Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
How do Large Language Models Navigate Conflicts between Honesty and Helpfulness?
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2402.07282.
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 2026-08-07T12:59:46.192236Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T10:48:02.422300Z
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 51262a20-3615-4009-b319-8df2320193ab · inbound
Accelerating RLHF Training with Reward Variance Increase cites this paper.
Accelerating RLHF Training with Reward Variance Increase How do Large Language Models Navigate Conflicts between Honesty and Helpfulness?
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:59:46.192236Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7be93626-a516-4606-8595-c8b613f77e11 · inbound
Training language models to be warm and empathetic makes them less reliable and more sycophantic cites this paper.
Training language models to be warm and empathetic makes them less reliable and more sycophantic How do Large Language Models Navigate Conflicts between Honesty and Helpfulness?
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T12:18:40.111118Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 29c415b1-cd38-41c4-badb-dfa71c9732b1 · inbound
Designing Psychometric Bias Measures for ChatBots: An Application to Racial Bias Measurement cites this paper.
Designing Psychometric Bias Measures for ChatBots: An Application to Racial Bias Measurement How do Large Language Models Navigate Conflicts between Honesty and Helpfulness?
Reference 17
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T22:12:51.780463Z
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 dfb45dc4-1bb2-41db-acdc-dd950484922b · inbound
Transition from Statistical to Hardware-Limited Scaling in Photonic Quantum State Reconstruction cites this paper.
Transition from Statistical to Hardware-Limited Scaling in Photonic Quantum State Reconstruction How do Large Language Models Navigate Conflicts between Honesty and Helpfulness?
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T22:25:15.261445Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 13771fb3-781a-4fc8-a9d6-8a186185d08b · inbound
Normative Robustness as a Frontier for Non-Verifiable Reasoning in LLMs cites this paper.
Normative Robustness as a Frontier for Non-Verifiable Reasoning in LLMs How do Large Language Models Navigate Conflicts between Honesty and Helpfulness?
Reference 103
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T10:48:02.423863Z
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.