Paper Citation Record · LEDGER

Offline-to-Online Learning in Linear Bandits

As of 9 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2606.04305.

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

pith.paper-citation-record.v1
2606.04305 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-28T06:57:24.510463Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

19 of 19 outbound references displayed

verified exact2
verified fuzzy0
unresolved17
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8d5e47cc-5975-49ce-9201-b4f73b8bfe44 · outbound

This paper cites Improved algorithms for linear stochastic bandits.

Offline-to-Online Learning in Linear Bandits Improved algorithms for linear stochastic bandits

Reference 1

Resolution: unresolved; no resolver link, observed 2026-06-28T06:57:24.510463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb3adeb0-9cde-48b6-86cb-cc16774cd602 · outbound

This paper cites Jump starting bandits with LLM -generated prior knowledge.

Offline-to-Online Learning in Linear Bandits Jump starting bandits with LLM -generated prior knowledge

Reference 2

Resolution: unresolved; no resolver link, observed 2026-06-28T06:57:24.510463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd17f499-8023-4dae-9419-8ea440741adb · outbound

This paper cites Finite-time analysis of the multiarmed bandit problem.

Offline-to-Online Learning in Linear Bandits Finite-time analysis of the multiarmed bandit problem

Reference 3

Resolution: unresolved; no resolver link, observed 2026-06-28T06:57:24.510463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 81e49d25-7eae-4c80-8b81-0766da39f630 · outbound

This paper cites Bandit online linear optimization with hints and queries.

Offline-to-Online Learning in Linear Bandits Bandit online linear optimization with hints and queries

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-28T06:57:24.510463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df477036-392d-4dda-8f83-8adf4a1683b5 · outbound

This paper cites Leveraging (biased) information: Multi-armed bandits with offline data.

Offline-to-Online Learning in Linear Bandits Leveraging (biased) information: Multi-armed bandits with offline data

Reference 5

Resolution: unresolved; no resolver link, observed 2026-06-28T06:57:24.510463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40c33903-f05f-41f9-82c8-cc5ddb7cfdaf · outbound

This paper cites Leveraging initial hints for free in stochastic linear bandits.

Offline-to-Online Learning in Linear Bandits Leveraging initial hints for free in stochastic linear bandits

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-28T06:57:24.510463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ede5438-309c-4020-8c46-5d1f656ff80e · outbound

This paper cites Leveraging demonstrations to improve online learning: Quality matters.

Offline-to-Online Learning in Linear Bandits Leveraging demonstrations to improve online learning: Quality matters

Reference 7

Resolution: unresolved; no resolver link, observed 2026-06-28T06:57:24.510463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b4ec17da-45be-4117-8746-ea74022623a2 · outbound

This paper cites Learning across the gap: Hybrid multi-armed bandits with heterogeneous offline and online data.

Offline-to-Online Learning in Linear Bandits Learning across the gap: Hybrid multi-armed bandits with heterogeneous offline and online data

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-28T06:57:24.510463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23a59bf0-3815-422d-be6d-0fdc17f4c2a7 · outbound

This paper cites Conservative contextual linear bandits.

Offline-to-Online Learning in Linear Bandits Conservative contextual linear bandits

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-28T06:57:24.510463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17420425-ee18-490c-b91a-06dc741c7334 · outbound

This paper cites Bandit algorithms.

Offline-to-Online Learning in Linear Bandits Bandit algorithms

Reference 10

Resolution: unresolved; no resolver link, observed 2026-06-28T06:57:24.510463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bdf16dc5-bb3f-4860-844c-6b6041a6dcb9 · outbound

This paper cites Pessimism for offline linear contextual bandits using _p confidence sets.

Offline-to-Online Learning in Linear Bandits Pessimism for offline linear contextual bandits using _p confidence sets

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-28T06:57:24.510463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31509049-0645-42f3-80fd-19aa45da837c · outbound

This paper cites A contextual-bandit approach to personalized news article recommendation.

Offline-to-Online Learning in Linear Bandits A contextual-bandit approach to personalized news article recommendation

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-28T06:57:24.510463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8b459540-178e-4b47-85ec-3ba033f53549 · outbound

This paper cites Balancing optimism and pessimism in offline-to-online learning.

Offline-to-Online Learning in Linear Bandits Balancing optimism and pessimism in offline-to-online learning

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-07-02T07:26:45.903892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b273fa15-3ecb-4e7f-badd-46c04c800649 · outbound

This paper cites Multi-armed bandit problems with history.

Offline-to-Online Learning in Linear Bandits Multi-armed bandit problems with history

Reference 14

Resolution: unresolved; no resolver link, observed 2026-06-28T06:57:24.510463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 953f1640-8167-49d7-a59b-78174cd13a11 · outbound

This paper cites Spectral bandits for smooth graph functions.

Offline-to-Online Learning in Linear Bandits Spectral bandits for smooth graph functions

Reference 15

Resolution: unresolved; no resolver link, observed 2026-06-28T06:57:24.510463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ab6aad4-f164-47e8-a3b4-be7187288a35 · outbound

This paper cites Regret minimization in Linear Bandits with offline data via extended D-optimal exploration.

Offline-to-Online Learning in Linear Bandits Regret minimization in Linear Bandits with offline data via extended D-optimal exploration

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-07-02T07:26:45.906618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 71d3b1db-1b2d-4617-9273-f82022629a03 · outbound

This paper cites Taking a hint: How to leverage loss predictors in contextual bandits? Conference on Learning Theory, 2020.

Offline-to-Online Learning in Linear Bandits Taking a hint: How to leverage loss predictors in contextual bandits? Conference on Learning Theory, 2020

Reference 17

Resolution: unresolved; no resolver link, observed 2026-06-28T06:57:24.510463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 13032a3a-3631-4d76-9536-57157e806b6d · outbound

This paper cites Conservative bandits.

Offline-to-Online Learning in Linear Bandits Conservative bandits

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-28T06:57:24.510463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ff653a7-ca9b-4f90-b4b4-d3d5bbdcea73 · outbound

This paper cites On the optimality of batch policy optimization algorithms.

Offline-to-Online Learning in Linear Bandits On the optimality of batch policy optimization algorithms

Reference 19

Resolution: unresolved; no resolver link, observed 2026-06-28T06:57:24.510463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.