Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
WALL-E: World Alignment by Rule Learning Improves World Model-based LLM Agents
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2410.07484.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T13:45:34.917874Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T19:40:06.142990Z
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 c1411a1b-74ed-474a-a17b-3bfcb3da0879 · inbound
Agent-Environment Alignment via Automated Interface Generation cites this paper.
Agent-Environment Alignment via Automated Interface Generation WALL-E: World Alignment by Rule Learning Improves World Model-based LLM Agents
Reference 63
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:45:34.917874Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3f2e8c3e-9801-439b-9faa-654e3e74d124 · inbound
Edge General Intelligence Through World Models and Agentic AI: Fundamentals, Solutions, and Challenges cites this paper.
Edge General Intelligence Through World Models and Agentic AI: Fundamentals, Solutions, and Challenges WALL-E: World Alignment by Rule Learning Improves World Model-based LLM Agents
Reference 167
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T21:02:04.804019Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fb88287e-b307-4eb0-9d8c-575723db98c1 · inbound
MultiFluxAI Enhancing Platform Engineering with Advanced Agent-Orchestrated Retrieval Systems cites this paper.
MultiFluxAI Enhancing Platform Engineering with Advanced Agent-Orchestrated Retrieval Systems WALL-E: World Alignment by Rule Learning Improves World Model-based LLM Agents
Reference 35
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T14:28:40.473346Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c6b1abd0-da8d-4060-9b40-fc87a5726517 · inbound
Mini Amusement Parks (MAPs): A Testbed for Modelling Business Decisions cites this paper.
Mini Amusement Parks (MAPs): A Testbed for Modelling Business Decisions WALL-E: World Alignment by Rule Learning Improves World Model-based LLM Agents
Reference 54
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T21:20:40.653205Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e652c211-19ce-484a-8350-3ac090c6487b · inbound
ReCAPA: Hierarchical Predictive Correction to Mitigate Cascading Failures cites this paper.
ReCAPA: Hierarchical Predictive Correction to Mitigate Cascading Failures WALL-E: World Alignment by Rule Learning Improves World Model-based LLM Agents
Reference 26
- Resolution
- verified exact
- arxiv_id, observed 2026-05-09T22:44:15.183738Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation b6f8d41c-eaf3-4cc7-8967-13e90e995673 · inbound
ReCAPA: Hierarchical Predictive Correction to Mitigate Cascading Failures cites this paper.
ReCAPA: Hierarchical Predictive Correction to Mitigate Cascading Failures WALL-E: World Alignment by Rule Learning Improves World Model-based LLM Agents
Reference 26
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T03:11:19.350622Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation c313a040-e68e-4145-ae45-7d6a9afaf05f · inbound
Beyond Next-Observation Prediction: Agent-Authored World Modeling for Sequential Decision Making cites this paper.
Beyond Next-Observation Prediction: Agent-Authored World Modeling for Sequential Decision Making WALL-E: World Alignment by Rule Learning Improves World Model-based LLM Agents
Reference 27
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T19:40:06.144683Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 22123607-f8f8-470f-89ba-9012aad610e9 · inbound
Agent vs. Parametric World Models: Hybrid Planning for Reliable Language Agents cites this paper.
Agent vs. Parametric World Models: Hybrid Planning for Reliable Language Agents WALL-E: World Alignment by Rule Learning Improves World Model-based LLM Agents
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-07-12T11:37:35.542449Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 83c96a2d-31e5-41ee-a841-927b51b1252c · inbound
Object-Centric Environment Modeling for Agentic Tasks cites this paper.
Object-Centric Environment Modeling for Agentic Tasks WALL-E: World Alignment by Rule Learning Improves World Model-based LLM Agents
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-07-12T06:39:21.435864Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.