Paper Citation Record · LEDGER

ExTernD: Expanded-Rank Ternary Decomposition Ternary LLM PTQ with Accuracy Approaching Any Quantization Level

As of 8 August 2026, this Paper Citation Record lists 9 of 9 outbound references and 0 inbound Pith citation observations for arXiv:2607.13511.

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

pith.paper-citation-record.v1
2607.13511 v1

Coverage vector

measured 9 of 9 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T05:02:33.018306Z

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

9 of 9 outbound references displayed

verified exact0
verified fuzzy0
unresolved9
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 76f403ad-57b6-4908-83fe-b848d56cd727 · outbound

This paper cites BitNet: Scaling 1-bit Transformers for Large Language Models.

ExTernD: Expanded-Rank Ternary Decomposition Ternary LLM PTQ with Accuracy Approaching Any Quantization Level BitNet: Scaling 1-bit Transformers for Large Language Models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T05:02:32.401384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d0836ca-4e65-4ccd-b7a5-d76e4334c752 · outbound

This paper cites The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits.

ExTernD: Expanded-Rank Ternary Decomposition Ternary LLM PTQ with Accuracy Approaching Any Quantization Level The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-02T05:02:32.482313Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b40a251a-68f6-405d-93de-bcaf3ad2a5ea · outbound

This paper cites Ternary Weight Networks.

ExTernD: Expanded-Rank Ternary Decomposition Ternary LLM PTQ with Accuracy Approaching Any Quantization Level Ternary Weight Networks

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T05:02:32.547154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ebc5ce4-e4b4-4fde-8e96-09742a7fd340 · outbound

This paper cites Trained Ternary Quantization.

ExTernD: Expanded-Rank Ternary Decomposition Ternary LLM PTQ with Accuracy Approaching Any Quantization Level Trained Ternary Quantization

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-02T05:02:32.602175Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 301d4df4-c336-4613-ba53-6fdf28a098e6 · outbound

This paper cites an unresolved cited work.

ExTernD: Expanded-Rank Ternary Decomposition Ternary LLM PTQ with Accuracy Approaching Any Quantization Level Unresolved cited work

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-02T05:02:32.709356Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a516ef7c-85c2-4cde-9a5b-184acac37424 · outbound

This paper cites an unresolved cited work.

ExTernD: Expanded-Rank Ternary Decomposition Ternary LLM PTQ with Accuracy Approaching Any Quantization Level Unresolved cited work

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T05:02:32.788362Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ca49007-e331-4bd6-99e1-95a9f5a2f714 · outbound

This paper cites GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers.

ExTernD: Expanded-Rank Ternary Decomposition Ternary LLM PTQ with Accuracy Approaching Any Quantization Level GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T05:02:32.834248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4303767c-6ac6-430e-9a79-77af88cd7fc7 · outbound

This paper cites an unresolved cited work.

ExTernD: Expanded-Rank Ternary Decomposition Ternary LLM PTQ with Accuracy Approaching Any Quantization Level Unresolved cited work

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-02T05:02:32.933003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f853ec2-a042-444a-90a0-f731b80946eb · outbound

This paper cites Wang et al.

ExTernD: Expanded-Rank Ternary Decomposition Ternary LLM PTQ with Accuracy Approaching Any Quantization Level Wang et al

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T05:02:33.018306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.