Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T00:44:27.569160Z
Paper Citation Record · LEDGER
No-Regret Learning Under Adversarial Resource Constraints: A Spending Plan Is All You Need!
As of 9 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 2 inbound Pith citation observations for arXiv:2506.13244.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-21T06:23:20.784755Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-21T06:24:00.495250Z
Reference resolution
12 of 12 outbound references displayed
- verified exact1
- verified fuzzy5
- unresolved5
- parse uncertain0
- malformed identifier0
- metadata mismatch1
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 749bf43f-291f-408b-b111-8593be55fd5d · outbound
This paper cites [2023a] focus on online allocation with a single resource.
No-Regret Learning Under Adversarial Resource Constraints: A Spending Plan Is All You Need! [2023a] focus on online allocation with a single resource
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:44:28.868007Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 724166f9-8385-4d40-96d4-58fdd462ea0e · outbound
This paper cites Adversarial bandits with knapsacks.
No-Regret Learning Under Adversarial Resource Constraints: A Spending Plan Is All You Need! Adversarial bandits with knapsacks
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:44:29.498765Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 682e3d12-d6a2-40af-a2d5-2fd95bf9efa7 · outbound
This paper cites Online Stochastic Optimization with Wasserstein Based Non-stationarity.
No-Regret Learning Under Adversarial Resource Constraints: A Spending Plan Is All You Need! Online Stochastic Optimization with Wasserstein Based Non-stationarity
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T00:44:26.727369Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3e2019fd-c2a0-45a5-b72e-d8bf4ee1bd98 · outbound
This paper cites Learning with General ConstraintsThere exists an extended literature on online learning problem with general constraints (e.g., [Mannor et al., 2009, Liakopoulos et al., 2019]).
No-Regret Learning Under Adversarial Resource Constraints: A Spending Plan Is All You Need! Learning with General ConstraintsThere exists an extended literature on online learning problem with general constraints (e.g., [Mannor et al., 2009, Liakopoulos et al., 2019])
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:44:28.563399Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation c3517586-4ea4-46a6-af47-4b099fe68fcf · outbound
This paper cites Later, Agrawal et al.
No-Regret Learning Under Adversarial Resource Constraints: A Spending Plan Is All You Need! Later, Agrawal et al
Reference 2010
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:44:29.112056Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 2fd1b0ae-2a62-400a-a190-de0b67619e07 · outbound
This paper cites Optimal Spend Rate Estimation and Pacing for Ad Campaigns with Budgets.
No-Regret Learning Under Adversarial Resource Constraints: A Spending Plan Is All You Need! Optimal Spend Rate Estimation and Pacing for Ad Campaigns with Budgets
Reference 2014
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T00:44:27.892664Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 56dd4fff-747a-4e23-98de-7158cb074772 · outbound
This paper cites Bandits with knapsacks.
No-Regret Learning Under Adversarial Resource Constraints: A Spending Plan Is All You Need! Bandits with knapsacks
Reference 2016
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T00:44:29.842921Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 8c408b1d-45ae-4f0e-be9a-c40a6b2ffdb9 · outbound
This paper cites Provably Efficient Model-Free Algorithm for MDPs with Peak Constraints.
No-Regret Learning Under Adversarial Resource Constraints: A Spending Plan Is All You Need! Provably Efficient Model-Free Algorithm for MDPs with Peak Constraints
Reference 2018
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T00:44:26.151610Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f0b63ff1-abc4-4b06-9e7e-4acfa4241994 · outbound
This paper cites Online Learning: A Modern Introduction Using Convex Optimization.
No-Regret Learning Under Adversarial Resource Constraints: A Spending Plan Is All You Need! Online Learning: A Modern Introduction Using Convex Optimization
Reference 2019
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T00:44:27.137290Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e0820b41-f4b5-402f-aef3-21ef84b9141e · outbound
This paper cites Exploration-Exploitation in Constrained MDPs.
No-Regret Learning Under Adversarial Resource Constraints: A Spending Plan Is All You Need! Exploration-Exploitation in Constrained MDPs
Reference 2020
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T00:44:26.431839Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a48b5e45-c020-4f85-983c-bea6457fb9b8 · outbound
This paper cites Learning Adversarial MDPs with Stochastic Hard Constraints.
No-Regret Learning Under Adversarial Resource Constraints: A Spending Plan Is All You Need! Learning Adversarial MDPs with Stochastic Hard Constraints
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T00:44:27.212457Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b34d673c-8cec-4b41-ac58-f0601f8f7796 · outbound
This paper cites A New Benchmark for Online Learning with Budget-Balancing Constraints.
No-Regret Learning Under Adversarial Resource Constraints: A Spending Plan Is All You Need! A New Benchmark for Online Learning with Budget-Balancing Constraints
Reference 2025
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-07T00:44:28.154591Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Pith citing papers
Observation c8c5cc38-7aec-449f-84e3-ae727dba3dab · inbound
Constrained Contextual Bandits with Adversarial Contexts cites this paper.
Constrained Contextual Bandits with Adversarial Contexts No-Regret Learning Under Adversarial Resource Constraints: A Spending Plan Is All You Need!
Reference 267
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T18:51:08.094234Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 5c4b23db-c002-43cc-b389-2161da616cb5 · inbound
A Geometric Approach to Constrained Online Learning cites this paper.
A Geometric Approach to Constrained Online Learning No-Regret Learning Under Adversarial Resource Constraints: A Spending Plan Is All You Need!
Reference 277
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:24:00.496839Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.