Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
LLM-Assist: Enhancing Closed-Loop Planning with Language-Based Reasoning
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2401.00125.
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 2026-08-07T20:44:01.754517Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T19:30:07.193386Z
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 337ecc25-8630-463d-9eca-a4d470f854a0 · inbound
Knowledge Integration Strategies in Autonomous Vehicle Prediction and Planning: A Comprehensive Survey cites this paper.
Knowledge Integration Strategies in Autonomous Vehicle Prediction and Planning: A Comprehensive Survey LLM-Assist: Enhancing Closed-Loop Planning with Language-Based Reasoning
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T20:44:01.754517Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 14f0662e-bd18-494f-bda9-780f3884f562 · inbound
LiloDriver: A Lifelong Learning Framework for Closed-loop Motion Planning in Long-tail Autonomous Driving Scenarios cites this paper.
LiloDriver: A Lifelong Learning Framework for Closed-loop Motion Planning in Long-tail Autonomous Driving Scenarios LLM-Assist: Enhancing Closed-Loop Planning with Language-Based Reasoning
Reference 30
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T13:21:35.674668Z
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 792efa38-91cb-474e-9e98-721ee4ab9bcc · inbound
Novelty-based Tree-of-Thought Search for LLM Reasoning and Planning cites this paper.
Novelty-based Tree-of-Thought Search for LLM Reasoning and Planning LLM-Assist: Enhancing Closed-Loop Planning with Language-Based Reasoning
Reference 32
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T19:56:08.621662Z
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 55acfd52-17ce-4730-8897-5b6eb29f2e58 · inbound
Position: Uncertainty Quantification in LLMs is Just Unsupervised Clustering cites this paper.
Position: Uncertainty Quantification in LLMs is Just Unsupervised Clustering LLM-Assist: Enhancing Closed-Loop Planning with Language-Based Reasoning
Reference 8
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-20T06:58:06.227987Z
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 967f823f-39fa-44f4-873a-33b0c8b21169 · inbound
ASSCG: Just-Right Gating over Chattering for Fast-Slow LLM Planning in Autonomous Driving cites this paper.
ASSCG: Just-Right Gating over Chattering for Fast-Slow LLM Planning in Autonomous Driving LLM-Assist: Enhancing Closed-Loop Planning with Language-Based Reasoning
Reference 28
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-04T19:30:07.195003Z
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 a1fb0cba-a6c3-4b83-af1f-e86832949976 · inbound
Agent-driven Long-tail Simulation for Autonomous Driving cites this paper.
Agent-driven Long-tail Simulation for Autonomous Driving LLM-Assist: Enhancing Closed-Loop Planning with Language-Based Reasoning
Reference 49
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T20:01:39.628512Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 00d4f116-b7b7-43f6-810b-767c2dff5c91 · inbound
Who Responds When the Driver Is Gone? A Framework for Holistic Passenger Intent Understanding cites this paper.
Who Responds When the Driver Is Gone? A Framework for Holistic Passenger Intent Understanding LLM-Assist: Enhancing Closed-Loop Planning with Language-Based Reasoning
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T15:28:28.559056Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.