Paper Citation Record · LEDGER

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models

As of 20 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 2 inbound Pith citation observations for arXiv:2506.20251.

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

pith.paper-citation-record.v1
2506.20251 v1

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:00:19.643921Z

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-14T08:45:52.855783Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T02:13:30.051815Z

Reference resolution

49 of 49 outbound references displayed

verified exact2
verified fuzzy1
unresolved45
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5e0785be-b6c2-490b-8182-a791103ad961 · outbound

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

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.487900Z

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Observation 4539ba0d-6f7a-472c-a27c-c1b85ec456a7 · outbound

This paper cites Quantifying the Capabilities of LLMs across Scale and Precision.

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models Quantifying the Capabilities of LLMs across Scale and Precision

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.492020Z

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Observation 00875733-8dc6-4479-b87f-39693db4771b · outbound

This paper cites Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback.

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.495735Z

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Observation d9fbfd4e-e824-401d-b391-772d2b489a83 · outbound

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

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models INT2.1: Towards Fine-Tunable Quantized Large Language Models with Error Correction through Low-Rank Adaptation

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.503155Z

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Observation fbfdd1f4-5006-4668-ad4d-d7defadad16f · outbound

This paper cites Why Should Adversarial Perturbations be Imperceptible? Rethink the Research Paradigm in Adversarial NLP.

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models Why Should Adversarial Perturbations be Imperceptible? Rethink the Research Paradigm in Adversarial NLP

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.506346Z

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Observation 689babd4-9ad4-4521-843a-937a500f0bd1 · outbound

This paper cites TEQ: Trainable Equivalent Transformation for Quantization of LLMs.

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models TEQ: Trainable Equivalent Transformation for Quantization of LLMs

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-08-06T23:00:19.965307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d33b3879-494b-40f1-a65a-20f6c9abcd64 · outbound

This paper cites UltraFeedback: Boosting Language Models with Scaled AI Feedback.

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models UltraFeedback: Boosting Language Models with Scaled AI Feedback

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.516351Z

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Observation 9eda0494-dd20-4f21-be98-f0f98ace6a74 · outbound

This paper cites SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression.

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.519528Z

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Observation 8ad88c67-5de8-455f-90cc-bd4460508410 · outbound

This paper cites Enhancing Chat Language Models by Scaling High-quality Instructional Conversations.

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models Enhancing Chat Language Models by Scaling High-quality Instructional Conversations

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.522619Z

Source-reported events for the cited work

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Observation 1ae8183d-82e0-46cc-9bf1-0bb9076891e9 · outbound

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

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models BitDistiller: Unleashing the Potential of Sub-4-Bit LLMs via Self-Distillation

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.525721Z

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Observation 64ba23fe-bd76-43e3-8320-52f2e528e5f8 · outbound

This paper cites Exploiting LLM Quantization.

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models Exploiting LLM Quantization

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.528854Z

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Observation 58eaad20-086d-4325-9ae9-7323145700c7 · outbound

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

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models Extreme Compression of Large Language Models via Additive Quantization

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.532049Z

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Observation 3340f34a-0738-4f92-a433-a33eb67a963e · outbound

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

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.539701Z

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Observation 60016d0c-8bf3-48c2-b1e7-caa4e00fe9b7 · outbound

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

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models LQ-LoRA: Low-rank Plus Quantized Matrix Decomposition for Efficient Language Model Finetuning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.542797Z

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Observation 716ca101-91a8-4787-99ac-ca851702663f · outbound

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

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models LoRA+: Efficient Low Rank Adaptation of Large Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.546271Z

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Observation 0ca9828c-5f3b-459c-9652-10c4bb43c315 · outbound

This paper cites From Words to Actions: Unveiling the Theoretical Underpinnings of LLM-Driven Autonomous Systems.

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models From Words to Actions: Unveiling the Theoretical Underpinnings of LLM-Driven Autonomous Systems

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-08-06T23:00:19.872934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 56b4a5db-6959-4436-9fa4-fb83cdcf6016 · outbound

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

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.552626Z

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Observation 4e63ccb5-8ef6-4bcf-a40c-d785d3254895 · outbound

This paper cites Catastrophic Jailbreak of Open-source LLMs via Exploiting Generation.

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models Catastrophic Jailbreak of Open-source LLMs via Exploiting Generation

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.555633Z

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Observation 53dfb406-e291-4a4b-badf-f4e1a106241a · outbound

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

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models SqueezeLLM: Dense-and-Sparse Quantization

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.558832Z

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Observation e85c48a5-6869-4fa6-a91f-b814b854d16e · outbound

This paper cites QUICK: Quantization-aware Interleaving and Conflict-free Kernel for efficient LLM inference.

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models QUICK: Quantization-aware Interleaving and Conflict-free Kernel for efficient LLM inference

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.562688Z

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Observation d6ce4aef-7da2-4931-a3a7-8f5f2d8ea19b · outbound

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

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.569973Z

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Observation 7581cd33-ceb0-42cc-8e90-1deb6d8272e1 · outbound

This paper cites HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal.

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.573170Z

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Observation a274cb67-87a7-462f-9018-4af02697adeb · outbound

This paper cites Outliers and Calibration Sets have Diminishing Effect on Quantization of Modern LLMs.

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models Outliers and Calibration Sets have Diminishing Effect on Quantization of Modern LLMs

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.576498Z

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Observation 9d15065a-dc73-4f80-8dce-f8478c36e740 · outbound

This paper cites Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!.

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.583683Z

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Observation 6d222a10-dc3c-43b4-a92f-a14a9784836f · outbound

This paper cites Position: Understanding LLMs Requires More Than Statistical Generalization.

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models Position: Understanding LLMs Requires More Than Statistical Generalization

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.586821Z

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Observation 0996d68a-fd79-417b-a84d-e650e408bd8b · outbound

This paper cites PB-LLM: Partially Binarized Large Language Models.

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models PB-LLM: Partially Binarized Large Language Models

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.590254Z

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Observation 39d67b9d-8413-474a-82c7-dcfcc9e8db8e · outbound

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

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.593559Z

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Observation 9349d506-9723-4722-8c1d-6ac5b156a399 · outbound

This paper cites A StrongREJECT for Empty Jailbreaks.

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models A StrongREJECT for Empty Jailbreaks

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.597335Z

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Observation 498f0760-32de-46d1-ad71-287ca6a6e97c · outbound

This paper cites Gemma 2: Improving Open Language Models at a Practical Size.

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models Gemma 2: Improving Open Language Models at a Practical Size

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.601286Z

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Observation bfd6f8d0-9bf1-40e0-93b6-c105454220da · outbound

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

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.604475Z

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Observation 9b293a47-23d1-4807-8d7a-b34cb4df8079 · outbound

This paper cites Zephyr: Direct Distillation of LM Alignment.

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models Zephyr: Direct Distillation of LM Alignment

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.607683Z

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Observation 32bf6349-d0e6-4e50-bce4-50b815969fc6 · outbound

This paper cites Outlier Suppression+: Accurate quantization of large language models by equivalent and optimal shifting and scaling.

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models Outlier Suppression+: Accurate quantization of large language models by equivalent and optimal shifting and scaling

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.611331Z

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Observation d1466df5-fb21-4e86-879e-5d9ad4bd481f · outbound

This paper cites HuggingFace's Transformers: State-of-the-art Natural Language Processing.

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models HuggingFace's Transformers: State-of-the-art Natural Language Processing

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.614654Z

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Observation 56838325-0136-47d9-a8c0-582bab515fe5 · outbound

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

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.617930Z

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Observation 401a0149-7bef-4eb7-95a5-cff96ea5e6e1 · outbound

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

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models OneBit: Towards Extremely Low-bit Large Language Models

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.621017Z

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Observation 3c95b49e-d931-464c-98ec-bb89f3495c16 · outbound

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

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models RPTQ: Reorder-based Post-training Quantization for Large Language Models

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.624008Z

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Observation 0f2d9e24-efd8-43c9-bf37-44c75b1e2e61 · outbound

This paper cites AIR-Bench 2024: A Safety Benchmark Based on Risk Categories from Regulations and Policies.

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models AIR-Bench 2024: A Safety Benchmark Based on Risk Categories from Regulations and Policies

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.627162Z

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Observation 80a66c5d-3841-47f2-9391-cd8c2d36cf8c · outbound

This paper cites Activation Approximations Can Incur Safety Vulnerabilities Even in Aligned LLMs: Comprehensive Analysis and Defense.

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models Activation Approximations Can Incur Safety Vulnerabilities Even in Aligned LLMs: Comprehensive Analysis and Defense

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.630547Z

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Observation 0365a828-9cb1-4377-b751-7c28b563deeb · outbound

This paper cites Universal and Transferable Adversarial Attacks on Aligned Language Models.

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models Universal and Transferable Adversarial Attacks on Aligned Language Models

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.633676Z

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Observation 45ed98f6-7de5-4da7-a5fd-2cee95970f5f · outbound

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Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models Unresolved cited work

Reference 47

Resolution: unresolved; raw_fallback, observed 2026-08-06T23:00:20.059874Z

Source-reported events for the cited work

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Observation db635d82-38aa-4af0-8cb0-13afb93fa4db · outbound

This paper cites ASRVanilla: Tested with system prompt:”You are a helpful assistant.

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models ASRVanilla: Tested with system prompt:”You are a helpful assistant

Reference 48

Resolution: malformed identifier; raw_fallback, observed 2026-08-06T23:00:20.050712Z

Source-reported events for the cited work

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Observation 6a5ff4c0-fa57-478d-b2a6-dde65acec5ab · outbound

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Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models Unresolved cited work

Reference 49

Resolution: unresolved; raw_fallback, observed 2026-08-06T23:00:20.040409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 53031d22-f6a6-49d8-938f-7cc3cf6f8c47 · outbound

This paper cites JailbreakRadar: Comprehensive Assessment of Jailbreak Attacks Against LLMs.

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models JailbreakRadar: Comprehensive Assessment of Jailbreak Attacks Against LLMs

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.513275Z

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Observation 7a90c41f-4898-42d3-86d6-c6a44e90120a · outbound

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Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models SALAD-Bench: A Hierarchical and Comprehensive Safety Benchmark for Large Language Models

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.566396Z

Source-reported events for the cited work

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Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models Instruction Tuning with GPT-4

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.579669Z

Source-reported events for the cited work

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Observation b4a0c716-2058-454d-83ed-a637157748f5 · outbound

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

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models HarmLevelBench: Evaluating Harm-Level Compliance and the Impact of Quantization on Model Alignment

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.499755Z

Source-reported events for the cited work

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Observation f7021a1b-5078-4ed8-8cf5-53e483c72be2 · outbound

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Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models GPT-4 Technical Report

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.480415Z

Source-reported events for the cited work

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Observation 5341d5a9-ed0c-4624-8130-c5348f4c79a9 · outbound

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Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models PaLM 2 Technical Report

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-06T23:00:19.484466Z

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Observation 730be733-a0db-446d-babf-ddc3c399ef90 · outbound

This paper cites Accessed: 2025-01-24.

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models Accessed: 2025-01-24

Reference 2025

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:00:20.071040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

Observation 1a36ddfb-7141-4243-95c9-f0d1c6cd1d7f · inbound

Knowledge Beyond Language: Bridging the Gap in Multilingual Machine Unlearning Evaluation cites this paper.

Knowledge Beyond Language: Bridging the Gap in Multilingual Machine Unlearning Evaluation Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-15T02:13:30.053304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 49685228-f86e-4eb3-901e-86c011bb2c24 · inbound

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

Reliability Scaling Laws for Quantized Large Language Models Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models

Reference 148

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

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Unavailable: canonical work link unavailable.