Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
MobileQuant: Mobile-friendly Quantization for On-device Language Models
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2408.13933.
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 2026-08-09T19:12:56.203006Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T18:41:10.755619Z
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 ef96afa8-2e41-47f1-810e-ab31e5b2c0a4 · inbound
MQuant: Unleashing the Inference Potential of Multimodal Large Language Models via Full Static Quantization cites this paper.
MQuant: Unleashing the Inference Potential of Multimodal Large Language Models via Full Static Quantization MobileQuant: Mobile-friendly Quantization for On-device Language Models
Reference 51
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T19:12:56.203006Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7f66a7b5-21a4-4ddd-bfa0-846558a22d63 · inbound
Dissecting the Impact of Mobile DVFS Governors on LLM Inference Performance and Energy Efficiency cites this paper.
Dissecting the Impact of Mobile DVFS Governors on LLM Inference Performance and Energy Efficiency MobileQuant: Mobile-friendly Quantization for On-device Language Models
Reference 35
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T20:44:17.139047Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7905a8ab-a160-4d63-b651-de5acaef198f · inbound
HCInfer: An Efficient Inference System via Error Compensation for Resource-Constrained Devices cites this paper.
HCInfer: An Efficient Inference System via Error Compensation for Resource-Constrained Devices MobileQuant: Mobile-friendly Quantization for On-device Language Models
Reference 16
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T18:41:10.758930Z
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.