Paper Citation Record · LEDGER

Beyond Logprobs: A Multi-Signal Confidence Engine for LLM-Based Document Field Extraction

As of 5 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2606.24420.

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

pith.paper-citation-record.v1
2606.24420 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-25T23:52:07.754083Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

29 of 29 outbound references displayed

verified exact9
verified fuzzy0
unresolved18
parse uncertain0
malformed identifier0
metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 33477f41-1dcd-4428-b29b-2070870969bb · outbound

This paper cites LMDX: Language Model-based Document Information Extraction and Localization.

Beyond Logprobs: A Multi-Signal Confidence Engine for LLM-Based Document Field Extraction LMDX: Language Model-based Document Information Extraction and Localization

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-07-04T17:09:59.434210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 7c936fa0-35fc-427c-b6bc-645698ba693c · outbound

This paper cites DocILE Benchmark for Document Information Localization and Extraction.

Beyond Logprobs: A Multi-Signal Confidence Engine for LLM-Based Document Field Extraction DocILE Benchmark for Document Information Localization and Extraction

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-07-04T17:09:59.455219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 3ca612ff-8b89-4cff-a5b2-a066729851fc · outbound

This paper cites Reflect then Learn: Active Prompting for Information Extraction Guided by Introspective Confusion.

Beyond Logprobs: A Multi-Signal Confidence Engine for LLM-Based Document Field Extraction Reflect then Learn: Active Prompting for Information Extraction Guided by Introspective Confusion

Reference 3

Resolution: metadata mismatch; local_arxiv, observed 2026-07-04T17:09:59.461035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d5909480-579b-4801-ae06-8fbd642690f5 · outbound

This paper cites Geifman and R.

Beyond Logprobs: A Multi-Signal Confidence Engine for LLM-Based Document Field Extraction Geifman and R

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-25T23:52:07.754083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d8c3280-5da1-4d6b-98e6-601235376b13 · outbound

This paper cites Corbière et al.Addressing Failure Prediction by Learning Model Confidence.NeurIPS, 2019.

Beyond Logprobs: A Multi-Signal Confidence Engine for LLM-Based Document Field Extraction Corbière et al.Addressing Failure Prediction by Learning Model Confidence.NeurIPS, 2019

Reference 5

Resolution: unresolved; no resolver link, observed 2026-06-25T23:52:07.754083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2881d927-9667-416b-94d3-fabcfdcafec1 · outbound

This paper cites Geifman and R.

Beyond Logprobs: A Multi-Signal Confidence Engine for LLM-Based Document Field Extraction Geifman and R

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-25T23:52:07.754083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea77c59a-17fc-44a6-9de4-c5e465c1db3a · outbound

This paper cites an unresolved cited work.

Beyond Logprobs: A Multi-Signal Confidence Engine for LLM-Based Document Field Extraction Unresolved cited work

Reference 7

Resolution: unresolved; no resolver link, observed 2026-06-25T23:52:07.754083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a0299e3-0cbd-4154-8c8e-ffc1ee591d31 · outbound

This paper cites Blum and T.

Beyond Logprobs: A Multi-Signal Confidence Engine for LLM-Based Document Field Extraction Blum and T

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-25T23:52:07.754083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d042cf0-bd2f-4549-a6c7-8bfe0ba5935d · outbound

This paper cites Lakshminarayanan, A.

Beyond Logprobs: A Multi-Signal Confidence Engine for LLM-Based Document Field Extraction Lakshminarayanan, A

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-25T23:52:07.754083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57e8abab-aa45-4315-8adf-d667245691fd · outbound

This paper cites Li et al.Evaluating Object Hallucination in Large Vision-Language Models.EMNLP, 2023.

Beyond Logprobs: A Multi-Signal Confidence Engine for LLM-Based Document Field Extraction Li et al.Evaluating Object Hallucination in Large Vision-Language Models.EMNLP, 2023

Reference 10

Resolution: unresolved; no resolver link, observed 2026-06-25T23:52:07.754083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db1c0695-faa0-4579-9fc3-b63c80f7b661 · outbound

This paper cites Min et al.FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation.EMNLP, 2023.

Beyond Logprobs: A Multi-Signal Confidence Engine for LLM-Based Document Field Extraction Min et al.FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation.EMNLP, 2023

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-25T23:52:07.754083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e21ecebb-1986-4a21-9207-59cf8b82c536 · outbound

This paper cites Gero et al.Self-Verification Improves Few-Shot Clinical Information Extraction.ACL Workshop on Clinical NLP, 2023.

Beyond Logprobs: A Multi-Signal Confidence Engine for LLM-Based Document Field Extraction Gero et al.Self-Verification Improves Few-Shot Clinical Information Extraction.ACL Workshop on Clinical NLP, 2023

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-25T23:52:07.754083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c6213764-e4bd-4856-a71f-cbbec86fbe3b · outbound

This paper cites HYCEDIS: HYbrid Confidence Engine for Deep Document Intelligence System.

Beyond Logprobs: A Multi-Signal Confidence Engine for LLM-Based Document Field Extraction HYCEDIS: HYbrid Confidence Engine for Deep Document Intelligence System

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-07-04T17:09:59.464244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f3a2fb88-a550-462a-bd52-7641ef996207 · outbound

This paper cites Rombach and M.

Beyond Logprobs: A Multi-Signal Confidence Engine for LLM-Based Document Field Extraction Rombach and M

Reference 14

Resolution: verified exact; doi, observed 2026-06-25T23:58:42.875601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 47900fbc-2fc7-4e95-8af0-d0822de66af8 · outbound

This paper cites Confidence-Aware Document OCR Error Detection.

Beyond Logprobs: A Multi-Signal Confidence Engine for LLM-Based Document Field Extraction Confidence-Aware Document OCR Error Detection

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-07-04T17:09:59.426366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 6aac120c-8ca0-4473-9a1a-0c02f97dfe38 · outbound

This paper cites an unresolved cited work.

Beyond Logprobs: A Multi-Signal Confidence Engine for LLM-Based Document Field Extraction Unresolved cited work

Reference 16

Resolution: unresolved; no resolver link, observed 2026-06-25T23:52:07.754083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8219bdcd-d35a-4190-8d6b-7a5fbeaf27d6 · outbound

This paper cites Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness.

Beyond Logprobs: A Multi-Signal Confidence Engine for LLM-Based Document Field Extraction Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-07-04T17:09:59.423569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 95000829-9ec6-4285-b19e-6f29d362bbbb · outbound

This paper cites Goh and J.

Beyond Logprobs: A Multi-Signal Confidence Engine for LLM-Based Document Field Extraction Goh and J

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-07-04T17:09:59.457979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 41a80365-ef03-43ee-ae27-14213686f7a0 · outbound

This paper cites Farquhar et al.Detecting Hallucinations in Large Language Models using Semantic Entropy.

Beyond Logprobs: A Multi-Signal Confidence Engine for LLM-Based Document Field Extraction Farquhar et al.Detecting Hallucinations in Large Language Models using Semantic Entropy

Reference 19

Resolution: unresolved; no resolver link, observed 2026-06-25T23:52:07.754083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5fcc03e1-fd95-4e18-84ec-cdbe1b6db4ea · outbound

This paper cites Language Models (Mostly) Know What They Know.

Beyond Logprobs: A Multi-Signal Confidence Engine for LLM-Based Document Field Extraction Language Models (Mostly) Know What They Know

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-07-04T17:09:59.428922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation e622431a-d4eb-401d-a148-c66978bcc057 · outbound

This paper cites Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback.

Beyond Logprobs: A Multi-Signal Confidence Engine for LLM-Based Document Field Extraction Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback

Reference 21

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T17:09:59.431676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 5fd84323-5992-4546-968b-b4fde0a9227b · outbound

This paper cites Calibrating Structured Output Predictors for Natural Language Processing.

Beyond Logprobs: A Multi-Signal Confidence Engine for LLM-Based Document Field Extraction Calibrating Structured Output Predictors for Natural Language Processing

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-07-04T17:09:59.436748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 273e6707-9ac5-49d9-a714-eec7051fa33d · outbound

This paper cites Nixon et al.Measuring Calibration in Deep Learning.CVPR Workshops, 2019.

Beyond Logprobs: A Multi-Signal Confidence Engine for LLM-Based Document Field Extraction Nixon et al.Measuring Calibration in Deep Learning.CVPR Workshops, 2019

Reference 23

Resolution: unresolved; no resolver link, observed 2026-06-25T23:52:07.754083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d19391dd-af82-4f7e-9b54-7303ec8619bf · outbound

This paper cites Kull et al.Beyond Temperature Scaling.NeurIPS, 2019.

Beyond Logprobs: A Multi-Signal Confidence Engine for LLM-Based Document Field Extraction Kull et al.Beyond Temperature Scaling.NeurIPS, 2019

Reference 24

Resolution: unresolved; no resolver link, observed 2026-06-25T23:52:07.754083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7c8cb3fa-ed0a-4914-802d-d6c630c1ee2f · outbound

This paper cites Park et al.CORD: A Consolidated Receipt Dataset for Post-OCR Parsing.NeurIPS Workshop, 2019.

Beyond Logprobs: A Multi-Signal Confidence Engine for LLM-Based Document Field Extraction Park et al.CORD: A Consolidated Receipt Dataset for Post-OCR Parsing.NeurIPS Workshop, 2019

Reference 25

Resolution: unresolved; no resolver link, observed 2026-06-25T23:52:07.754083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a490256-14f7-4ee7-a452-a544d0f07839 · outbound

This paper cites Huang et al.ICDAR 2019 Competition on Scanned Receipt OCR and Information Extraction.ICDAR, 2019.

Beyond Logprobs: A Multi-Signal Confidence Engine for LLM-Based Document Field Extraction Huang et al.ICDAR 2019 Competition on Scanned Receipt OCR and Information Extraction.ICDAR, 2019

Reference 26

Resolution: unresolved; no resolver link, observed 2026-06-25T23:52:07.754083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db265e49-5d42-42a2-9de6-f604703a6815 · outbound

This paper cites Prokhorenkova et al.CatBoost: Unbiased Boosting with Categorical Features.NeurIPS, 2018.

Beyond Logprobs: A Multi-Signal Confidence Engine for LLM-Based Document Field Extraction Prokhorenkova et al.CatBoost: Unbiased Boosting with Categorical Features.NeurIPS, 2018

Reference 27

Resolution: unresolved; no resolver link, observed 2026-06-25T23:52:07.754083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c4f47594-7f95-44d7-aba7-16c99987b411 · outbound

This paper cites Wang et al.Self-Consistency Improves Chain of Thought Reasoning.ICLR, 2023.

Beyond Logprobs: A Multi-Signal Confidence Engine for LLM-Based Document Field Extraction Wang et al.Self-Consistency Improves Chain of Thought Reasoning.ICLR, 2023

Reference 28

Resolution: unresolved; no resolver link, observed 2026-06-25T23:52:07.754083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5597a8bc-583d-4f70-895e-500b7772249b · outbound

This paper cites Feature names correspond to column headers in the pipeline output and to the feature importance plot in Figure 4a.

Beyond Logprobs: A Multi-Signal Confidence Engine for LLM-Based Document Field Extraction Feature names correspond to column headers in the pipeline output and to the feature importance plot in Figure 4a

Reference 29

Resolution: unresolved; no resolver link, observed 2026-06-25T23:52:07.754083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.