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Paper Citation Record · LEDGER

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

As of 21 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 2026-08-20T06:33:59.587034+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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:52:44.830664Z digest=sha256:e386d015824817007b369a8684e46617ae3ab30eec35975b9c6ecc449d05a731

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 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T15:52:44.836388Z digest=sha256:c47fa9d30e78051e8cc344de52a8174333581e1ba9cdb3be36094d211c443604

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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source=arxiv_source observed=2026-08-05T15:52:44.842479Z digest=sha256:1250c9fc7a6529a590699c26d774e5270d1b3653975f8d977f170ed10202b8f0

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

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source=arxiv_source observed=2026-08-05T15:52:44.847568Z digest=sha256:0ce6597b21828c7ef8dca855f7913d8000d2e478875b805de276abde13072409

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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no resolver link, observed 2026-08-05T15:52:44.853521Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:52:44.853521Z digest=sha256:52e4be4b6e386e2c58e91218eb36898bf0e2b417ac376ad048f2c9f2907e6d69

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:b676cd6f8a44632500dac290f1d6f11493d78d65b806d513a9142dfbe41511ea

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:dd169f349535ebaded1e5eaefbd4c20c6fa675c6fb2375b1c029852df4104275

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=sha256:6ac1cdc027f611ab2f05495772c2dcdf8c241f2a15863fd303b5da2cdca2d213

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:be7c0803171d4caa46374d6de41bf2f2a42952eaa1e3cecd0fdb4be4466142c1

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:c9375a24946ff4c7df4312bb317b52cf8a38f66e57350dd2c48a31de979fe065

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=sha256:852b4b2dae68500e5e879d8bac4051f50c46695e62e7d7a7ff511394e14dee76

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:d551a51dc17cf70b2a9ee2fb2d5b8adb993b709383efac184a2a9204ed75f6ea

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=sha256:4f23c6e6badd2950e9517c4f4d9712ce3e904bb923b0e774b583ff80d55fe3b7

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:acf3d7f927bb3f84d4274478f32a557414eef80c01eaf740a4e1a77f460ed248

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=sha256:64fcc94f90065ecd00f083d6195397453295bab7b5cb9fde876d05bbdc656427

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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no resolver link, observed 2026-08-05T15:52:44.916835Z

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source=arxiv_source observed=2026-08-05T15:52:44.916835Z digest=sha256:dfaa45a2d3b861fdd129b278105200c583a257e7bb041d1f89f10a5319dc09bb

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=sha256:63b9bd0e2cfb41a18bb0abf43bca32f3b02fdf29e7438c1af48fc174b343b9c9

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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raw_fallback, observed 2026-08-05T15:52:46.086261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T15:52:44.926706Z digest=sha256:021019f617ba76e1044e7ce5c64f2ec5b351336cf82a0abf78187cf65aa350b4

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:d2b4564796f1916f109ba71bdc768528805ce9b94dc9c7846ffaadf69fa0748e

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:fa0db0222b368622ca4634713a530f1f219e78718562873e276eeee48f614238

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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source=arxiv_source observed=2026-08-05T15:52:44.941127Z digest=sha256:7adc5c4527ed2efc1a30b4298a2267b45fcb35e3b8263cf21ecd10f7f0b8ce2c

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 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T15:52:44.945564Z digest=sha256:7eac0ab79ca3b71d7a427587118f74e8955aebae54f70c68ef020992591b71b2

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:a5a8bb2fca842c7211ab8cf094c67b2e2434d8251c586ed5bc2885ac6b02b2e2

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 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T15:52:44.954783Z digest=sha256:13801ee256852b4e318d521ba32ca6e9abecd2e158c6d8487af0350dbd350144

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=sha256:2bb1b6cc337b6263ed12a12b79e66817bd8ca235d32390b8f8f2db42ed0e1294

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 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T15:52:44.963641Z digest=sha256:f1068f26874e0d32e77b69ec8226292b48fee1e81ffd134a24eb540ceb22a665

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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raw_fallback, observed 2026-08-05T15:52:46.018287Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T15:52:44.968498Z digest=sha256:a3f63b756658bcecf585c45d610157dde063a331b099d1a109365d67754e634d

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:f42f757e25e7a31542852bbbf39a1fd6beb19b749926ec9ab8145361aaa08eff

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T15:52:44.977603Z digest=sha256:51fc7ef6d2362b335e9c571072357f4a5ca610cc2a1b749756c506675f590b96

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=sha256:3e76716435da3d437d20f32e2026cd814d893681eac0c55f7dda0fae937e2448

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:a3cf76596dd66521ea8856659a6332ade73bc93670789dbdfb9c26686b84eb5c

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=sha256:299acd570a3269bc9cd3f21e5a03faa642425acaa0554690b2de5a48578d0616

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:d2184968d22345edc6a81243e78b7bc5ea0ca0f82dec2e0b6fd5b522b2bb2704

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:f92f581b9ffbb22df79214dc4f11fff6bf05d6b7a3668d2df603cfd85952b63f

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 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T15:52:45.007027Z digest=sha256:c4b63c84caa13dd35533b36f4aba501c2e9f2d2a493c287bf8ef73c2ed57cc3e

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:52:45.011645Z digest=sha256:3d25cf776e26bc96c84151817bfecb2264d220190a4975925219a0c8c7a804d7

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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no resolver link, observed 2026-08-05T15:52:45.016364Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:52:45.016364Z digest=sha256:792cd5eacc93b3d59fd9e7362684e0f1cf32187b3bc7f96c170b90f144cbf57b

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 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T15:52:45.020958Z digest=sha256:eede76ed3390f62763347f748b7d0fb7c3b2d0e4d94505c81200c05eb1a511a7

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:e109e5cfd224ff1a406f18900ce19f1aa6eea6424573dd08f7b7368dabfb0e10

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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no resolver link, observed 2026-08-05T15:52:45.031065Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:52:45.031065Z digest=sha256:4718a4b3f9f8bf0cb0ee6d73b8ec600848868606b2f5ff91d9ee971f12867923

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

Resolution
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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=sha256:5361adaa74656d3ce269c8be902478dcdc6f44c7d2117c18cfbbd112640a3a1e

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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unresolved
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=sha256:5a18b78e5b40a9d607d46ae1e1dee07ead896ed025f5be2834bbf9c912ce72f8

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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unresolved
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 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T15:52:45.046660Z digest=sha256:9aee9ccfdc51942bdb6d4b844cbfb506c0bc15e6e756815c8b1afac1796c6bba

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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unresolved
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:e71855cef1d36ab61a0eafec6dfe19696b48767582f77fb4d451ede12c2dc32a

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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unresolved
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:db190d125d80c913df97ed27af5e14151ae3a56a638f27248a73355663f8ac98

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=sha256:646be5a969663f3d86782e513c15cddd099e45860165d19d8c4375f94d5aa5ce

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=sha256:12fb3eb08f79949795e97270ead29ac90de861a6a3d24d7113cc4ead1ac6c915

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 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T15:52:45.073183Z digest=sha256:b0074216e93d02bf3e97f633add0c0c3e1b8a3705e4c613fd7475d259b36f4c9

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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no resolver link, observed 2026-08-05T15:52:45.078051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:52:45.078051Z digest=sha256:3aec59fbbbb901b7f8ae535a65b7d436d55a7afd1cbb210f58dd47b3bbe6e3d0

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 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-05T15:52:45.083106Z digest=sha256:901ba9df033040daf572b600c20361a4579aec44391aa3d9b08f1616898283f8

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

Resolution
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=sha256:5e54872d3eab64a53d7f568249d16ebfcb1f56eadde496f1294af978dd537d63

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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unresolved
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=sha256:5671d24c2c698254b75487c75b25eb311abe3e6c89ba7e13deb0fa77f0de256a

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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unresolved
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=sha256:7395e1fc829cd801bea7438c40cd543860c129c9927762a8f6308c8314f8b84c

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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unresolved
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:e26c38cd3421f72076bdcf80ae74133113baa5790c6faf7186414ed00d189b9e

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:deffb24fa3208a8b4fd73680853659cec49dc2b22447d853fe6222acbc062ec4

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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unresolved
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=sha256:61848fb3d8b2e6c7b5221b119a367e74fd16c87e8b123b63cf86b24a875dd052

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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unresolved
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=sha256:3f1019bba9cbac65e7df5c8e4c1ab66fdc3febe21c2c7e2028fb3b1be86b082c

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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unresolved
no resolver link, observed 2026-08-05T15:52:45.122017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:52:45.122017Z digest=sha256:1cc5317ab970ff5c223226618830a6a972735785c0d88336d3b0d0ece98dca69

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

Resolution
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 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-10T02:32:50.182859Z digest=sha256:32c8352ac979f6bbb5e4788ca74b22c793271369bde49620e2df8a2924fb00ce

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:a7b7c342457cf791546102c3428e13cc21beab1c4157ea633066042a3560ba3f