Paper Citation Record · LEDGER

Adacc: An Adaptive Framework Unifying Compression and Activation Recomputation for LLM Training

As of 20 August 2026, this Paper Citation Record lists 1 of 1 outbound references and 3 inbound Pith citation observations for arXiv:2508.00806.

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

pith.paper-citation-record.v1
2508.00806 v2

Coverage vector

measured 1 of 1 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T05:58:30.074525Z

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-26T21:05:49.893508Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T00:39:16.838598Z

Reference resolution

1 of 1 outbound references displayed

verified exact1
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 47c06a09-c9ca-4eed-8635-678982d7ea5c · outbound

This paper cites On the controllability of the Kuramoto-Sivashinsky equation on multi-dimensional cylindrical domains.

Adacc: An Adaptive Framework Unifying Compression and Activation Recomputation for LLM Training On the controllability of the Kuramoto-Sivashinsky equation on multi-dimensional cylindrical domains

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-08-06T05:58:30.280520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

Observation 7fa41a23-20e3-4402-a2a5-fd279fa84e71 · inbound

AGoQ: Activation and Gradient Quantization for Memory-Efficient Distributed Training of LLMs cites this paper.

AGoQ: Activation and Gradient Quantization for Memory-Efficient Distributed Training of LLMs Adacc: An Adaptive Framework Unifying Compression and Activation Recomputation for LLM Training

Reference 112

Resolution: verified exact; arxiv_id, observed 2026-05-11T15:31:18.086018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3b1c5ac1-7aa0-4980-a4e4-460cf57f65ab · inbound

AGoQ: Activation and Gradient Quantization for Memory-Efficient Distributed Training of LLMs cites this paper.

AGoQ: Activation and Gradient Quantization for Memory-Efficient Distributed Training of LLMs Adacc: An Adaptive Framework Unifying Compression and Activation Recomputation for LLM Training

Reference 112

Resolution: verified exact; arxiv_id, observed 2026-05-12T05:21:30.749431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6b46fc0a-7641-4618-9ba6-ffa5a09b0306 · inbound

Techniques for Peak Memory Reduction for LoRA Fine-tuning of LLMs on Edge Devices cites this paper.

Techniques for Peak Memory Reduction for LoRA Fine-tuning of LLMs on Edge Devices Adacc: An Adaptive Framework Unifying Compression and Activation Recomputation for LLM Training

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-07-04T00:39:16.840253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.