Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Developing Safe and Responsible Large Language Model : Can We Balance Bias Reduction and Language Understanding in Large Language Models?
As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2404.01399.
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 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T23:01:05.019358Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-22T20:25:05.458583Z
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 b1994f4a-8592-4206-8661-7595b712b042 · inbound
EQUATOR: A Deterministic Framework for Evaluating LLM Reasoning with Open-Ended Questions. # v1.0.0-beta cites this paper.
EQUATOR: A Deterministic Framework for Evaluating LLM Reasoning with Open-Ended Questions. # v1.0.0-beta Developing Safe and Responsible Large Language Model : Can We Balance Bias Reduction and Language Understanding in Large Language Models?
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T23:01:05.019358Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 75f9b1dc-4c0c-4cd1-8713-41f2ccd6892b · inbound
Optimizing Large Language Models: Metrics, Energy Efficiency, and Case Study Insights cites this paper.
Optimizing Large Language Models: Metrics, Energy Efficiency, and Case Study Insights Developing Safe and Responsible Large Language Model : Can We Balance Bias Reduction and Language Understanding in Large Language Models?
Reference 22
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T20:25:05.460231Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 79009b5f-8d94-4a22-8b2b-c0ad2f578f1e · inbound
Thinking Beyond Tokens: From Brain-Inspired Intelligence to Cognitive Foundations for Artificial General Intelligence and its Societal Impact cites this paper.
Thinking Beyond Tokens: From Brain-Inspired Intelligence to Cognitive Foundations for Artificial General Intelligence and its Societal Impact Developing Safe and Responsible Large Language Model : Can We Balance Bias Reduction and Language Understanding in Large Language Models?
Reference 273
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:07:11.584577Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.