Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
BeHonest: Benchmarking Honesty in Large Language Models
As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2406.13261.
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 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T20:38:34.500200Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T20:18:56.663568Z
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 1cc81a92-98cc-4197-9b84-da0c2dcf4763 · inbound
Exploring Consciousness in LLMs: A Systematic Survey of Theories, Implementations, and Frontier Risks cites this paper.
Exploring Consciousness in LLMs: A Systematic Survey of Theories, Implementations, and Frontier Risks BeHonest: Benchmarking Honesty in Large Language Models
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:09:50.708278Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4f920a70-598d-475b-82ab-86009dc57379 · inbound
MTCMB: A Multi-Task Benchmark Framework for Evaluating LLMs on Knowledge, Reasoning, and Safety in Traditional Chinese Medicine cites this paper.
MTCMB: A Multi-Task Benchmark Framework for Evaluating LLMs on Knowledge, Reasoning, and Safety in Traditional Chinese Medicine BeHonest: Benchmarking Honesty in Large Language Models
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:50:53.798081Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 716eb961-9bcf-48e3-8049-2dbe0bfc9589 · inbound
LLM-based Question-Answer Framework for Sensor-driven HVAC System Interaction cites this paper.
LLM-based Question-Answer Framework for Sensor-driven HVAC System Interaction BeHonest: Benchmarking Honesty in Large Language Models
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:43:58.189681Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 43f927cd-3bec-473e-9032-bf525bfac3e5 · inbound
Alignment and Safety in Large Language Models: Safety Mechanisms, Training Paradigms, and Emerging Challenges cites this paper.
Alignment and Safety in Large Language Models: Safety Mechanisms, Training Paradigms, and Emerging Challenges BeHonest: Benchmarking Honesty in Large Language Models
Reference 98
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:13:06.291665Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 75180596-08b1-4632-8046-36a663f80dea · inbound
Unlearners Can Lie: Evaluating and Improving Honesty in LLM Unlearning cites this paper.
Unlearners Can Lie: Evaluating and Improving Honesty in LLM Unlearning BeHonest: Benchmarking Honesty in Large Language Models
Reference 2
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-12T07:31:24.489114Z
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.
Observation 13d213e0-542c-436b-8658-ed6f6f6dc5d4 · inbound
Navigating the Sea of LLM Evaluation: Investigating Bias in Toxicity Benchmarks cites this paper.
Navigating the Sea of LLM Evaluation: Investigating Bias in Toxicity Benchmarks BeHonest: Benchmarking Honesty in Large Language Models
Reference 3
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-12T05:31:23.935337Z
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.
Observation f48f2433-9f2c-487e-91e2-55c73e13ae0e · inbound
DECOR: Auditing LLM Deception via Information Manipulation Theory cites this paper.
DECOR: Auditing LLM Deception via Information Manipulation Theory BeHonest: Benchmarking Honesty in Large Language Models
Reference 21
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T06:28:05.381264Z
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.
Observation bf0bdbc0-8745-477a-894d-c71c971ee0a0 · inbound
SPADE-Bench: Evaluating Spontaneous Strategic Deception in Agents via Plan-Action Divergence cites this paper.
SPADE-Bench: Evaluating Spontaneous Strategic Deception in Agents via Plan-Action Divergence BeHonest: Benchmarking Honesty in Large Language Models
Reference 2
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-01T23:06:20.590107Z
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.
Observation cfbb8b37-c1c3-4263-bdd6-9f2c03bfb24b · inbound
SPADE-Bench: Evaluating Spontaneous Strategic Deception in Agents via Plan-Action Divergence cites this paper.
SPADE-Bench: Evaluating Spontaneous Strategic Deception in Agents via Plan-Action Divergence BeHonest: Benchmarking Honesty in Large Language Models
Reference 2
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-06-30T10:54:36.985886Z
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.
Observation d33f246a-485b-4c20-9b3e-204721c35d77 · inbound
RogueAI: A Reverse Turing Test for Detecting Licensed AI Deception in Dialogue cites this paper.
RogueAI: A Reverse Turing Test for Detecting Licensed AI Deception in Dialogue BeHonest: Benchmarking Honesty in Large Language Models
Reference 21
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T15:18:33.688342Z
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.
Observation 05a3b2ca-af7e-45c6-bd80-db214128ad5e · inbound
Decoding Hidden Deception in Reasoning LLMs: Activation Explainers for Deception Auditing cites this paper.
Decoding Hidden Deception in Reasoning LLMs: Activation Explainers for Deception Auditing BeHonest: Benchmarking Honesty in Large Language Models
Reference 3
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-03T20:18:56.665646Z
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.
Observation fc86b4ff-f50e-443f-b78b-adfa071959e4 · inbound
From Values to Benchmarks: Evaluating Large Language Models for Governmental Use in Dutch cites this paper.
From Values to Benchmarks: Evaluating Large Language Models for Governmental Use in Dutch BeHonest: Benchmarking Honesty in Large Language Models
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T04:15:50.166929Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fc96404e-bfe2-44c4-a015-a4e9f1703cff · inbound
Discovering Efficient and Explainable Communication Topologies for LLM-based Multi-Agent Systems via Causal Inference cites this paper.
Discovering Efficient and Explainable Communication Topologies for LLM-based Multi-Agent Systems via Causal Inference BeHonest: Benchmarking Honesty in Large Language Models
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T20:38:34.500200Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4ad81314-3d72-4c7c-b999-843c4ecb3b3c · inbound
How Do VLMs Behave When Blind or Misled? Behavioral Evaluation of VLMs on Scientific Figures cites this paper.
How Do VLMs Behave When Blind or Misled? Behavioral Evaluation of VLMs on Scientific Figures BeHonest: Benchmarking Honesty in Large Language Models
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T15:06:26.693276Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.