Paper Citation Record · LEDGER

Ascend HiFloat8 Format for Deep Learning

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2409.16626.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2409.16626 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:30:56.425818Z

measured 1 of 1 external citation measurements

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

1
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 5052a4fc-35d9-4428-b1d4-5b21fb129e12 · inbound

Low-Precision Training of Large Language Models: Methods, Challenges, and Opportunities cites this paper.

Low-Precision Training of Large Language Models: Methods, Challenges, and Opportunities Ascend HiFloat8 Format for Deep Learning

Reference 117

Resolution: unresolved; no resolver link, observed 2026-08-16T04:30:56.425818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df531b9f-dce4-4ecb-9a45-488194f1804e · inbound

Analysis of Floating-Point Matrix Multiplication Computed via Integer Arithmetic cites this paper.

Analysis of Floating-Point Matrix Multiplication Computed via Integer Arithmetic Ascend HiFloat8 Format for Deep Learning

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-19T09:12:14.210629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a948c4f8-9ab8-4102-8b09-cd7ea7c0581d · inbound

What is New in Stochastic Rounding: a Survey on Theory, Hardware, and Applications cites this paper.

What is New in Stochastic Rounding: a Survey on Theory, Hardware, and Applications Ascend HiFloat8 Format for Deep Learning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-07-15T14:02:44.140957Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d9fd664a-75e0-43e0-a3d8-c1ecbaff330d · inbound

OSP-Next: Efficient High-Quality Video Generation with Sparse Sequence Parallelism, HiF8 Quantization, and Reinforcement Learning cites this paper.

OSP-Next: Efficient High-Quality Video Generation with Sparse Sequence Parallelism, HiF8 Quantization, and Reinforcement Learning Ascend HiFloat8 Format for Deep Learning

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-06-29T13:13:27.491056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 39382753-e800-48d8-8de9-6e3250753ad6 · inbound

Boundary-Protection W8A8 HiFloat8 Quantization for Large-Scale Text-to-Video Diffusion Transformers cites this paper.

Boundary-Protection W8A8 HiFloat8 Quantization for Large-Scale Text-to-Video Diffusion Transformers Ascend HiFloat8 Format for Deep Learning

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-07-01T20:46:13.520818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 334bbd5b-dbc8-47e0-9fba-1e38106c6424 · inbound

GoldenFloat: A Phi-Derived Static-Split Floating-Point Family from GF4 to GF1024 with a Lucas-Exact Integer Identity cites this paper.

GoldenFloat: A Phi-Derived Static-Split Floating-Point Family from GF4 to GF1024 with a Lucas-Exact Integer Identity Ascend HiFloat8 Format for Deep Learning

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-07-02T11:26:54.603201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e3f7cae5-1963-4665-bb7f-4fe279da2caf · inbound

HINT: Toward an Executable Hardware-Intent Representation Layer for LLM-Driven RTL Generation cites this paper.

HINT: Toward an Executable Hardware-Intent Representation Layer for LLM-Driven RTL Generation Ascend HiFloat8 Format for Deep Learning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T00:34:19.129259Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.