Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Relax: Composable Abstractions for End-to-End Dynamic Machine Learning
As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2311.02103.
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 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T20:30:11.338178Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-16T23:58:43.007325Z
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 66d43ce9-8a64-442d-8977-b075ff0fe687 · inbound
Local deployment of large-scale music AI models on commodity hardware cites this paper.
Local deployment of large-scale music AI models on commodity hardware Relax: Composable Abstractions for End-to-End Dynamic Machine Learning
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T20:30:11.338178Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9214a4fc-1df9-4837-93a6-01246410944b · inbound
ATiM: Autotuning Tensor Programs for Processing-in-DRAM cites this paper.
ATiM: Autotuning Tensor Programs for Processing-in-DRAM Relax: Composable Abstractions for End-to-End Dynamic Machine Learning
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T00:14:06.591020Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d29aee1d-be8e-44b0-bd73-0df2a92a7fc1 · inbound
ODMA: On-Demand Memory Allocation Strategy for LLM Serving on LPDDR-Class Accelerators cites this paper.
ODMA: On-Demand Memory Allocation Strategy for LLM Serving on LPDDR-Class Accelerators Relax: Composable Abstractions for End-to-End Dynamic Machine Learning
Reference 42
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T23:58:43.008900Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.