Paper Citation Record · LEDGER

Understanding and Overcoming the Challenges of Efficient Transformer Quantization

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2109.12948.

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

pith.paper-citation-record.v1
2109.12948 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:55:14.109364Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T12:36:56.029956Z

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 45a3d574-8780-4186-9f90-ab8356ad0364 · inbound

LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale cites this paper.

LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale Understanding and Overcoming the Challenges of Efficient Transformer Quantization

Reference 120

Resolution: verified exact; arxiv_id, observed 2026-05-13T13:35:36.041677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e82989ce-b32f-437b-a7e9-e613644e434e · inbound

Massive Activations in Large Language Models cites this paper.

Massive Activations in Large Language Models Understanding and Overcoming the Challenges of Efficient Transformer Quantization

Reference 107

Resolution: verified exact; arxiv_id, observed 2026-05-16T07:02:53.968703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 46096209-e9cd-482a-8745-83417ccf525d · inbound

Post-Training Quantization of Generative and Discriminative LSTM Text Classifiers: A Study of Calibration, Class Balance, and Robustness cites this paper.

Post-Training Quantization of Generative and Discriminative LSTM Text Classifiers: A Study of Calibration, Class Balance, and Robustness Understanding and Overcoming the Challenges of Efficient Transformer Quantization

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T17:55:14.109364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49ff8c98-eafd-4f81-bb6b-602d93bc7237 · inbound

I-Segmenter: Integer-Only Vision Transformer for Efficient Semantic Segmentation cites this paper.

I-Segmenter: Integer-Only Vision Transformer for Efficient Semantic Segmentation Understanding and Overcoming the Challenges of Efficient Transformer Quantization

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T17:57:09.346300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8653d2c7-9cb7-43bd-8f0d-526ea9e400b7 · inbound

A Comprehensive FP8 Training Recipe for Reasoning-Enhanced Language Models cites this paper.

A Comprehensive FP8 Training Recipe for Reasoning-Enhanced Language Models Understanding and Overcoming the Challenges of Efficient Transformer Quantization

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-04T14:51:28.491836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d9a76ec-d298-49ca-97e6-b9bcb050be85 · inbound

MUXQ: Mixed-to-Uniform Precision MatriX Quantization via Low-Rank Outlier Decomposition cites this paper.

MUXQ: Mixed-to-Uniform Precision MatriX Quantization via Low-Rank Outlier Decomposition Understanding and Overcoming the Challenges of Efficient Transformer Quantization

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-10T23:30:50.803740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d3029044-f5a8-4af6-aa63-fc8efe78c83b · inbound

$\text{Log}_\text{b}$Quant: Quantizing Language Models in Logarithmic Space cites this paper.

$\text{Log}_\text{b}$Quant: Quantizing Language Models in Logarithmic Space Understanding and Overcoming the Challenges of Efficient Transformer Quantization

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-07-02T12:36:56.031421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c1bb3eca-1d65-4534-ab2a-c7672dd1587e · inbound

MXSens: Sensitivity-Aware Mixed-Precision Quantization for Efficient LLM Inference cites this paper.

MXSens: Sensitivity-Aware Mixed-Precision Quantization for Efficient LLM Inference Understanding and Overcoming the Challenges of Efficient Transformer Quantization

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-01T17:12:27.428735Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.