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Paper Citation Record · LEDGER

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs

As of 9 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 2 inbound Pith citation observations for arXiv:2508.19432.

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

pith.paper-citation-record.v1
2508.19432 v1

Coverage vector

measured 58 of 58 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T15:52:45.122017Z

measured 60 of 60 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T14:11:08.660471Z

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

58 of 58 outbound references displayed

  • verified exact2
  • verified fuzzy0
  • unresolved56
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 11a400df-adca-4bcc-bbd8-996e85a5a47e · outbound

This paper cites GPT-4 Technical Report.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs GPT-4 Technical Report

Reference 1

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:52:44.830664Z digest=sha256:8ec7dd5402c5d33f08d19b03c56dcf0bb56755c97a8f24ecbe43bb49f9873dcf

Observation 13f8ce39-b6ce-41d9-bbe2-e80e1564b1a6 · outbound

This paper cites an unresolved cited work.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs Unresolved cited work

Reference 2

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raw_fallback, observed 2026-08-05T15:52:46.112755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:52:44.836388Z digest=sha256:7b27c8155bd31c28e79def7f038c0e4c0533dc25cb3d43c0dd5e659535c03715

Observation 067f2c01-8786-4228-a802-cc41c75cdd45 · outbound

This paper cites The Internal State of an LLM Knows When It's Lying.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs The Internal State of an LLM Knows When It's Lying

Reference 3

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no resolver link, observed 2026-08-05T15:52:44.842479Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:52:44.842479Z digest=sha256:590337d0704939f853a7e1b66504d1b80bad22cae3510816aed076a307b9206d

Observation dd55b223-7514-4b9c-98b6-d4f195425413 · outbound

This paper cites HarmLevelBench: Evaluating Harm-Level Compliance and the Impact of Quantization on Model Alignment.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs HarmLevelBench: Evaluating Harm-Level Compliance and the Impact of Quantization on Model Alignment

Reference 4

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:52:44.847568Z digest=sha256:e1ba936fd0cf1e99d59701f4c493954ed5bd2a19775d0330770f9707876adcca

Observation 4a185ee7-7fe7-4312-80e1-2d3011deda79 · outbound

This paper cites Truth is Universal: Robust Detection of Lies in LLMs.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs Truth is Universal: Robust Detection of Lies in LLMs

Reference 5

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source=arxiv_source observed=2026-08-05T15:52:44.853521Z digest=sha256:bb6a37d8f5d5e7ccf51c43715e613add32680fa1599cc08888c8386e836f5096

Observation 34721bb2-9705-4205-8fb2-c98b1cc3fd4e · outbound

This paper cites Discovering Latent Knowledge in Language Models Without Supervision.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs Discovering Latent Knowledge in Language Models Without Supervision

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:52:44.867137Z digest=sha256:e2850337a58c998296aef4ec022ca69fa7afbd5b22e86299e1839abafbcdc90f

Observation 532f346b-bf62-476d-9d95-24477cb4d118 · outbound

This paper cites Explore, Establish, Exploit: Red Teaming Language Models from Scratch.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs Explore, Establish, Exploit: Red Teaming Language Models from Scratch

Reference 7

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source=arxiv_source observed=2026-08-05T15:52:44.872573Z digest=sha256:40e29504d377b95e6ba7002c0f64a891c7579f22577b62a9ee4456e076a321c0

Observation 200862cd-924e-415c-889b-9bcebea329f2 · outbound

This paper cites INT2.1: Towards Fine-Tunable Quantized Large Language Models with Error Correction through Low-Rank Adaptation.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs INT2.1: Towards Fine-Tunable Quantized Large Language Models with Error Correction through Low-Rank Adaptation

Reference 8

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source=arxiv_source observed=2026-08-05T15:52:44.877779Z digest=sha256:b535ecd56155adb11c6f32fd65bfed036936e8493c39c7b96733887f70e2b96f

Observation 6470bd67-c79b-4b19-b402-96bf9275aff0 · outbound

This paper cites DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models

Reference 9

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source=arxiv_source observed=2026-08-05T15:52:44.883513Z digest=sha256:e175365391f9f3014b187e5a3731eee1645d08167cd3770e6b3a093720ec7270

Observation 699c9967-9a62-41f3-837f-6b8f0ccd945b · outbound

This paper cites an unresolved cited work.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs Unresolved cited work

Reference 10

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source=arxiv_source observed=2026-08-05T15:52:44.888234Z digest=sha256:1e3166910b1e2312a0c397a5dcec929e305aff5b57e91f5b8f8609649d51b304

Observation 1fa332ee-f1d5-405e-b287-ff37af7eb41d · outbound

This paper cites BitDistiller: Unleashing the Potential of Sub-4-Bit LLMs via Self-Distillation.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs BitDistiller: Unleashing the Potential of Sub-4-Bit LLMs via Self-Distillation

Reference 11

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source=arxiv_source observed=2026-08-05T15:52:44.893150Z digest=sha256:181063e4a2bf55c9e6cd26257b93df760582124c77321b6ee041609d87996de2

Observation b8c67ab1-714c-4d8c-8f36-95b5cd19b449 · outbound

This paper cites The Llama 3 Herd of Models.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs The Llama 3 Herd of Models

Reference 12

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source=arxiv_source observed=2026-08-05T15:52:44.897942Z digest=sha256:1410efd36ca1012dcb7e56471765ef22062a7f8e72acb6c90c514a94f732639e

Observation de39af27-0440-4f44-930f-c3680bf270bd · outbound

This paper cites Exploiting LLM Quantization.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs Exploiting LLM Quantization

Reference 13

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source=arxiv_source observed=2026-08-05T15:52:44.902789Z digest=sha256:a49e70e10423b9c91f72ba807d48c3ec30c522f724033f829fb664a3993e2f6e

Observation dfc0ec88-b4a0-4c5d-9b0e-e792557c7531 · outbound

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

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs Extreme Compression of Large Language Models via Additive Quantization

Reference 14

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source=arxiv_source observed=2026-08-05T15:52:44.907408Z digest=sha256:41de5cb8ed5ffdb2d10b1ea21e22eae79791f9683318a1858e224bdbb3bf17f3

Observation 7c582569-8c34-4bca-b7eb-8cf4c4ccefab · outbound

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

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers

Reference 15

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source=arxiv_source observed=2026-08-05T15:52:44.912164Z digest=sha256:dd6090897e16cfd5f505788fa60ec5473a73d10eda623e3adaf1d5f983c411a7

Observation 33d3a558-db79-4d6e-ad9d-44376d97b26c · outbound

This paper cites an unresolved cited work.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs Unresolved cited work

Reference 16

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source=arxiv_source observed=2026-08-05T15:52:44.916835Z digest=sha256:65a26cebdb8edf6a413563b9f24b54815d49ca87e06ff10e460178feedca85b4

Observation 4fb24caf-2ba6-4d6a-9a97-85d9d3f898bc · outbound

This paper cites LQ-LoRA: Low-rank Plus Quantized Matrix Decomposition for Efficient Language Model Finetuning.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs LQ-LoRA: Low-rank Plus Quantized Matrix Decomposition for Efficient Language Model Finetuning

Reference 17

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source=arxiv_source observed=2026-08-05T15:52:44.921539Z digest=sha256:65a9e538f326ceaf26e6248021f8a67a8a295466037062d345fdb5f762ef178c

Observation 751c0867-feb2-4d66-8538-2c0d605eba52 · outbound

This paper cites an unresolved cited work.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs Unresolved cited work

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:52:44.926706Z digest=sha256:0cca469d79a9e87cad181a4be85b16c41d673a5e441c22952c799b7fab667dda

Observation 3794c98a-133b-4e0f-ad9c-3747afa29340 · outbound

This paper cites LoRA+: Efficient Low Rank Adaptation of Large Models.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs LoRA+: Efficient Low Rank Adaptation of Large Models

Reference 19

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source=arxiv_source observed=2026-08-05T15:52:44.931287Z digest=sha256:5269141a4963683de5b11694551ee4e22d9c325f747502bfed3193db6b787277

Observation ff60a444-4908-4f31-8bb4-749cd00c70f8 · outbound

This paper cites Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression

Reference 20

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source=arxiv_source observed=2026-08-05T15:52:44.936368Z digest=sha256:f51d4ea00a979ee6c1acaa8f7c1788b38ab688c941d96c5ad099d3f49689a7c0

Observation 42d02f77-18ab-4516-b832-a979ee974706 · outbound

This paper cites Mistral 7B.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs Mistral 7B

Reference 21

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:52:44.941127Z digest=sha256:2dc8e9910751bc11e96fe57519e2f62663ff1bee1a3bd3986fd5573113a87326

Observation bbd6d204-3edc-4be4-886d-2345406b4831 · outbound

This paper cites an unresolved cited work.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs Unresolved cited work

Reference 22

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:52:44.945564Z digest=sha256:8663a2e81c7b2c9e70e97d2871b0b8b6f4139529d909dad554a1dc692c2222f6

Observation 7aa8ef5c-c2e7-459f-b440-804064a16c33 · outbound

This paper cites SqueezeLLM: Dense-and-Sparse Quantization.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs SqueezeLLM: Dense-and-Sparse Quantization

Reference 23

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source=arxiv_source observed=2026-08-05T15:52:44.950132Z digest=sha256:c51c7e38d2fdbc431e5cd3e67c8795d76f3d722170947b6d6c08b8f53c51e1a9

Observation 24fbf338-10e4-4b55-8fd8-e96715e2d44d · outbound

This paper cites an unresolved cited work.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs Unresolved cited work

Reference 24

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:52:44.954783Z digest=sha256:a7180d3c9c569ee6e58f8079eb578f2f301343f57bc4ea67ff67b984c44f37b9

Observation bbbe0ef8-ddc7-4ec3-aac2-6476f3513623 · outbound

This paper cites OWQ: Outlier-Aware Weight Quantization for Efficient Fine-Tuning and Inference of Large Language Models.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs OWQ: Outlier-Aware Weight Quantization for Efficient Fine-Tuning and Inference of Large Language Models

Reference 25

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source=arxiv_source observed=2026-08-05T15:52:44.959022Z digest=sha256:3e541221db336cf8fa78abbd3048c232a87ad4edeb4292317d4f1850ae67d8cd

Observation 4dfac070-558c-4fa6-a56a-17a1845eff9e · outbound

This paper cites an unresolved cited work.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs Unresolved cited work

Reference 26

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:52:44.963641Z digest=sha256:8f82cb4f97943309c96a8b3eedf8c54c9801ded8487738e5a7062afb7eec9b93

Observation 225bd0eb-a63f-47bb-add8-958ac8a09b6e · outbound

This paper cites an unresolved cited work.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs Unresolved cited work

Reference 27

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:52:44.968498Z digest=sha256:11af0d373b5f0121e8d8a742aff155be20ceeae1803c35a3c02b9ee9f41a8ab4

Observation d63e35b2-fe0b-4e0d-bdcc-ba2b240cf54a · outbound

This paper cites LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models

Reference 28

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source=arxiv_source observed=2026-08-05T15:52:44.972851Z digest=sha256:e77dcc941f2c7c867e681c131c7c5b7b34e21018ff0e70331cd16ffe2a2b5aae

Observation 5e1a3d74-7acf-4518-81dd-db4f2899ca31 · outbound

This paper cites an unresolved cited work.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs Unresolved cited work

Reference 29

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:52:44.977603Z digest=sha256:4585c580207fe0563a162afd446a69a450be19b67d00d9ddd79ae92c1f343331

Observation 3927fc63-32d9-41c1-a2c4-0e88f31b4a08 · outbound

This paper cites TruthfulQA: Measuring How Models Mimic Human Falsehoods.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs TruthfulQA: Measuring How Models Mimic Human Falsehoods

Reference 30

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source=arxiv_source observed=2026-08-05T15:52:44.982184Z digest=sha256:42e24f34d21ceb891d2d42752e2d60f14f40b59461c63df8c964ccf5cc6cd99f

Observation 6d0c7454-be91-4a71-9872-4e4468443fe1 · outbound

This paper cites QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Models.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Models

Reference 31

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source=arxiv_source observed=2026-08-05T15:52:44.987170Z digest=sha256:84cf0f2219e2fde0391b4d4a88b030f91189c6840c9e66f0867ee33655bcf06a

Observation 6c8ae708-654e-4b8e-9995-e665688d7eef · outbound

This paper cites Do Emergent Abilities Exist in Quantized Large Language Models: An Empirical Study.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs Do Emergent Abilities Exist in Quantized Large Language Models: An Empirical Study

Reference 32

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source=arxiv_source observed=2026-08-05T15:52:44.992363Z digest=sha256:9377950c422c60bc1a8e442f32ccabe736a886debf17b5a8641b36be0d3a7b1d

Observation df962eed-6dcd-46ac-a387-c1fc943dcf18 · outbound

This paper cites LLM-QAT: Data-Free Quantization Aware Training for Large Language Models.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs LLM-QAT: Data-Free Quantization Aware Training for Large Language Models

Reference 33

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source=arxiv_source observed=2026-08-05T15:52:44.997182Z digest=sha256:e9532933a9356335915a21fa800331e95e202e5ebdaf6aa8c4cd73c85a49fbc8

Observation c36f15e2-7215-42dc-9825-61c32a2ec28b · outbound

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

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Reference 34

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source=arxiv_source observed=2026-08-05T15:52:45.002146Z digest=sha256:59978cfacef64fe613459474a4d260563bc8efc584efc16a71f89af8d33dd7b4

Observation 84054e03-2bd7-40af-b950-8dcdfb7f93e4 · outbound

This paper cites an unresolved cited work.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs Unresolved cited work

Reference 35

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:52:45.007027Z digest=sha256:83f512e48570129d5e74b1b5eb1a465e24e46cc93a28374a668d4166ec1f1ce9

Observation 4b130b9a-f695-4a17-8c92-06ed7ad516d3 · outbound

This paper cites The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets

Reference 36

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:52:45.011645Z digest=sha256:85f5338657af4e5dd05268a1fd67c62dcf33275aea109b438b39fcc1a28ee07b

Observation 0e192c90-f314-4baf-97c2-5421a626f6b5 · outbound

This paper cites Large Language Models Meet NLP: A Survey.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs Large Language Models Meet NLP: A Survey

Reference 37

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:52:45.016364Z digest=sha256:7ef815eb15f309830882610076fe966e6a06adfc572ebee038255dbf73b908a1

Observation 2cdc0f6c-d80c-42d0-8ba1-e0cd03e8420a · outbound

This paper cites SEPSIS: I Can Catch Your Lies -- A New Paradigm for Deception Detection.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs SEPSIS: I Can Catch Your Lies -- A New Paradigm for Deception Detection

Reference 38

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verified exact
local_arxiv, observed 2026-08-05T15:52:45.499814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:52:45.020958Z digest=sha256:c0855a8f040b1535d728bd9dabc72dc39ee2c6e9bdc8be7fc11d5689cf24e1b3

Observation e28914da-2d68-4a56-becc-d012126e74f7 · outbound

This paper cites Large Language Models can Strategically Deceive their Users when Put Under Pressure.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs Large Language Models can Strategically Deceive their Users when Put Under Pressure

Reference 39

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no resolver link, observed 2026-08-05T15:52:45.025680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:52:45.025680Z digest=sha256:77f3d6d5c2a8c7efc34589adffc65673746e24ac51b3f07b8e3bd4d2269d3376

Observation fc793817-40d7-4bb7-9839-2477fdb3e23d · outbound

This paper cites OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models

Reference 40

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:52:45.031065Z digest=sha256:6cb3771eb705514ab62a6f97ecf59936a8c2e3bf29e1192528ec7cfe1c2e391f

Observation 23fcb0bd-acfe-4e93-ba16-5694c86f0b57 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 41

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no resolver link, observed 2026-08-05T15:52:45.036046Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:52:45.036046Z digest=sha256:34a333f4003e26f76a1ddcb649b9d56ce7cdb5464ebbdc4b5e70db1056e74eef

Observation 0c106958-39d9-4aca-85ba-031dcddc8406 · outbound

This paper cites When Thinking LLMs Lie: Unveiling the Strategic Deception in Representations of Reasoning Models.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs When Thinking LLMs Lie: Unveiling the Strategic Deception in Representations of Reasoning Models

Reference 42

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no resolver link, observed 2026-08-05T15:52:45.041136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:52:45.041136Z digest=sha256:f8bd70d90ae57c1038c5f3c135bb54947d1aca9c42162d0ce84c48174b7b96ce

Observation 17f09e56-699b-4e61-bc78-9610976d72bc · outbound

This paper cites an unresolved cited work.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs Unresolved cited work

Reference 43

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raw_fallback, observed 2026-08-05T15:52:45.968564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:52:45.046660Z digest=sha256:1135a0bb4df6008ee9337f1be655859e25b1282a4322748cc351a0206a10a77f

Observation a9ce1493-4f2f-4368-bd5e-5187a4e624ee · outbound

This paper cites an unresolved cited work.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs Unresolved cited work

Reference 44

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no resolver link, observed 2026-08-05T15:52:45.051958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:52:45.051958Z digest=sha256:d0c92d1d660bcd8c386157105bd7b91d4d3b1911f425fd138d1d8870d0e525d4

Observation aaeeabe3-e4d4-431c-88e8-14a3d27e403e · outbound

This paper cites an unresolved cited work.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs Unresolved cited work

Reference 45

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no resolver link, observed 2026-08-05T15:52:45.057175Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:52:45.057175Z digest=sha256:2a2ec2038572f8c30a323a88ab4263286986f37d07a4cd463dcd914242e84bdb

Observation 218ca83a-32e5-47f8-aef5-3f8ff7839512 · outbound

This paper cites QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models

Reference 46

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no resolver link, observed 2026-08-05T15:52:45.062597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:52:45.062597Z digest=sha256:f4e594488970f0fda1df6e0fcdb4fd24b887b6bfaf3413fdd821d7fc6f8bae4a

Observation a828655e-af32-44f0-91a8-547b1247e065 · outbound

This paper cites OneBit: Towards Extremely Low-bit Large Language Models.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs OneBit: Towards Extremely Low-bit Large Language Models

Reference 47

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no resolver link, observed 2026-08-05T15:52:45.067539Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:52:45.067539Z digest=sha256:0f1897761725ca05355b74b55341d3c7619797920125a0f1f936c7dff9222956

Observation 7359eb8f-16cb-4164-be9c-24147f7a6b85 · outbound

This paper cites Beyond Perplexity: Multi-dimensional Safety Evaluation of LLM Compression.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs Beyond Perplexity: Multi-dimensional Safety Evaluation of LLM Compression

Reference 48

Resolution
verified exact
local_arxiv, observed 2026-08-05T15:52:45.274884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:52:45.073183Z digest=sha256:4041dba740bc99316799bca93b42151f2e48d8d59db7dd7f43f98a9314734d65

Observation ead1c449-f901-4945-9706-0997cf5be3f9 · outbound

This paper cites Qwen2.5 Technical Report.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs Qwen2.5 Technical Report

Reference 49

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:52:45.078051Z digest=sha256:719a2f9481541394215284d7263980bb0de2524cd7a327ef83f3eff43f3ca01f

Observation 098f5e3d-2fb8-4815-8a4f-6108a0d58254 · outbound

This paper cites an unresolved cited work.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs Unresolved cited work

Reference 50

Resolution
unresolved
raw_fallback, observed 2026-08-05T15:52:45.942585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-05T15:52:45.083106Z digest=sha256:7d5821e0bee22ab6cb1a822b29f24fa7ff7239511f0a929c3c17d0c472538c0d

Observation 53e56d0d-4e31-4984-af5b-30ac6e7003f2 · outbound

This paper cites Jailbreak Attacks and Defenses Against Large Language Models: A Survey.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs Jailbreak Attacks and Defenses Against Large Language Models: A Survey

Reference 51

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unresolved
no resolver link, observed 2026-08-05T15:52:45.088349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:52:45.088349Z digest=sha256:3de4512c85cc16bc66920cdd927b9e81a8b44ff00b84c09a30f9fc0fe39c2e6e

Observation 6644c61f-3f2d-4246-872a-185b49f7c556 · outbound

This paper cites RPTQ: Reorder-based Post-training Quantization for Large Language Models.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs RPTQ: Reorder-based Post-training Quantization for Large Language Models

Reference 52

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no resolver link, observed 2026-08-05T15:52:45.093167Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:52:45.093167Z digest=sha256:0443db29dfa73165dd92f7bd8810df59a33d93d7c2e3842790a2e4785fe94cf3

Observation 54327a6f-f6eb-4ba0-a299-d09721068a08 · outbound

This paper cites A Survey of Large Language Models.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs A Survey of Large Language Models

Reference 53

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no resolver link, observed 2026-08-05T15:52:45.098011Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:52:45.098011Z digest=sha256:35ab6dc7a0bc58cee938328b00c889be5704625b51714da0d77dd2ea48cd22f9

Observation 91ac271e-0468-4dd2-b2d1-672683a11b99 · outbound

This paper cites an unresolved cited work.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs Unresolved cited work

Reference 54

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no resolver link, observed 2026-08-05T15:52:45.102995Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:52:45.102995Z digest=sha256:f1a067e1e9295898feb9e2ecacc54447bc68601af0c24c08e7530e8ddb87297f

Observation 9281691d-b1ba-4272-b977-f8fc1035787a · outbound

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

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs A Survey on Efficient Inference for Large Language Models

Reference 55

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unresolved
no resolver link, observed 2026-08-05T15:52:45.107548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:52:45.107548Z digest=sha256:2338de98b91891220f7fb98ee694298e2a6e86017308e5cf2446f39ea5742bb7

Observation 65f374e7-d076-469c-89f0-38f6d2283401 · outbound

This paper cites ProSA: Assessing and Understanding the Prompt Sensitivity of LLMs.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs ProSA: Assessing and Understanding the Prompt Sensitivity of LLMs

Reference 56

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no resolver link, observed 2026-08-05T15:52:45.112544Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:52:45.112544Z digest=sha256:3eddf72dfae0df52921c4c43fa5547a613ad1dfb7755704e90b6309272d936ae

Observation 282784a2-0f4e-4f03-beaa-baf47060ac0e · outbound

This paper cites online" 'onlinestring :=.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs online" 'onlinestring :=

Reference 57

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no resolver link, observed 2026-08-05T15:52:45.117149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:52:45.117149Z digest=sha256:2ea607e0b70b29b4d5b3f9d986ae4e46e72839fb7f15595d2b480e2b5cfaf62b

Observation 57f80691-f258-4713-a8e9-e02b3dfa877e · outbound

This paper cites write newline.

Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs write newline

Reference 58

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:52:45.122017Z digest=sha256:92da113ac2ee0a9306384bf6f84ebb0f1717fb121f48e8e6ae6a1eff685522f8

Pith citing papers

Observation a272750b-2626-459e-8415-92d98daa8058 · 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 Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs

Reference 20

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verified exact
arxiv_id, observed 2026-05-10T02:38:17.189378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-10T02:32:50.182859Z digest=sha256:e620199b36bfeb099b905ed1ead128c93278267cfb9f6117ce468b373835c6c5

Observation 3cf375ff-4c82-4809-b00d-3f70caac7fc8 · 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 Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs

Reference 8

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no resolver link, observed 2026-08-01T14:11:08.660471Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:11:08.660471Z digest=sha256:a444bd0c9654d0e1ee236ae3ff4383134c84ee3d9a8336e67df096e0f17d804e