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Paper Citation Record · LEDGER

Safety Assessment of Chinese Large Language Models

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 25 inbound Pith citation observations for arXiv:2304.10436.

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

pith.paper-citation-record.v1
2304.10436 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 25 of 25 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:17:26.706992Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T01:07:30.335333Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation a7fe65c9-3ccf-478f-9be5-addbf3429d28 · inbound

GPTFUZZER: Red Teaming Large Language Models with Auto-Generated Jailbreak Prompts cites this paper.

GPTFUZZER: Red Teaming Large Language Models with Auto-Generated Jailbreak Prompts Safety Assessment of Chinese Large Language Models

Reference 54

Resolution
metadata mismatch
arxiv_id, observed 2026-05-15T06:25:21.054175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-15T06:25:20.966510Z digest=sha256:3aa85433934ceb8d794f532f393fc61fe68d1bcd30943adbc5b0227f556fe5c9

Observation 3ee1ec1a-2c2e-4059-b067-94352bba98d3 · inbound

DeepSeek LLM: Scaling Open-Source Language Models with Longtermism cites this paper.

DeepSeek LLM: Scaling Open-Source Language Models with Longtermism Safety Assessment of Chinese Large Language Models

Reference 146

Resolution
verified exact
arxiv_id, observed 2026-05-11T06:08:06.220864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-11T06:08:05.550346Z digest=sha256:8e0fd33d016677cf5e135b2e5c24c80c4392e43173e4ed2c1d255e168a532733

Observation 6a692cf6-0523-4533-80d4-4a56f9571983 · inbound

TrustLLM: Trustworthiness in Large Language Models cites this paper.

TrustLLM: Trustworthiness in Large Language Models Safety Assessment of Chinese Large Language Models

Reference 187

Resolution
metadata mismatch
arxiv_id, observed 2026-05-18T11:17:08.571399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-18T11:17:08.108565Z digest=sha256:639c61d3644d1f1c04c07c5de96a6899f1540196d75756666f9bcb08ef248a4a

Observation f2fd6df4-3a9e-4cb2-948f-6ef70dfd5402 · inbound

DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model cites this paper.

DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model Safety Assessment of Chinese Large Language Models

Reference 141

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verified exact
arxiv_id, observed 2026-05-11T05:36:27.206515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-11T05:36:26.207359Z digest=sha256:9bb0f10e70d11d70cf1c21f895f965c2f7e606961f05f354ec058c50338024bc

Observation 3ec50fd2-280b-4c61-8255-dc92afc44ef1 · inbound

WildGuard: Open One-Stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs cites this paper.

WildGuard: Open One-Stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs Safety Assessment of Chinese Large Language Models

Reference 31

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metadata mismatch
arxiv_id, observed 2026-05-17T16:25:14.891841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-17T16:25:14.744887Z digest=sha256:f12b063edbb9f0ad934b0f377d664d0c9cecd8a438fa6e76645cf232bfe43b5b

Observation 399528c1-27b8-4b54-9dc2-fea8369d4253 · inbound

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

Jailbreak Attacks and Defenses Against Large Language Models: A Survey Safety Assessment of Chinese Large Language Models

Reference 86

Resolution
metadata mismatch
arxiv_id, observed 2026-05-15T02:20:44.838488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-15T02:20:44.368219Z digest=sha256:3041ff0236b3d6b5232793f85ad9f3b7fe205a47f456e79a4984bad46b523535

Observation 86fa3827-6a84-4057-addf-83750dbedcec · inbound

The Scales of Justitia: A Comprehensive Survey on Safety Evaluation of LLMs cites this paper.

The Scales of Justitia: A Comprehensive Survey on Safety Evaluation of LLMs Safety Assessment of Chinese Large Language Models

Reference 39

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unresolved
no resolver link, observed 2026-08-07T10:17:26.706992Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:17:26.706992Z digest=sha256:6199dfebc81997b2916f1708d9f19d2b3c63607ce39d60e8e3e878bc9b58489e

Observation a8778340-3b0d-4dec-b31e-c5a21a7e5752 · inbound

Fine-Tuning Lowers Safety and Disrupts Evaluation Consistency cites this paper.

Fine-Tuning Lowers Safety and Disrupts Evaluation Consistency Safety Assessment of Chinese Large Language Models

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-06T23:33:39.890116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:33:39.890116Z digest=sha256:72a3b4e0be8359510a9314c7c3627a683319e7d76e270cba9ceef6ef91c738ad

Observation 78394735-2d95-427c-ad43-54c0195f69c9 · inbound

GaussMaster: An LLM-based Database Copilot System cites this paper.

GaussMaster: An LLM-based Database Copilot System Safety Assessment of Chinese Large Language Models

Reference 7

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unresolved
no resolver link, observed 2026-08-06T21:48:30.577413Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:48:30.577413Z digest=sha256:24ccbd892cef0823833d830a3cd608cdb8ce9e8a66f605a8f84514a92ab0b8a9

Observation dcd091c3-cdfe-43ca-aa4e-c8b61be00b0b · inbound

Does Math Reasoning Improve General LLM Capabilities? Understanding Transferability of LLM Reasoning cites this paper.

Does Math Reasoning Improve General LLM Capabilities? Understanding Transferability of LLM Reasoning Safety Assessment of Chinese Large Language Models

Reference 226

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verified exact
arxiv_id, observed 2026-05-19T01:01:10.137580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-19T01:01:09.840919Z digest=sha256:771ed902943efd0606b5daa0b9c4371e883ad68a8c70ea8ba5ae0b9493b45249

Observation b16ebd34-448b-436c-9fe3-8fc75f3a99b4 · inbound

Libra: Large Chinese-based Safeguard for AI Content cites this paper.

Libra: Large Chinese-based Safeguard for AI Content Safety Assessment of Chinese Large Language Models

Reference 22

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unresolved
no resolver link, observed 2026-08-06T12:17:38.703912Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:17:38.703912Z digest=sha256:528c292c766ce377597435d95206d25894c73f837de70863c5a2c9cc58c70034

Observation 5b00630f-055c-443e-b90e-8eec7e5ce2fa · inbound

A Comprehensive Evaluation framework of Alignment Techniques for LLMs cites this paper.

A Comprehensive Evaluation framework of Alignment Techniques for LLMs Safety Assessment of Chinese Large Language Models

Reference 30

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unresolved
no resolver link, observed 2026-08-05T20:43:20.510246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T20:43:20.510246Z digest=sha256:148eb521c80afe143b273bb187d57ba42c607f44e9841d6a0621aec816759a4b

Observation 30543690-372d-42ba-926f-8515079ba1fa · inbound

EPT Benchmark: Evaluation of Persian Trustworthiness in Large Language Models cites this paper.

EPT Benchmark: Evaluation of Persian Trustworthiness in Large Language Models Safety Assessment of Chinese Large Language Models

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-04T23:03:16.432583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T23:03:16.432583Z digest=sha256:57702c4d8cd53f5d65d275665199fc395840084809fff2f124a8afc9731b7ddf

Observation 50e9a650-1576-4307-a997-56c6542d7b07 · inbound

Paladin: Defending LLM-enabled Phishing Emails with a New Trigger-Tag Paradigm cites this paper.

Paladin: Defending LLM-enabled Phishing Emails with a New Trigger-Tag Paradigm Safety Assessment of Chinese Large Language Models

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-04T22:33:25.544372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T22:33:25.544372Z digest=sha256:ec82c163796b1100eeb77b88480374d4bf32a348a3b7193e6df575f51e85e9bf

Observation 64717eeb-59d7-4c39-9848-cadf5261bfce · inbound

SafeToolBench: Pioneering a Prospective Benchmark to Evaluating Tool Utilization Safety in LLMs cites this paper.

SafeToolBench: Pioneering a Prospective Benchmark to Evaluating Tool Utilization Safety in LLMs Safety Assessment of Chinese Large Language Models

Reference 2025

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unresolved
no resolver link, observed 2026-08-04T22:30:34.155084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T22:30:34.155084Z digest=sha256:12ee84442c1317a2ca5d60568461022be670a3516b666b22ee35e2575ffbd5ae

Observation cad58cab-3983-470c-b615-a40ec41ca9c8 · inbound

Certifiable Safe RLHF: Semantic Grounding and Fixed Penalty Constraint Optimization for Safer LLM Alignment cites this paper.

Certifiable Safe RLHF: Semantic Grounding and Fixed Penalty Constraint Optimization for Safer LLM Alignment Safety Assessment of Chinese Large Language Models

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-04T12:27:28.723743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T12:27:28.723743Z digest=sha256:49bd6b36ed16c22506d0785f5ec50ea2dd77ba8141583985ae17697341c0ef9c

Observation a7af2d15-d6fc-4dd6-a899-7e1ad6a5ae9e · inbound

OutSafe-Bench: A Benchmark for Multimodal Offensive Content Detection in Large Language Models cites this paper.

OutSafe-Bench: A Benchmark for Multimodal Offensive Content Detection in Large Language Models Safety Assessment of Chinese Large Language Models

Reference 50

Resolution
verified exact
arxiv_id, observed 2026-05-17T22:30:23.201586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-17T22:29:36.960961Z digest=sha256:6be5dbfead4a32281a2d5274aca0f9f54075faa9d57d0eef15e2e4b272124c6d

Observation 7a377562-7cf7-428d-9741-6f6845c9ee1b · inbound

To Lie or Not to Lie? Investigating The Biased Spread of Global Lies by LLMs cites this paper.

To Lie or Not to Lie? Investigating The Biased Spread of Global Lies by LLMs Safety Assessment of Chinese Large Language Models

Reference 32

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verified exact
arxiv_id, observed 2026-05-11T00:05:50.813915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-10T18:41:54.081628Z digest=sha256:afead74bbe4063a244028c0554c9f0f2f27469a171df447965d41d0a11b8a3ce

Observation a4a5c17f-b439-49f9-a3f7-cb602169d532 · inbound

VoxSafeBench: Not Just What Is Said, but Who, How, and Where cites this paper.

VoxSafeBench: Not Just What Is Said, but Who, How, and Where Safety Assessment of Chinese Large Language Models

Reference 11

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verified exact
arxiv_id, observed 2026-05-10T10:24:22.093373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T10:19:28.041282Z digest=sha256:890753e048ac6a9ae222b622042c99e2b666b1cd75e257e3ea72179906331e0f

Observation d956385a-b5c1-4d45-aa07-32b34f477717 · inbound

TWGuard: A Case Study of LLM Safety Guardrails for Localized Linguistic Contexts cites this paper.

TWGuard: A Case Study of LLM Safety Guardrails for Localized Linguistic Contexts Safety Assessment of Chinese Large Language Models

Reference 17

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metadata mismatch
arxiv_id, observed 2026-05-10T09:08:25.527564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T09:07:57.713675Z digest=sha256:d1ea352418fcd86d0c228ec62ae3d83d644cc476087a1814c04abaa542fb7c54

Observation 0e02607a-7e51-4b8e-b9d3-1bee6f400f88 · inbound

Harder to Defend: Towards Chinese Toxicity Attacks via Implicit Enhancement and Obfuscation Rewriting cites this paper.

Harder to Defend: Towards Chinese Toxicity Attacks via Implicit Enhancement and Obfuscation Rewriting Safety Assessment of Chinese Large Language Models

Reference 23

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verified exact
arxiv_id, observed 2026-05-22T06:01:09.240505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-22T05:56:08.504337Z digest=sha256:c7066d95a7252f0e3a88c4eefb0713b53fc211bae461a8946c61216204aedad5

Observation 616c8f3c-9f67-4d6b-b323-81bd9a2cd733 · inbound

JT-SAFE-V2: Safety-by-Design Foundation Model with World-Context Data cites this paper.

JT-SAFE-V2: Safety-by-Design Foundation Model with World-Context Data Safety Assessment of Chinese Large Language Models

Reference 13

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verified exact
arxiv_id, observed 2026-06-30T13:54:44.158388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-30T13:45:38.305767Z digest=sha256:bdb259293b669faaa11eb4fc8f24e84d454fa9a335ba234cb7cd21f4964331fc

Observation 6c8c03d5-6ccb-4247-88a7-e45772ac4e2a · inbound

AlbanianLLMSafety: A Safety Evaluation Dataset for Large Language Models in Albanian cites this paper.

AlbanianLLMSafety: A Safety Evaluation Dataset for Large Language Models in Albanian Safety Assessment of Chinese Large Language Models

Reference 2

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T17:53:47.027493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-29T17:50:46.802662Z digest=sha256:96ea38c6996c977f5c9da8c2261385eb39c3681542aac00f9393a83f7aabd0a7

Observation df8c5b28-3b3c-400d-9ef0-a626a3721cbf · inbound

Beyond English and Evasion: A Human-Annotated Multi-Domain Benchmark for High-Stakes LLM Safety Evaluation in Chinese cites this paper.

Beyond English and Evasion: A Human-Annotated Multi-Domain Benchmark for High-Stakes LLM Safety Evaluation in Chinese Safety Assessment of Chinese Large Language Models

Reference 9

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verified exact
arxiv_id, observed 2026-06-29T08:03:14.652464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-29T07:55:07.161442Z digest=sha256:faa9d4321b96dfd052fe0b9a76c297f10dae1bd91787819fb1faf5bfe458dca1

Observation a23c8900-76a3-4683-a09d-180a93164fb2 · inbound

Culturally-Adapted Red-Teaming Across East and Southeast Asian Contexts: A Methodological and Comparative Analysis cites this paper.

Culturally-Adapted Red-Teaming Across East and Southeast Asian Contexts: A Methodological and Comparative Analysis Safety Assessment of Chinese Large Language Models

Reference 12

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metadata mismatch
arxiv_id, observed 2026-07-03T01:07:30.337023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-27T16:48:54.802860Z digest=sha256:10832b05026621f6c51ec4fdcc765f97b9e7987eb5fcc79071b71c8fc42dbc84