Paper Citation Record · LEDGER

Bootstrap-Conditioned Action Selection with Tabular Foundation Models

As of 18 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 0 inbound Pith citation observations for arXiv:2608.06559.

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

pith.paper-citation-record.v1
2608.06559 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T04:22:19.503336Z

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

12 of 12 outbound references displayed

verified exact0
verified fuzzy4
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a7e42cdc-174b-47e3-b974-81ab9a3447cb · outbound

This paper cites This follows the recommendation of the open-source TabPFNv2 implementation.

Bootstrap-Conditioned Action Selection with Tabular Foundation Models This follows the recommendation of the open-source TabPFNv2 implementation

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T04:22:19.577775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0c41db70-e080-491b-835a-fe3d72660fae · outbound

This paper cites These methods enjoy strong theoretical foundations but are limited in expressiveness and can perform poorly under model misspecification (Lattimore & Szepesv´ari, 2017).

Bootstrap-Conditioned Action Selection with Tabular Foundation Models These methods enjoy strong theoretical foundations but are limited in expressiveness and can perform poorly under model misspecification (Lattimore & Szepesv´ari, 2017)

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T04:22:19.629191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0221eef7-49b4-4293-8884-0feb9ddee60c · outbound

This paper cites (2021) extends posterior sampling to deep networks while Gal & Ghahramani (2016) consider dropout-based uncertainty.

Bootstrap-Conditioned Action Selection with Tabular Foundation Models (2021) extends posterior sampling to deep networks while Gal & Ghahramani (2016) consider dropout-based uncertainty

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T04:22:19.609448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5a437ec5-8cd6-4158-9763-64e94c121e0b · outbound

This paper cites an unresolved cited work.

Bootstrap-Conditioned Action Selection with Tabular Foundation Models Unresolved cited work

Reference 10

Resolution: unresolved; raw_fallback, observed 2026-08-10T04:22:19.599540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e45dd786-7271-4e5b-ad74-b1ce6c216783 · outbound

This paper cites an unresolved cited work.

Bootstrap-Conditioned Action Selection with Tabular Foundation Models Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-10T04:22:19.589740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6bcf802e-255f-4830-a714-facb11346689 · outbound

This paper cites Neural network-based contextual bandits further improve expressiveness by learning flexible reward models.

Bootstrap-Conditioned Action Selection with Tabular Foundation Models Neural network-based contextual bandits further improve expressiveness by learning flexible reward models

Reference 2010

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T04:22:19.619265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 510366bf-0cb8-4210-a990-536ea12a9333 · outbound

This paper cites Active Exploration via Autoregressive Generation of Missing Data.

Bootstrap-Conditioned Action Selection with Tabular Foundation Models Active Exploration via Autoregressive Generation of Missing Data

Reference 2013

Resolution: unresolved; no resolver link, observed 2026-08-10T04:22:19.463795Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41a0df89-e67a-4abc-a14d-c4f547490594 · outbound

This paper cites Thompson sampling with the online bootstrap.

Bootstrap-Conditioned Action Selection with Tabular Foundation Models Thompson sampling with the online bootstrap

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-10T04:22:19.472746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 61c9d68f-e727-422c-80d2-5dc3c9791c2b · outbound

This paper cites RL$^2$: Fast Reinforcement Learning via Slow Reinforcement Learning.

Bootstrap-Conditioned Action Selection with Tabular Foundation Models RL$^2$: Fast Reinforcement Learning via Slow Reinforcement Learning

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-10T04:22:19.468551Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a4fd7df-3857-47d4-bba4-574a1de2ef6c · outbound

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

Bootstrap-Conditioned Action Selection with Tabular Foundation Models SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-10T04:22:19.480860Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd7e4c70-9870-4dde-8c19-c5ff1f450545 · outbound

This paper cites an unresolved cited work.

Bootstrap-Conditioned Action Selection with Tabular Foundation Models Unresolved cited work

Reference 2020

Resolution: unresolved; raw_fallback, observed 2026-08-10T04:22:19.638820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2be1b41e-c96f-4712-bced-b061f9bebb9c · outbound

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

Bootstrap-Conditioned Action Selection with Tabular Foundation Models TabTransformer: Tabular Data Modeling Using Contextual Embeddings

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-10T04:22:19.476637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.