Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
The Efficiency Spectrum of Large Language Models: An Algorithmic Survey
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2312.00678.
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 2026-08-07T05:56:56.774041Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
11
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 2a898309-6375-4602-a9dd-02e8e0f4477f · inbound
A Survey on Efficient Inference for Large Language Models cites this paper.
A Survey on Efficient Inference for Large Language Models The Efficiency Spectrum of Large Language Models: An Algorithmic Survey
Reference 21
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T02:39:33.658267Z
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.
Observation d3f7b30d-9b1d-4ea6-a197-5db3bdaf6871 · inbound
AI Safety Landscape for Large Language Models: Taxonomy, State-of-the-art, and Future Directions cites this paper.
AI Safety Landscape for Large Language Models: Taxonomy, State-of-the-art, and Future Directions The Efficiency Spectrum of Large Language Models: An Algorithmic Survey
Reference 181
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T21:55:50.108625Z
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.
Observation 5a9e363e-7f67-4f63-9e44-a51864a34603 · inbound
Towards Efficient Multi-LLM Inference: Characterization and Analysis of LLM Routing and Hierarchical Techniques cites this paper.
Towards Efficient Multi-LLM Inference: Characterization and Analysis of LLM Routing and Hierarchical Techniques The Efficiency Spectrum of Large Language Models: An Algorithmic Survey
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T05:56:56.774041Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 74017b55-efaf-4d73-b710-31c1a8b22500 · inbound
A Survey of Context Engineering for Large Language Models cites this paper.
A Survey of Context Engineering for Large Language Models The Efficiency Spectrum of Large Language Models: An Algorithmic Survey
Reference 227
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T20:58:45.300849Z
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.
Observation 5bcb6932-b6ef-44fd-a145-651462efecbc · inbound
GPT-OSS-20B: A Comprehensive Deployment-Centric Analysis of OpenAI's Open-Weight Mixture of Experts Model cites this paper.
GPT-OSS-20B: A Comprehensive Deployment-Centric Analysis of OpenAI's Open-Weight Mixture of Experts Model The Efficiency Spectrum of Large Language Models: An Algorithmic Survey
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T17:35:14.778485Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.