Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Improving the End-to-End Efficiency of Offline Inference for Multi-LLM Applications Based on Sampling and Simulation
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2503.16893.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T21:16:14.732186Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-29T10:13:17.802581Z
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 97dfd605-77d7-4623-b699-e30971073d1b · inbound
Toward Edge General Intelligence with Multiple-Large Language Model (Multi-LLM): Architecture, Trust, and Orchestration cites this paper.
Toward Edge General Intelligence with Multiple-Large Language Model (Multi-LLM): Architecture, Trust, and Orchestration Improving the End-to-End Efficiency of Offline Inference for Multi-LLM Applications Based on Sampling and Simulation
Reference 48
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:16:14.732186Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 73c3680f-d624-4025-898d-e45fd1506bcc · inbound
AI Reasoning for Wireless Communications and Networking: A Survey and Perspectives cites this paper.
AI Reasoning for Wireless Communications and Networking: A Survey and Perspectives Improving the End-to-End Efficiency of Offline Inference for Multi-LLM Applications Based on Sampling and Simulation
Reference 49
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T19:34:26.709248Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4fb8e0ac-34dc-4678-80c3-dd5b7a8d9be7 · inbound
SiDP: Memory-Efficient Data Parallelism for Offline LLM Inference cites this paper.
SiDP: Memory-Efficient Data Parallelism for Offline LLM Inference Improving the End-to-End Efficiency of Offline Inference for Multi-LLM Applications Based on Sampling and Simulation
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T10:13:17.804076Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.