Paper Citation Record · LEDGER

Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach

As of 14 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2501.09107.

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

pith.paper-citation-record.v1
2501.09107 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:14:57.782249Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

42 of 42 outbound references displayed

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verified fuzzy5
unresolved37
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External citation measurements

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Outbound references

Observation 2b13fed0-58f9-458a-91ad-0aadfb755dc4 · outbound

This paper cites write newline.

Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach write newline

Reference 1

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Observation b9ca7613-10f5-427c-8388-4285c5b04ae2 · outbound

This paper cites an unresolved cited work.

Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach Unresolved cited work

Reference 2

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Observation d95f137f-524b-487f-b5e1-b7379a9ec5cc · outbound

This paper cites QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs.

Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs

Reference 3

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This paper cites Program Synthesis with Large Language Models.

Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach Program Synthesis with Large Language Models

Reference 4

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Observation 25b837f4-5cb1-4d76-9535-0d4ef1b782a9 · outbound

This paper cites an unresolved cited work.

Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach Unresolved cited work

Reference 5

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This paper cites an unresolved cited work.

Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach Unresolved cited work

Reference 6

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Observation 2c419ea2-b46b-43dc-a6ed-c92f459e484e · outbound

This paper cites an unresolved cited work.

Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach Unresolved cited work

Reference 7

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Observation 3f909076-f14c-4aac-a203-69b19cf45cc1 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach Evaluating Large Language Models Trained on Code

Reference 8

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Observation a03fa18a-3c39-4841-988c-7185a3bd41ca · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 9

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Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach Unresolved cited work

Reference 10

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This paper cites an unresolved cited work.

Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach Unresolved cited work

Reference 11

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Observation a1efe09d-e685-4625-9fb5-e42a89cc6097 · outbound

This paper cites an unresolved cited work.

Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach Unresolved cited work

Reference 12

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Observation 956d9e00-2d63-4feb-929a-4460bd6d6942 · outbound

This paper cites A., Egiazarian, V., Kuznedelev, D., Frantar, E., Ashkboos, S., Borzunov, A., Hoefler, T., and Alistarh, D.

Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach A., Egiazarian, V., Kuznedelev, D., Frantar, E., Ashkboos, S., Borzunov, A., Hoefler, T., and Alistarh, D

Reference 13

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Observation 3824d0e5-0d97-42f0-9a04-f34c739ab35c · outbound

This paper cites Extreme Compression of Large Language Models via Additive Quantization.

Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach Extreme Compression of Large Language Models via Additive Quantization

Reference 14

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Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach and Alistarh, D

Reference 15

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Observation 47c00fda-f0e4-475e-8f4a-c71407c10ad7 · outbound

This paper cites an unresolved cited work.

Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach Unresolved cited work

Reference 16

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Observation 7bf917fa-664d-47d8-b6ed-b8c47b714bb0 · outbound

This paper cites The Pile: An 800GB Dataset of Diverse Text for Language Modeling.

Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach The Pile: An 800GB Dataset of Diverse Text for Language Modeling

Reference 17

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Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach Unresolved cited work

Reference 18

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Observation 436e435e-aa83-48cc-b3f4-37ff8e07a5ca · outbound

This paper cites S., Tayaranian, M., Asgharian, M., and Partovi Nia, V.

Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach S., Tayaranian, M., Asgharian, M., and Partovi Nia, V

Reference 19

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This paper cites and Stork, D.

Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach and Stork, D

Reference 20

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Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach Unresolved cited work

Reference 21

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Observation 6b55a75c-fa8a-4943-9cb1-45a46314377d · outbound

This paper cites an unresolved cited work.

Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach Unresolved cited work

Reference 22

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Observation c3e39e70-b950-4f7b-87c1-6133f9d3318e · outbound

This paper cites AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration.

Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration

Reference 23

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Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving

Reference 24

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Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 25

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Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach Pointer Sentinel Mixture Models

Reference 26

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Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach A., Van Baalen, M., Louizos, C., and Blankevoort, T

Reference 27

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Observation 3fe7ec17-bc69-4f26-aea9-07e4a0090233 · outbound

This paper cites The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data, and Web Data Only.

Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data, and Web Data Only

Reference 28

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Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach Unresolved cited work

Reference 29

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Observation 75ab4bbb-5a9c-4f2e-933f-53db3269d1f2 · outbound

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Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach Code Llama: Open Foundation Models for Code

Reference 30

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Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach L., Bhagavatula, C., and Choi, Y

Reference 31

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Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach LLaMA: Open and Efficient Foundation Language Models

Reference 32

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Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 33

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Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach Unresolved cited work

Reference 34

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Observation c7bd6acf-dd72-4cfb-b190-b5f5bb371332 · outbound

This paper cites an unresolved cited work.

Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach Unresolved cited work

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This paper cites HellaSwag: Can a Machine Really Finish Your Sentence?.

Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach HellaSwag: Can a Machine Really Finish Your Sentence?

Reference 36

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Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach OPT: Open Pre-trained Transformer Language Models

Reference 37

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Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach Unresolved cited work

Reference 38

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Observation 63214e17-010f-476c-84f3-d49e9e2e1435 · outbound

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Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach Unresolved cited work

Reference 39

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Observation 8f6db896-561a-42c1-ba00-13823eaa0394 · outbound

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Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach Unresolved cited work

Reference 40

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Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach A Survey on Model Compression for Large Language Models

Reference 41

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Rethinking Post-Training Quantization: Introducing a Statistical Pre-Calibration Approach Unresolved cited work

Reference 42

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Pith citing papers

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