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Paper Citation Record · LEDGER

Evaluating Quantized Large Language Models

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 20 inbound Pith citation observations for arXiv:2402.18158.

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

pith.paper-citation-record.v1
2402.18158 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 20 of 20 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 20 of 20 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T05:56:55.140233Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

9
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation a641a9ca-a70c-44e2-9388-49afc993aa36 · inbound

A Survey on Efficient Inference for Large Language Models cites this paper.

A Survey on Efficient Inference for Large Language Models Evaluating Quantized Large Language Models

Reference 214

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metadata mismatch
arxiv_id, observed 2026-05-15T02:39:33.265457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-15T02:39:33.007894Z digest=sha256:5c030301a93f090a0724f4972ca8c5f625cb5ecabf494c6524bf58977cf3374c

Observation 862a78e2-e4d7-445d-a3fd-fd1aec2ef33e · inbound

Vision-Language and Large Language Model Performance in Gastroenterology: GPT, Claude, Llama, Phi, Mistral, Gemma, and Quantized Models cites this paper.

Vision-Language and Large Language Model Performance in Gastroenterology: GPT, Claude, Llama, Phi, Mistral, Gemma, and Quantized Models Evaluating Quantized Large Language Models

Reference 31

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verified exact
arxiv_id, observed 2026-05-23T22:18:31.866486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-23T22:15:52.638622Z digest=sha256:b8989d12d80d73e406c7e6ade23d13b36dfaff56090a5a75127c8184a8b76b01

Observation b6586653-72ae-4257-81b4-6bf90a70891a · inbound

Precision or Peril: A PoC of Python Code Quality from Quantized Large Language Models cites this paper.

Precision or Peril: A PoC of Python Code Quality from Quantized Large Language Models Evaluating Quantized Large Language Models

Reference 24

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metadata mismatch
arxiv_id, observed 2026-05-23T17:33:15.804739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-23T17:30:54.204300Z digest=sha256:2a10a407c3aeb46ad73e7372318a2ebe5a60855079afdb18c11cb939ebcaa5ee

Observation f2a28fcf-820d-414d-baf0-d4d999d9731b · inbound

Inference-time sparse attention with asymmetric indexing cites this paper.

Inference-time sparse attention with asymmetric indexing Evaluating Quantized Large Language Models

Reference 2022

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unresolved
no resolver link, observed 2026-08-08T05:56:55.140233Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T05:56:55.140233Z digest=sha256:7e6f2f603b4e7816fe83325afb3bb0f87937a16e89d9cee09159396e29b6101e

Observation 49c2c6c4-0842-4523-82b2-4b6c13b7baf4 · inbound

QM-ToT: A Medical Tree of Thoughts Reasoning Framework for Quantized Model cites this paper.

QM-ToT: A Medical Tree of Thoughts Reasoning Framework for Quantized Model Evaluating Quantized Large Language Models

Reference 9

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metadata mismatch
arxiv_id, observed 2026-05-22T19:45:03.999245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-22T19:44:16.630377Z digest=sha256:c032bc773d81958c6115b4b7a8317b61f3e269c345fc76ad1c14af33b857e032

Observation 791978d9-f2a4-4084-8f0a-e4bacc79b3eb · inbound

Rethinking the Outlier Distribution in Large Language Models: An In-depth Study cites this paper.

Rethinking the Outlier Distribution in Large Language Models: An In-depth Study Evaluating Quantized Large Language Models

Reference 19

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unresolved
no resolver link, observed 2026-08-07T13:30:39.231092Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:30:39.231092Z digest=sha256:10d9e6f449a860947ec834fe41b13fb786271c5bb5032706d070c6eedbb0d15b

Observation 28dadb7d-edbc-4464-bdb0-e51cb846929c · inbound

Pruning General Large Language Models into Customized Expert Models cites this paper.

Pruning General Large Language Models into Customized Expert Models Evaluating Quantized Large Language Models

Reference 26

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unresolved
no resolver link, observed 2026-08-07T11:27:14.258704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:27:14.258704Z digest=sha256:e887241a41b943235aaa8c591ea63d837ab933d38fff4dec51f6710e618788f1

Observation 8c4cb3a6-46e1-4183-bac2-86cdaabd1031 · inbound

Unifying Block-wise PTQ and Distillation-based QAT for Progressive Quantization toward 2-bit Instruction-Tuned LLMs cites this paper.

Unifying Block-wise PTQ and Distillation-based QAT for Progressive Quantization toward 2-bit Instruction-Tuned LLMs Evaluating Quantized Large Language Models

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-07T05:04:02.889275Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:04:02.889275Z digest=sha256:3ce2e563e5cec8bf180c3df61f6218de4102cb6cff347a47e541780a6509cfd2

Observation 1cede3b5-eac3-48a3-bf2d-db4b57c70020 · inbound

Edge-ASR: Towards Low-Bit Quantization of Automatic Speech Recognition Models cites this paper.

Edge-ASR: Towards Low-Bit Quantization of Automatic Speech Recognition Models Evaluating Quantized Large Language Models

Reference 12

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unresolved
no resolver link, observed 2026-08-06T18:33:17.787323Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:33:17.787323Z digest=sha256:4bd2ea61b0564763d77659ead24251ac4182b18cceb328ce0fc32d64b850d739

Observation 5321d1b0-82b7-4fe2-b846-3797573e3090 · inbound

Quantized Large Language Models in Biomedical Natural Language Processing: Evaluation and Recommendation cites this paper.

Quantized Large Language Models in Biomedical Natural Language Processing: Evaluation and Recommendation Evaluating Quantized Large Language Models

Reference 26

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unresolved
no resolver link, observed 2026-08-05T10:38:33.171501Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:38:33.171501Z digest=sha256:8d17517d77793d58c70caaf6fd7f7288759337ad286a721bff285bd3eb865394

Observation 994bf317-485b-406e-9b17-b7dc8e9239e8 · inbound

Are Large Language Models Economically Viable for Industry Deployment? cites this paper.

Are Large Language Models Economically Viable for Industry Deployment? Evaluating Quantized Large Language Models

Reference 53

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T13:01:18.858666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-10T02:28:12.686424Z digest=sha256:533f7b7738d27da28e1f4f9b67da304132092854e2595a156355db992e77ffdf

Observation be665ed4-b785-4c91-aa89-6a310314efce · inbound

From Signal Degradation to Computation Collapse: Uncovering the Two Failure Modes of LLM Quantization cites this paper.

From Signal Degradation to Computation Collapse: Uncovering the Two Failure Modes of LLM Quantization Evaluating Quantized Large Language Models

Reference 3

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T02:38:17.211730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-10T02:32:50.182859Z digest=sha256:64ab6dc49dacb7090e28538f70368f9f9c8a9ebc74616915831e9f8ecc05a4dd

Observation 9c61f32c-77f3-4168-b6dd-c6aabcdfd732 · inbound

Perplexity Can Miss SAE Feature Damage Under Quantization cites this paper.

Perplexity Can Miss SAE Feature Damage Under Quantization Evaluating Quantized Large Language Models

Reference 10

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T01:36:25.768691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-28T11:41:18.460538Z digest=sha256:2cd59cd9184df103999e4cdb7352701ac64d6cdde31bcdf28679456fefe866cb

Observation f3e9302a-6a15-4969-a71b-1c4e382d91d0 · inbound

Silent Failures in Quantized LLM Reasoning: A Taxonomy-Based Analysis of Hollow Convergence and Failure Mode Shifts cites this paper.

Silent Failures in Quantized LLM Reasoning: A Taxonomy-Based Analysis of Hollow Convergence and Failure Mode Shifts Evaluating Quantized Large Language Models

Reference 4

Resolution
unresolved
no resolver link, observed 2026-07-14T01:09:27.619062Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T01:09:27.619062Z digest=sha256:d96e83665602f004b51c3482fc43ffa471162da3875676464e791f5025f56e77

Observation aa195c14-2a97-447f-b0b5-67b817eb6da2 · inbound

Silent Failures in Quantized LLM Reasoning: A Taxonomy-Based Analysis of Hollow Convergence and Failure Mode Shifts cites this paper.

Silent Failures in Quantized LLM Reasoning: A Taxonomy-Based Analysis of Hollow Convergence and Failure Mode Shifts Evaluating Quantized Large Language Models

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-02T07:32:09.425235Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T07:32:09.425235Z digest=sha256:2a06914776354123794e9469db745507fff7837225a77e109df2ea8976d65e20

Observation d07172d7-c5a5-4169-ae9c-fa21a4da35a0 · inbound

Reliability Scaling Laws for Quantized Large Language Models cites this paper.

Reliability Scaling Laws for Quantized Large Language Models Evaluating Quantized Large Language Models

Reference 147

Resolution
unresolved
no resolver link, observed 2026-07-14T08:45:52.855783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-14T08:45:52.855783Z digest=sha256:518814ff817609944f72929c0591eca7e0d504a64ac7ecbc9514a274b604d072

Observation 77a50fc8-4e32-4fd5-abfa-13ed2c24cc7d · inbound

HindsightBench: A Black-Box Behavioral Audit Protocol for Parametric Hindsight in Time-Indexed LLM Decision Tasks cites this paper.

HindsightBench: A Black-Box Behavioral Audit Protocol for Parametric Hindsight in Time-Indexed LLM Decision Tasks Evaluating Quantized Large Language Models

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-01T14:11:08.947017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:11:08.947017Z digest=sha256:54776dbe089b9fbbb6a22dffda8f7d54156e567bb5ac2ed3169cc2c862d1faff

Observation 95b8362e-7bda-4fa3-97a6-70d21818ffdd · inbound

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines cites this paper.

Where Facts Go Missing: A Layerwise Taxonomy and Per-Layer Attribution of Information Omission in Air-Gapped LLMAgent Pipelines Evaluating Quantized Large Language Models

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-01T04:48:26.573189Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T04:48:26.573189Z digest=sha256:7206052cc53a36242d90883e6a603dea9503099a1bd5cf42d0404f06d7c1063e

Observation ec3223d8-5603-4358-8451-54a6824152ac · inbound

Studying quantization trade-offs for efficient inference deployment in machine translation cites this paper.

Studying quantization trade-offs for efficient inference deployment in machine translation Evaluating Quantized Large Language Models

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-03T07:51:21.284174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T07:51:21.284174Z digest=sha256:71f0c2e462a662c7be788f70488da9793b531a32b361b9097f21ea2c17eec1e6

Observation 21f944eb-a174-4f2c-8927-6569e53c812e · inbound

Studying quantization trade-offs for efficient inference deployment in machine translation cites this paper.

Studying quantization trade-offs for efficient inference deployment in machine translation Evaluating Quantized Large Language Models

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-05T04:25:21.969659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T04:25:21.969659Z digest=sha256:0be50c2f82e355e7dbb8492e6160af2fe3a91e33a54b4aea8166784f316e6ec9