Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 26 inbound Pith citation observations for arXiv:2306.11698.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T13:40:35.417043Z
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
- parse uncertain0
- malformed identifier0
- metadata mismatch0
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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+00:00.
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
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T13:40:35.417043Z
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
Source-reported events for the cited work
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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+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 2026-08-08T06:32:00.761636+00:00.