Paper Citation Record · LEDGER

Benchmarking LLMs via Uncertainty Quantification

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 17 inbound Pith citation observations for arXiv:2401.12794.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2401.12794 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 17 of 17 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:05:53.991965Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-23T19:35:47.071151Z

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 0b6b0dde-0951-4955-9c07-8801e8d687d9 · inbound

Functional-level Uncertainty Quantification for Calibrated Fine-tuning on LLMs cites this paper.

Functional-level Uncertainty Quantification for Calibrated Fine-tuning on LLMs Benchmarking LLMs via Uncertainty Quantification

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-23T19:35:47.074997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2585fb1e-f6a1-4c8c-99e9-3f5822fe85fd · inbound

Predictive Inference With Fast Feature Conformal Prediction cites this paper.

Predictive Inference With Fast Feature Conformal Prediction Benchmarking LLMs via Uncertainty Quantification

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-12T05:15:32.810048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 70f47db3-29ef-4ee5-967c-0ddbac94071f · inbound

A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directions cites this paper.

A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directions Benchmarking LLMs via Uncertainty Quantification

Reference 234

Resolution: unresolved; no resolver link, observed 2026-08-11T20:37:55.217077Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98e279e1-ebd1-4776-b17f-165d8101602c · inbound

Evolution of Thought: Diverse and High-Quality Reasoning via Multi-Objective Optimization cites this paper.

Evolution of Thought: Diverse and High-Quality Reasoning via Multi-Objective Optimization Benchmarking LLMs via Uncertainty Quantification

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-12T13:52:26.468638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 360d51e6-76ad-47c8-b0ad-b91b98ba1658 · inbound

Prune 'n Predict: Optimizing LLM Decision-making with Conformal Prediction cites this paper.

Prune 'n Predict: Optimizing LLM Decision-making with Conformal Prediction Benchmarking LLMs via Uncertainty Quantification

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T22:54:43.825588Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c88540e-9749-46c8-aa8b-8dd0a528c27f · inbound

Multiple Choice Questions: Reasoning Makes Large Language Models (LLMs) More Self-Confident, Especially When They are Wrong cites this paper.

Multiple Choice Questions: Reasoning Makes Large Language Models (LLMs) More Self-Confident, Especially When They are Wrong Benchmarking LLMs via Uncertainty Quantification

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-23T05:37:36.048475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e7e3174e-72ef-4043-8cf8-490a5ba224f2 · inbound

Towards Trustworthy Retrieval Augmented Generation for Large Language Models: A Survey cites this paper.

Towards Trustworthy Retrieval Augmented Generation for Large Language Models: A Survey Benchmarking LLMs via Uncertainty Quantification

Reference 219

Resolution: unresolved; no resolver link, observed 2026-08-08T19:15:25.711690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e00f366-438d-44fa-abdc-e8e600095721 · inbound

Learning Conformal Abstention Policies for Adaptive Risk Management in Large Language and Vision-Language Models cites this paper.

Learning Conformal Abstention Policies for Adaptive Risk Management in Large Language and Vision-Language Models Benchmarking LLMs via Uncertainty Quantification

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-08T18:23:05.750075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d300528d-616e-49b6-aafa-fc10614d4fdd · inbound

Probabilistic Stability Guarantees for Feature Attributions cites this paper.

Probabilistic Stability Guarantees for Feature Attributions Benchmarking LLMs via Uncertainty Quantification

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-16T12:05:53.991965Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d39c7a9-bc97-4301-a42e-bd4b0b742cbb · inbound

aiXamine: Simplified LLM Safety and Security cites this paper.

aiXamine: Simplified LLM Safety and Security Benchmarking LLMs via Uncertainty Quantification

Reference 137

Resolution: unresolved; no resolver link, observed 2026-08-16T11:39:11.308079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17d5fe97-a88f-4836-a1f3-21295eb71081 · inbound

Calibrating Uncertainty Quantification of Multi-Modal LLMs using Grounding cites this paper.

Calibrating Uncertainty Quantification of Multi-Modal LLMs using Grounding Benchmarking LLMs via Uncertainty Quantification

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-16T04:54:19.601232Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eedb8e07-2ad8-4b15-bc7d-adbcc45cff54 · inbound

Bridging AI and Carbon Capture: A Dataset for LLMs in Ionic Liquids and CBE Research cites this paper.

Bridging AI and Carbon Capture: A Dataset for LLMs in Ionic Liquids and CBE Research Benchmarking LLMs via Uncertainty Quantification

Reference 101

Resolution: unresolved; no resolver link, observed 2026-08-15T22:31:28.894467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57a7a4cc-b903-42ee-bfcb-4c248d6deb4f · inbound

Recovering Event Probabilities from Large Language Model Embeddings via Axiomatic Constraints cites this paper.

Recovering Event Probabilities from Large Language Model Embeddings via Axiomatic Constraints Benchmarking LLMs via Uncertainty Quantification

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-15T22:41:50.885772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d80b6f44-9edc-4ea3-83ec-098c3230df77 · inbound

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs cites this paper.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs Benchmarking LLMs via Uncertainty Quantification

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-07T12:44:08.930215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cacc16af-496c-4296-8c9f-7faa68f42645 · inbound

Eliminating Hallucination-Induced Errors in LLM Code Generation with Functional Clustering cites this paper.

Eliminating Hallucination-Induced Errors in LLM Code Generation with Functional Clustering Benchmarking LLMs via Uncertainty Quantification

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-15T20:56:36.043524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58640330-70a4-45ad-9bb3-43527e453b96 · inbound

PARC: A Quantitative Framework Uncovering the Symmetries within Vision Language Models cites this paper.

PARC: A Quantitative Framework Uncovering the Symmetries within Vision Language Models Benchmarking LLMs via Uncertainty Quantification

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-07T11:12:03.559440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e83e0de-6cf3-4c91-9d0f-4027229e3059 · inbound

Uncertainty-Aware Complex Scientific Table Data Extraction cites this paper.

Uncertainty-Aware Complex Scientific Table Data Extraction Benchmarking LLMs via Uncertainty Quantification

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T20:58:52.234268Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.