Paper Citation Record · LEDGER

CBQ: Cross-Block Quantization for Large Language Models

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2312.07950.

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

pith.paper-citation-record.v1
2312.07950 v5

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 2026-08-06T06:34:29.942622+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:05:21.422495Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T23:44:26.518920Z

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 c9f9b799-e606-41d6-92f5-9b2ce40fda5d · inbound

Task-Specific Zero-shot Quantization-Aware Training for Object Detection cites this paper.

Task-Specific Zero-shot Quantization-Aware Training for Object Detection CBQ: Cross-Block Quantization for Large Language Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T15:05:21.422495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a39cb12d-e94e-4a54-a86b-a51a6c8f777e · inbound

Rethinking 1-bit Optimization Leveraging Pre-trained Large Language Models cites this paper.

Rethinking 1-bit Optimization Leveraging Pre-trained Large Language Models CBQ: Cross-Block Quantization for Large Language Models

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-21T23:44:26.521848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 5254c56b-ec7e-4e88-9394-75bff88e9515 · inbound

DPQuant: Efficient and Differentially-Private Model Training via Dynamic Quantization Scheduling cites this paper.

DPQuant: Efficient and Differentially-Private Model Training via Dynamic Quantization Scheduling CBQ: Cross-Block Quantization for Large Language Models

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-18T19:11:46.574988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation dca570d9-bc98-4065-8c5c-f1e8c777e6ff · inbound

CoreQ: Learning-Free Mismatch Correction and Successive Rounding for Quantization cites this paper.

CoreQ: Learning-Free Mismatch Correction and Successive Rounding for Quantization CBQ: Cross-Block Quantization for Large Language Models

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-16T06:52:28.407210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation dd62b779-1806-4787-adc9-94e8e236e84c · inbound

SEPTQ: A Simple and Effective Post-Training Quantization Paradigm for Large Language Models cites this paper.

SEPTQ: A Simple and Effective Post-Training Quantization Paradigm for Large Language Models CBQ: Cross-Block Quantization for Large Language Models

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-11T08:30:58.338769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 9c0f9c99-8640-42cf-9514-d2c93523cc35 · inbound

Breaking Modality Heterogeneity in Low-Bit Quantization for Large Vision-Language Models cites this paper.

Breaking Modality Heterogeneity in Low-Bit Quantization for Large Vision-Language Models CBQ: Cross-Block Quantization for Large Language Models

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-20T05:23:03.687934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.