Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-08T00:04:41.297220Z
Paper Citation Record · LEDGER
Ensemble based approach to quantifying uncertainty of LLM based classifications
As of 11 August 2026, this Paper Citation Record lists 9 of 9 outbound references and 0 inbound Pith citation observations for arXiv:2502.08631.
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 2026-08-11T06:34:44.6726+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
9 of 9 outbound references displayed
- verified exact0
- verified fuzzy7
- unresolved2
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation d5044e11-c43b-4ec1-a3ca-2eefa0ef74d6 · outbound
This paper cites LLM Lies: Hallucinations are not Bugs, but Features as Adversarial Examples.
Ensemble based approach to quantifying uncertainty of LLM based classifications LLM Lies: Hallucinations are not Bugs, but Features as Adversarial Examples
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T00:04:41.228134Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 42024140-99bd-416b-96cf-df967d5c775c · outbound
This paper cites LM-Polygraph: Uncertainty Estimation for Language Models,.
Ensemble based approach to quantifying uncertainty of LLM based classifications LM-Polygraph: Uncertainty Estimation for Language Models,
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T00:04:41.614062Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation f5a5929e-a87c-4a8e-8697-c784e0b5ae87 · outbound
This paper cites Semantic uncertainty: Linguistic invariances for uncertainty estimation in natural language generation,.
Ensemble based approach to quantifying uncertainty of LLM based classifications Semantic uncertainty: Linguistic invariances for uncertainty estimation in natural language generation,
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T00:04:41.550758Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation ce61005a-d07b-4452-8eeb-f11cdb713636 · outbound
This paper cites Unsupervised quality estimation for neural machine translation. ,.
Ensemble based approach to quantifying uncertainty of LLM based classifications Unsupervised quality estimation for neural machine translation. ,
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T00:04:41.506576Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 52a840ba-6080-4924-9fdf-550b316d7693 · outbound
This paper cites Shifting attention to relevance: Towards the predictive uncertainty quantification of free-form large language models.,.
Ensemble based approach to quantifying uncertainty of LLM based classifications Shifting attention to relevance: Towards the predictive uncertainty quantification of free-form large language models.,
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T00:04:41.478602Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation ab334920-a672-49ea-a097-b39eb36f87f0 · outbound
This paper cites Generating with confidence: Uncertainty quantification for black-box large language models.,.
Ensemble based approach to quantifying uncertainty of LLM based classifications Generating with confidence: Uncertainty quantification for black-box large language models.,
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T00:04:41.448462Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 329d3f63-fb62-4f62-b814-8acce39bde28 · outbound
This paper cites Self-Consistency Improves Chain of Thought Reasoning in Language Models.
Ensemble based approach to quantifying uncertainty of LLM based classifications Self-Consistency Improves Chain of Thought Reasoning in Language Models
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T00:04:41.268971Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5fcc0fb0-3d7a-4035-86f0-570841700086 · outbound
This paper cites Unc-TTP: A Method for Classifying LLM Uncertainty to Improve In-Context Example Selection.
Ensemble based approach to quantifying uncertainty of LLM based classifications Unc-TTP: A Method for Classifying LLM Uncertainty to Improve In-Context Example Selection
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T00:04:41.431786Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Observation 30b6f6ad-399d-450f-9034-b064c1fc6d70 · outbound
This paper cites Detecting hallucinations in large language models using semantic entropy,.
Ensemble based approach to quantifying uncertainty of LLM based classifications Detecting hallucinations in large language models using semantic entropy,
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T00:04:41.416630Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.
Pith citing papers
No inbound Pith citation observations are available.