Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Dealing with Sparse Rewards in Reinforcement Learning
As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:1910.09281.
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 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T17:21:19.537710Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T15:29:55.594907Z
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 337f6a73-6a5b-45ff-b647-f0f198d752fb · inbound
Noise-Resilient Symbolic Regression with Dynamic Gating Reinforcement Learning cites this paper.
Noise-Resilient Symbolic Regression with Dynamic Gating Reinforcement Learning Dealing with Sparse Rewards in Reinforcement Learning
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T22:40:16.221035Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bfb38035-4bbb-48cc-85b1-f078aa19bae0 · inbound
From Sparse to Dense: Toddler-inspired Reward Transition in Goal-Oriented Reinforcement Learning cites this paper.
From Sparse to Dense: Toddler-inspired Reward Transition in Goal-Oriented Reinforcement Learning Dealing with Sparse Rewards in Reinforcement Learning
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T04:37:01.861960Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3dcc38c7-143c-4d6c-9845-a260871e95c9 · inbound
VARD: Efficient and Dense Fine-Tuning for Diffusion Models with Value-based RL cites this paper.
VARD: Efficient and Dense Fine-Tuning for Diffusion Models with Value-based RL Dealing with Sparse Rewards in Reinforcement Learning
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:18:52.713790Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dc2e7ed3-6589-478f-8935-61ef15aaacef · inbound
SCAR: Shapley Credit Assignment for More Efficient RLHF cites this paper.
SCAR: Shapley Credit Assignment for More Efficient RLHF Dealing with Sparse Rewards in Reinforcement Learning
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:02:49.225204Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 25203ca4-d933-4425-b23a-05b3cf46c5f8 · inbound
SparseMap: A Sparse Tensor Accelerator Framework Based on Evolution Strategy cites this paper.
SparseMap: A Sparse Tensor Accelerator Framework Based on Evolution Strategy Dealing with Sparse Rewards in Reinforcement Learning
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T17:21:19.537710Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e44ce8df-e4ff-4b13-ae50-ce7f5db73183 · inbound
Spectral fluctuations and crossovers in multilayer network cites this paper.
Spectral fluctuations and crossovers in multilayer network Dealing with Sparse Rewards in Reinforcement Learning
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T17:19:37.815966Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ce1b4e95-c112-4510-8d56-4328a4dbab63 · inbound
Do Less, Achieve More: Do We Need Every-Step Optimization for RL Fine-tuning of Diffusion Models? cites this paper.
Do Less, Achieve More: Do We Need Every-Step Optimization for RL Fine-tuning of Diffusion Models? Dealing with Sparse Rewards in Reinforcement Learning
Reference 13
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T19:48:57.311552Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 824aeed7-4275-48ab-ba4a-539b19db6c86 · inbound
Mesh-RL: Coupled subgrid reinforcement learning cites this paper.
Mesh-RL: Coupled subgrid reinforcement learning Dealing with Sparse Rewards in Reinforcement Learning
Reference 28
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T15:29:55.596964Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation d234f2db-73f8-4d88-8010-ee730468adda · inbound
Learning Gait-Aware Quadruped Locomotion with Temporal Logic Specifications cites this paper.
Learning Gait-Aware Quadruped Locomotion with Temporal Logic Specifications Dealing with Sparse Rewards in Reinforcement Learning
Reference 30
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T12:06:55.368456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 11b4206c-2cfd-4ab9-a6c8-5e136347aefd · inbound
STAIR: Effective Incident Response Using an End-to-End Agentic Planning Framework cites this paper.
STAIR: Effective Incident Response Using an End-to-End Agentic Planning Framework Dealing with Sparse Rewards in Reinforcement Learning
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T15:45:23.242099Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.