Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1912.02572.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T20:29:13.303844Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T13:39:50.839688Z
0 of 0 outbound references displayed
External citation measurements
No source-named external measurement is stored.
No outbound reference observations are available for this paper version.
Observation 0b8970af-e32b-4697-9083-cd73952bf2a1 · inbound
Multi-Agent Reinforcement Learning for Dynamic Pricing in Supply Chains: Benchmarking Strategic Agent Behaviours under Realistically Simulated Market Conditions Dynamic Pricing on E-commerce Platform with Deep Reinforcement Learning: A Field Experiment
Reference 37
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f5a96118-9d84-4e97-a601-2d2dbaf09587 · inbound
PrefBench: Evaluating Zero-Shot LLM Agents in Hidden-Preference Personalized Pricing Negotiations Dynamic Pricing on E-commerce Platform with Deep Reinforcement Learning: A Field Experiment
Reference 2
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 f7f1b4de-fd2c-45f0-a4f0-eb664af404fa · inbound
AIGP: An LLM-Based Framework for Long-Term Value Alignment in E-Commerce Pricing Dynamic Pricing on E-commerce Platform with Deep Reinforcement Learning: A Field Experiment
Reference 7
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 d817cf8f-7b45-4294-9dc5-6fcc65caebf8 · inbound
Counterfactual Optimal Action Trees (COAT): Interpretable Prescriptive Policies from Observational Data Dynamic Pricing on E-commerce Platform with Deep Reinforcement Learning: A Field Experiment
Reference 28
Source-reported events for the cited work
Unavailable: canonical work link unavailable.