28T07:41:45.400855Z

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Observation 21530731-5102-4497-946b-f223aecd28a9 · outbound

This paper cites KumoRFM-2: Scaling foundation models for relational learning.

OpenRFM: Dissecting Relational In-Context Learning KumoRFM-2: Scaling foundation models for relational learning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-06-28T07:37:38.063200Z

Source-reported events for the cited work

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Observation ea6f0f78-0432-419a-b497-ce3516f64028 · outbound

This paper cites IEEE-CIS fraud de- tection.

OpenRFM: Dissecting Relational In-Context Learning IEEE-CIS fraud de- tection

Reference 25

Resolution: unresolved; no resolver link, observed 2026-06-28T07:37:38.063200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d408a95a-86e5-4fbd-bb0a-120cf0bca6da · outbound

This paper cites Neural tangent kernel: Convergence and generalization in neural networks.

OpenRFM: Dissecting Relational In-Context Learning Neural tangent kernel: Convergence and generalization in neural networks

Reference 26

Resolution: unresolved; no resolver link, observed 2026-06-28T07:37:38.063200Z

Source-reported events for the cited work

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Observation fc2efb15-1bf5-4a18-a71d-b6709affe089 · outbound

This paper cites Linkage and autocorrelation cause feature selection bias in relational learning.

OpenRFM: Dissecting Relational In-Context Learning Linkage and autocorrelation cause feature selection bias in relational learning

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-06-28T07:41:45.386842Z

Source-reported events for the cited work

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Observation 9dd577f3-4fb8-4669-833a-13d699d318a0 · outbound

This paper cites MIMIC-III, a freely accessible critical care database.

OpenRFM: Dissecting Relational In-Context Learning MIMIC-III, a freely accessible critical care database

Reference 28

Resolution: verified exact; doi, observed 2026-06-28T07:41:45.394723Z

Source-reported events for the cited work

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Observation dd672585-2f12-44c2-9b9a-1b3c977472fb · outbound

This paper cites Deep feature synthesis: Towards automating data science endeavors.

OpenRFM: Dissecting Relational In-Context Learning Deep feature synthesis: Towards automating data science endeavors

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-06-28T07:41:45.376837Z

Source-reported events for the cited work

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Observation d2f79195-690f-46cc-9e10-db728a46fc3a · outbound

This paper cites & Newman, M.

OpenRFM: Dissecting Relational In-Context Learning & Newman, M

Reference 30

Resolution: verified exact; doi, observed 2026-06-28T07:41:45.398600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 364b767c-726c-4892-8704-7ca160f5f5c3 · outbound

This paper cites Lightgbm: A highly efficient gradient boosting decision tree.

OpenRFM: Dissecting Relational In-Context Learning Lightgbm: A highly efficient gradient boosting decision tree

Reference 31

Resolution: unresolved; no resolver link, observed 2026-06-28T07:37:38.063200Z

Source-reported events for the cited work

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Observation e1be4d50-6cf9-4330-a4f0-0913d0fad4f1 · outbound

This paper cites Predictive Query Language: A Domain-Specific Language for Predictive Modeling on Relational Databases.

OpenRFM: Dissecting Relational In-Context Learning Predictive Query Language: A Domain-Specific Language for Predictive Modeling on Relational Databases

Reference 32

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Observation 04aeca26-776c-45f1-a789-ef6c613a350e · outbound

This paper cites PluRel: Synthetic data unlocks scaling laws for rela- tional foundation models.

OpenRFM: Dissecting Relational In-Context Learning PluRel: Synthetic data unlocks scaling laws for rela- tional foundation models

Reference 33

Resolution: unresolved; no resolver link, observed 2026-06-28T07:37:38.063200Z

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Observation 8fc7c5e3-2ee2-44db-a2a9-7caad314fe80 · outbound

This paper cites Position: Graph foundation models are already here.

OpenRFM: Dissecting Relational In-Context Learning Position: Graph foundation models are already here

Reference 34

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Observation a4fc22d3-14cb-4753-a992-5c336fb77230 · outbound

This paper cites Transformers can do bayesian inference.

OpenRFM: Dissecting Relational In-Context Learning Transformers can do bayesian inference

Reference 35

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Source-reported events for the cited work

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Observation 83b69c3f-0e2a-4cd0-9e25-9c81d66dff92 · outbound

This paper cites Statistical foundations of prior-data fitted networks.

OpenRFM: Dissecting Relational In-Context Learning Statistical foundations of prior-data fitted networks

Reference 36

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Source-reported events for the cited work

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Observation 385fffb2-18ab-427c-9986-79b45d01d28b · outbound

This paper cites Leveraging relational autocorrelation with latent group models.

OpenRFM: Dissecting Relational In-Context Learning Leveraging relational autocorrelation with latent group models

Reference 37

Resolution: verified exact; doi, observed 2026-06-28T07:41:45.392744Z

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Observation e1de84ca-efec-4ea7-ae2b-221e61f678c2 · outbound

This paper cites In: Zong, C., Xia, F., Li, W., Navigli, R.

OpenRFM: Dissecting Relational In-Context Learning In: Zong, C., Xia, F., Li, W., Navigli, R

Reference 38

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Observation bc7a30af-36df-4535-a957-189aacc6ead7 · outbound

This paper cites Character- izing graph datasets for node classification: Homophily-heterophily dichotomy and beyond.

OpenRFM: Dissecting Relational In-Context Learning Character- izing graph datasets for node classification: Homophily-heterophily dichotomy and beyond

Reference 39

Resolution: unresolved; no resolver link, observed 2026-06-28T07:37:38.063200Z

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Observation 1637ea10-62f6-4fd4-88a9-e8935333ba69 · outbound

This paper cites TabICL: A tabular foundation model for in-context learning on large data.

OpenRFM: Dissecting Relational In-Context Learning TabICL: A tabular foundation model for in-context learning on large data

Reference 40

Resolution: unresolved; no resolver link, observed 2026-06-28T07:37:38.063200Z

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Observation 45b24aa7-541b-43c9-90d3-b3750c2b054b · outbound

This paper cites Kanatsoulis, Roshan Reddy Upendra, Mahmoud Mohammadi, Joe Meyer, Tom Palczewski, Carlos Guestrin, and Jure Leskovec.

OpenRFM: Dissecting Relational In-Context Learning Kanatsoulis, Roshan Reddy Upendra, Mahmoud Mohammadi, Joe Meyer, Tom Palczewski, Carlos Guestrin, and Jure Leskovec

Reference 41

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Observation d9188648-54a2-4f69-965e-fdfb787d4680 · outbound

This paper cites Pretraining task diversity and the emergence of non-bayesian in-context learning for regression.

OpenRFM: Dissecting Relational In-Context Learning Pretraining task diversity and the emergence of non-bayesian in-context learning for regression

Reference 42

Resolution: unresolved; no resolver link, observed 2026-06-28T07:37:38.063200Z

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Observation 16abacb7-cff2-4bc1-8337-3dbc6ba477a9 · outbound

This paper cites Lenssen, Yiwen Yuan, Zecheng Zhang, Xinwei He, and Jure Leskovec.

OpenRFM: Dissecting Relational In-Context Learning Lenssen, Yiwen Yuan, Zecheng Zhang, Xinwei He, and Jure Leskovec

Reference 43

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Observation c57c0c46-f903-461c-b7d8-d93895524456 · outbound

This paper cites URL https://proceedings.neurips.cc/paper_ files/paper/2024/file/25cd345233c65fac1fec0ce61d0f7836-Paper-Datasets_ and_Benchmarks_Track.pdf.

OpenRFM: Dissecting Relational In-Context Learning URL https://proceedings.neurips.cc/paper_ files/paper/2024/file/25cd345233c65fac1fec0ce61d0f7836-Paper-Datasets_ and_Benchmarks_Track.pdf

Reference 44

Resolution: verified exact; doi, observed 2026-06-28T07:41:45.396677Z

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Observation dbfe31f3-95a6-4de3-935b-76572d33740d · outbound

This paper cites Prototypical networks for few-shot learning.

OpenRFM: Dissecting Relational In-Context Learning Prototypical networks for few-shot learning

Reference 45

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Observation c4ed9821-89c8-4bcf-b7a3-a26bd0d73740 · outbound

This paper cites A pre- training framework for relational data with information-theoretic principles.

OpenRFM: Dissecting Relational In-Context Learning A pre- training framework for relational data with information-theoretic principles

Reference 46

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Observation 50e7f82e-4ee7-4146-a610-63f9b7d772cb · outbound

This paper cites Transformers learn in-context by gradient descent.

OpenRFM: Dissecting Relational In-Context Learning Transformers learn in-context by gradient descent

Reference 47

Resolution: unresolved; no resolver link, observed 2026-06-28T07:37:38.063200Z

Source-reported events for the cited work

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Observation bced0889-8b08-43cb-ab02-fa4d4a80096e · outbound

This paper cites 4dbinfer: A 4d benchmarking toolbox for graph-centric predictive modeling on rdbs.

OpenRFM: Dissecting Relational In-Context Learning 4dbinfer: A 4d benchmarking toolbox for graph-centric predictive modeling on rdbs

Reference 48

Resolution: verified exact; doi, observed 2026-06-28T07:41:45.388759Z

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Observation 9da47d7f-2ccc-42bb-abd7-1a82dfcd4596 · outbound

This paper cites Griffin: Towards a graph-centric relational database foundation model.

OpenRFM: Dissecting Relational In-Context Learning Griffin: Towards a graph-centric relational database foundation model

Reference 49

Resolution: unresolved; no resolver link, observed 2026-06-28T07:37:38.063200Z

Source-reported events for the cited work

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Observation 3e415f33-4000-4f7c-a9ec-55548e2657ee · outbound

This paper cites Relational In-Context Learning via Synthetic Pre-training with Structural Prior.

OpenRFM: Dissecting Relational In-Context Learning Relational In-Context Learning via Synthetic Pre-training with Structural Prior

Reference 50

Resolution: verified exact; local_arxiv, observed 2026-07-02T06:06:41.442456Z

Source-reported events for the cited work

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Observation e629c128-26f6-4b4f-bf5a-3a2cfa3b9c52 · outbound

This paper cites Graph Foundation Models: A Comprehensive Survey.

OpenRFM: Dissecting Relational In-Context Learning Graph Foundation Models: A Comprehensive Survey

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-07-02T06:06:41.439996Z

Source-reported events for the cited work

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Observation e4c85886-a6f7-449e-8f29-18b2ced1375a · outbound

This paper cites Larger language models do in-context learning differently.

OpenRFM: Dissecting Relational In-Context Learning Larger language models do in-context learning differently

Reference 52

Resolution: verified exact; arxiv_id, observed 2026-07-02T06:06:41.434356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 20a32a3a-2823-413f-aab3-1fb69871d64d · outbound

This paper cites The learnability of in-context learning.

OpenRFM: Dissecting Relational In-Context Learning The learnability of in-context learning

Reference 53

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Source-reported events for the cited work

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Observation 01abb29d-cf66-41f9-afa1-2ff87c452b59 · outbound

This paper cites Large language models are good relational learners.

OpenRFM: Dissecting Relational In-Context Learning Large language models are good relational learners

Reference 54

Resolution: unresolved; no resolver link, observed 2026-06-28T07:37:38.063200Z

Source-reported events for the cited work

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Observation 80061069-a6e5-4cd3-9b02-09ce94d007cc · outbound

This paper cites Tackling prediction tasks in relational databases with LLMs.

OpenRFM: Dissecting Relational In-Context Learning Tackling prediction tasks in relational databases with LLMs

Reference 55

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T06:06:41.436991Z

Source-reported events for the cited work

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Observation 752b97fd-ab60-4d48-885f-1d467fce2a75 · outbound

This paper cites An explanation of in- context learning as implicit Bayesian inference.

OpenRFM: Dissecting Relational In-Context Learning An explanation of in- context learning as implicit Bayesian inference

Reference 56

Resolution: unresolved; no resolver link, observed 2026-06-28T07:37:38.063200Z

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Observation 82a1ddca-e46a-4c7b-aa90-23a07c9fd85a · outbound

This paper cites Do RDB foundation models even need data? InICLR 2026 Workshop on Foundation Models for Tabular and Structured Data (DATA-FM), 2026.

OpenRFM: Dissecting Relational In-Context Learning Do RDB foundation models even need data? InICLR 2026 Workshop on Foundation Models for Tabular and Structured Data (DATA-FM), 2026

Reference 57

Resolution: unresolved; no resolver link, observed 2026-06-28T07:37:38.063200Z

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Observation 10d22f09-9196-40c9-af68-36efe9813393 · outbound

This paper cites an unresolved cited work.

OpenRFM: Dissecting Relational In-Context Learning Unresolved cited work

Reference 58

Resolution: unresolved; no resolver link, observed 2026-06-28T07:37:38.063200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 729e1046-834f-4ea8-b67a-aa589db19b48 · outbound

This paper cites ContextGNN: Beyond two-tower recommendation systems.

OpenRFM: Dissecting Relational In-Context Learning ContextGNN: Beyond two-tower recommendation systems

Reference 59

Resolution: unresolved; no resolver link, observed 2026-06-28T07:37:38.063200Z

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Unavailable: canonical work link unavailable.

Observation cae1e117-9bb0-4522-ab4b-5ad43a008694 · outbound

This paper cites What and how does in-context learning learn? Bayesian model averaging, parameterization, and generalization.

OpenRFM: Dissecting Relational In-Context Learning What and how does in-context learning learn? Bayesian model averaging, parameterization, and generalization

Reference 60

Resolution: unresolved; no resolver link, observed 2026-06-28T07:37:38.063200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49a29fb5-e753-492e-b0b0-bdef93685985 · outbound

This paper cites RT is in the lazy / frozen-feature regime.

OpenRFM: Dissecting Relational In-Context Learning RT is in the lazy / frozen-feature regime

Reference 61

Resolution: malformed identifier; arxiv_id, observed 2026-07-02T06:06:41.445137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

Observation 6fbc9b01-ada8-4335-9bec-abf828d36e2f · inbound

Parameter-Free Encoders Remain Viable for RDB Foundation Models cites this paper.

Parameter-Free Encoders Remain Viable for RDB Foundation Models OpenRFM: Dissecting Relational In-Context Learning

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-11T11:47:14.742492Z

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Observation b74cd081-e5b7-48f5-a7dc-c75c0320a1d1 · inbound

Parameter-Free Encoders Remain Viable for RDB Foundation Models cites this paper.

Parameter-Free Encoders Remain Viable for RDB Foundation Models OpenRFM: Dissecting Relational In-Context Learning

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-02T08:36:02.132826Z

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