Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
IntersectionZoo: Eco-driving for Benchmarking Multi-Agent Contextual Reinforcement Learning
As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2410.15221.
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 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T23:36:51.292840Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-14T23:13:16.422819Z
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 b028a9f8-c0cf-435e-bc89-a75f99ee63dd · inbound
NeuralMOVES: A lightweight and microscopic vehicle emission estimation model based on reverse engineering and surrogate learning cites this paper.
NeuralMOVES: A lightweight and microscopic vehicle emission estimation model based on reverse engineering and surrogate learning IntersectionZoo: Eco-driving for Benchmarking Multi-Agent Contextual Reinforcement Learning
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T23:36:51.292840Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a5bf4872-b2a7-40e8-901e-7c00e8d39c39 · inbound
cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending cites this paper.
cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending IntersectionZoo: Eco-driving for Benchmarking Multi-Agent Contextual Reinforcement Learning
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T14:49:53.197679Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a4216f34-606f-403d-a886-475ebe4dea3e · inbound
Evo-Memory: Benchmarking LLM Agent Test-time Learning with Self-Evolving Memory cites this paper.
Evo-Memory: Benchmarking LLM Agent Test-time Learning with Self-Evolving Memory IntersectionZoo: Eco-driving for Benchmarking Multi-Agent Contextual Reinforcement Learning
Reference 83
- Resolution
- verified exact
- arxiv_id, observed 2026-05-14T23:13:16.426061Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 0ffb995c-0c11-4883-be7a-77a4bd5bc6a0 · inbound
Preference-Conditioned Multi-Objective Reinforcement Learning for Runtime-Tunable Transit Signal Priority cites this paper.
Preference-Conditioned Multi-Objective Reinforcement Learning for Runtime-Tunable Transit Signal Priority IntersectionZoo: Eco-driving for Benchmarking Multi-Agent Contextual Reinforcement Learning
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T09:19:38.492589Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.