Paper Citation Record · LEDGER

DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 34 inbound Pith citation observations for arXiv:2306.11698.

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

pith.paper-citation-record.v1
2306.11698 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 34 of 34 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T11:02:19.402504Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T20:00:07.922247Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
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malformed identifier0
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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 4db0a53b-787f-4a61-bfbe-dc41e1a074b8 · inbound

"Do Anything Now": Characterizing and Evaluating In-The-Wild Jailbreak Prompts on Large Language Models cites this paper.

"Do Anything Now": Characterizing and Evaluating In-The-Wild Jailbreak Prompts on Large Language Models DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Reference 84

Resolution: metadata mismatch; arxiv_id, observed 2026-05-17T08:39:28.148162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation fc20f52f-9f66-468a-80ee-38597e7048bb · 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 DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Reference 60

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:25:21.086517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7133d9f0-4fd0-4606-bbf8-076a4c12371c · inbound

TrustLLM: Trustworthiness in Large Language Models cites this paper.

TrustLLM: Trustworthiness in Large Language Models DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Reference 71

Resolution: verified exact; arxiv_id, observed 2026-05-18T11:17:08.434626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0210e987-d74d-4958-b911-c4fc9f579248 · inbound

Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models cites this paper.

Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Reference 110

Resolution: verified exact; arxiv_id, observed 2026-05-13T13:43:11.167893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 92ba5ce8-989e-458b-a320-97a0b8f4f39a · inbound

Harmful Fine-tuning Attacks and Defenses for Large Language Models: A Survey cites this paper.

Harmful Fine-tuning Attacks and Defenses for Large Language Models: A Survey DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Reference 154

Resolution: verified exact; arxiv_id, observed 2026-05-23T20:58:25.857135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 55b30acb-b6c2-4120-a2ad-d4f0a7e3c0c4 · inbound

Unveiling Performance Challenges of Large Language Models in Low-Resource Healthcare: A Demographic Fairness Perspective cites this paper.

Unveiling Performance Challenges of Large Language Models in Low-Resource Healthcare: A Demographic Fairness Perspective DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Reference 34

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Source-reported events for the cited work

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Observation c688595d-1906-4da0-ac98-231c039b2841 · inbound

Automated Extraction of Acronym-Expansion Pairs from Scientific Papers cites this paper.

Automated Extraction of Acronym-Expansion Pairs from Scientific Papers DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-12T04:43:58.753599Z

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Observation 2fda7b87-5c34-4be7-90b0-ff4483bb777b · inbound

Methods to Assess the UK Government's Current Role as a Data Provider for AI cites this paper.

Methods to Assess the UK Government's Current Role as a Data Provider for AI DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-12T11:02:19.402504Z

Source-reported events for the cited work

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Observation 7dd7d6ac-b7da-484a-8eb2-b093f7fc072f · inbound

On Adversarial Robustness and Out-of-Distribution Robustness of Large Language Models cites this paper.

On Adversarial Robustness and Out-of-Distribution Robustness of Large Language Models DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Reference 10

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Source-reported events for the cited work

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Observation cd03390e-9659-4c26-8995-3b5cd38df0b3 · inbound

Value Compass Benchmarks: A Platform for Fundamental and Validated Evaluation of LLMs Values cites this paper.

Value Compass Benchmarks: A Platform for Fundamental and Validated Evaluation of LLMs Values DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-10T20:53:59.851548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3355686f-75a9-4a76-ab65-d5a32a263c78 · inbound

MJ-VIDEO: Fine-Grained Benchmarking and Rewarding Video Preferences in Video Generation cites this paper.

MJ-VIDEO: Fine-Grained Benchmarking and Rewarding Video Preferences in Video Generation DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-09T14:50:57.942282Z

Source-reported events for the cited work

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Observation b219fbce-6ee7-4844-887d-2171c5551971 · inbound

Vulnerability Mitigation for Safety-Aligned Language Models via Debiasing cites this paper.

Vulnerability Mitigation for Safety-Aligned Language Models via Debiasing DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-09T13:14:34.113399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7cc4c40-8f05-42eb-87e2-f8bab05a5a8d · inbound

Online Aggregation of Trajectory Predictors cites this paper.

Online Aggregation of Trajectory Predictors DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 02b35cf5-23cd-4abb-b3f2-277592bb7ed5 · inbound

Bridging the Safety Gap: A Guardrail Pipeline for Trustworthy LLM Inferences cites this paper.

Bridging the Safety Gap: A Guardrail Pipeline for Trustworthy LLM Inferences DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-08T10:23:06.270812Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0955883b-c37d-4f8a-a42f-19e68cc01e40 · inbound

The Science of Evaluating Foundation Models cites this paper.

The Science of Evaluating Foundation Models DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-07T23:35:42.869827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f2c66839-14a2-4a52-bacd-ebdcea49ebbe · inbound

Position is Power: System Prompts as a Mechanism of Bias in Large Language Models (LLMs) cites this paper.

Position is Power: System Prompts as a Mechanism of Bias in Large Language Models (LLMs) DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-07T13:43:14.525588Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5724ed5a-dc59-49c0-9876-5279146e77aa · inbound

Aligned but Blind: Alignment Increases Implicit Bias by Reducing Awareness of Race cites this paper.

Aligned but Blind: Alignment Increases Implicit Bias by Reducing Awareness of Race DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-07T12:13:19.236371Z

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Unavailable: canonical work link unavailable.

Observation 7a3a8ecf-dfe8-4bb8-b2c8-cbb5955eb159 · inbound

MAGPIE: A dataset for Multi-AGent contextual PrIvacy Evaluation cites this paper.

MAGPIE: A dataset for Multi-AGent contextual PrIvacy Evaluation DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T22:47:24.374725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6b5dc35-8a3a-487e-aed3-02e7f334a5dc · inbound

BEAVER: An Efficient Deterministic LLM Verifier cites this paper.

BEAVER: An Efficient Deterministic LLM Verifier DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Reference 51

Resolution: metadata mismatch; arxiv_id, observed 2026-05-17T01:58:51.317326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ceb2946e-8705-4c94-98f1-18493444a687 · inbound

Beyond Context: Large Language Models' Failure to Grasp Users' Intent cites this paper.

Beyond Context: Large Language Models' Failure to Grasp Users' Intent DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-16T20:11:13.660619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 54ff72f6-97c3-4b95-aafd-7fa693fb6899 · inbound

Framing Instability in LLM Ethical Stance: Auditing Negation Sensitivity in Moral Dilemmas cites this paper.

Framing Instability in LLM Ethical Stance: Auditing Negation Sensitivity in Moral Dilemmas DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-03T07:03:15.134754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc07e591-05ae-4af4-8b5f-c04da5fad9d5 · inbound

Benchmark of Benchmarks: Unpacking Influence and Code Repository Quality in LLM Safety Benchmarks cites this paper.

Benchmark of Benchmarks: Unpacking Influence and Code Repository Quality in LLM Safety Benchmarks DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Reference 121

Resolution: metadata mismatch; arxiv_id, observed 2026-05-21T12:10:06.594229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5cacfdbf-d34c-4df6-b27c-e65578fe7111 · inbound

A Systematic Study of Training-Free Methods for Trustworthy Large Language Models cites this paper.

A Systematic Study of Training-Free Methods for Trustworthy Large Language Models DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Reference 49

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T08:22:37.342422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b1668728-b10d-40db-a4cc-b931a3c371ba · inbound

RLearner-LLM: Balancing Logical Grounding and Fluency in Large Language Models via Hybrid Direct Preference Optimization cites this paper.

RLearner-LLM: Balancing Logical Grounding and Fluency in Large Language Models via Hybrid Direct Preference Optimization DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:56:05.484799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a1eb1751-c4bf-4f96-a289-06bf31a45ae2 · inbound

RLearner-LLM: Balancing Logical Grounding and Fluency in Large Language Models via Hybrid Direct Preference Optimization cites this paper.

RLearner-LLM: Balancing Logical Grounding and Fluency in Large Language Models via Hybrid Direct Preference Optimization DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-12T07:21:26.471179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 527ad1e2-4ce9-4b72-8ab5-20ce8685977b · inbound

RLearner-LLM: Balancing Logical Grounding and Fluency in Large Language Models via Hybrid Direct Preference Optimization cites this paper.

RLearner-LLM: Balancing Logical Grounding and Fluency in Large Language Models via Hybrid Direct Preference Optimization DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-13T07:12:28.807805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4ee47a55-5feb-410b-9161-a7ba17536758 · inbound

RLearner-LLM: Balancing Logical Grounding and Fluency in Large Language Models via Hybrid Direct Preference Optimization cites this paper.

RLearner-LLM: Balancing Logical Grounding and Fluency in Large Language Models via Hybrid Direct Preference Optimization DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-02T14:53:23.078669Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47752c70-ef9a-488e-afc3-5eb0c072034a · inbound

CXR-ContraBench: Benchmarking Negated-Option Attraction in Medical VLMs cites this paper.

CXR-ContraBench: Benchmarking Negated-Option Attraction in Medical VLMs DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Reference 32

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T18:41:09.433527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation af6d18f2-de9f-480a-bd80-a9f876453f20 · inbound

Reducing Political Manipulation with Consistency Training cites this paper.

Reducing Political Manipulation with Consistency Training DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-22T05:34:40.195959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c2b48358-6547-4d20-86cc-21c5a292e836 · inbound

Reducing Political Manipulation with Consistency Training cites this paper.

Reducing Political Manipulation with Consistency Training DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-06-30T16:54:58.737164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c9077dec-4165-4e35-80a2-6375abd02c46 · inbound

A Paired Testing Protocol for Batch-Conditioned Refusal Robustness in LLM Serving cites this paper.

A Paired Testing Protocol for Batch-Conditioned Refusal Robustness in LLM Serving DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-06-29T18:03:47.862186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3c7c38b7-3822-42fc-92a9-47f016b3dfdb · inbound

Unveiling Privacy Risks in Multi-modal Large Language Models: Task-specific Vulnerabilities and Mitigation Challenges cites this paper.

Unveiling Privacy Risks in Multi-modal Large Language Models: Task-specific Vulnerabilities and Mitigation Challenges DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Reference 20

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T01:27:30.922163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6304b4f6-9dad-46ed-ae59-f3c6de2072be · inbound

Do Encoders Suffice? A Systematic Comparison of Encoder and Decoder Safety Judges for LLM Adversarial Evaluation cites this paper.

Do Encoders Suffice? A Systematic Comparison of Encoder and Decoder Safety Judges for LLM Adversarial Evaluation DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Reference 11

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T20:00:07.924444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 68a32cee-7b52-4259-8f3a-8fe60d1019e6 · inbound

From Interpretability to Control: Insights from Six Years of the TrustNLP Workshop cites this paper.

From Interpretability to Control: Insights from Six Years of the TrustNLP Workshop DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-12T04:51:16.888702Z

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Unavailable: canonical work link unavailable.