Paper Citation Record · LEDGER

Accurate INT8 Training Through Dynamic Block-Level Fallback

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2503.08040.

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

pith.paper-citation-record.v1
2503.08040 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:41:09.309660Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-06-30T18:04:57.980305Z

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 90f8cfd0-4918-4aef-831d-3931fb1084c7 · inbound

Scaling Law for Quantization-Aware Training cites this paper.

Scaling Law for Quantization-Aware Training Accurate INT8 Training Through Dynamic Block-Level Fallback

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-07T15:41:09.309660Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4dba0caa-bad5-4e6c-a16a-752d4abd5ae4 · inbound

PAROAttention: Pattern-Aware ReOrdering for Efficient Sparse and Quantized Attention in Visual Generation Models cites this paper.

PAROAttention: Pattern-Aware ReOrdering for Efficient Sparse and Quantized Attention in Visual Generation Models Accurate INT8 Training Through Dynamic Block-Level Fallback

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-06T23:51:05.603947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6eba80f-5fee-45ca-8246-297dde9e6c26 · inbound

Decomposing MXFP4 quantization error for LLM reinforcement learning: reducible bias, recoverable deadzone, and an irreducible floor cites this paper.

Decomposing MXFP4 quantization error for LLM reinforcement learning: reducible bias, recoverable deadzone, and an irreducible floor Accurate INT8 Training Through Dynamic Block-Level Fallback

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-05-21T07:59:50.016069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 98245253-d66a-427b-a56e-b95e0b78ef32 · inbound

Decomposing MXFP4 quantization error for LLM reinforcement learning: reducible bias, recoverable deadzone, and an irreducible floor cites this paper.

Decomposing MXFP4 quantization error for LLM reinforcement learning: reducible bias, recoverable deadzone, and an irreducible floor Accurate INT8 Training Through Dynamic Block-Level Fallback

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:50:23.669199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 73edc660-2ea2-43d3-82ab-325d47ac241d · inbound

Decomposing MXFP4 quantization error for LLM reinforcement learning: reducible bias, recoverable deadzone, and an irreducible floor cites this paper.

Decomposing MXFP4 quantization error for LLM reinforcement learning: reducible bias, recoverable deadzone, and an irreducible floor Accurate INT8 Training Through Dynamic Block-Level Fallback

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-06-30T18:04:57.982062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 413d721b-af23-4e38-80de-b56481417c8b · inbound

HiFloat4 Format for End-To-End Reinforcement Learning Post-Training of Large Language Models cites this paper.

HiFloat4 Format for End-To-End Reinforcement Learning Post-Training of Large Language Models Accurate INT8 Training Through Dynamic Block-Level Fallback

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-01T14:11:21.015267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.