Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T11:34:32.900349Z
Paper Citation Record · LEDGER
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records
As of 24 August 2026, this Paper Citation Record lists 65 of 65 outbound references and 6 inbound Pith citation observations for arXiv:2501.16672.
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 2026-08-23T06:30:58.430688+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T16:25:04.256622Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T11:08:02.946188Z
Reference resolution
65 of 65 outbound references displayed
- verified exact0
- verified fuzzy60
- unresolved5
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 4deb923e-d741-4abc-a69d-2a7529bf7a7a · outbound
This paper cites Adapted large language models can outperform medical experts in clinical text summarization.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Adapted large language models can outperform medical experts in clinical text summarization
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:34.157026Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 613a5e88-4c71-4d93-aeaf-aa0c827c716a · outbound
This paper cites Evaluating large language models on medical evidence summarization.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Evaluating large language models on medical evidence summarization
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:34.134531Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 8367ca84-572c-4a7e-881b-0041e360a9a7 · outbound
This paper cites Large language model capabilities in perioperative risk prediction and prognostication.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Large language model capabilities in perioperative risk prediction and prognostication
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:34.117677Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 2d919ddf-63b5-4e29-8089-9714d0b3a641 · outbound
This paper cites Diagnostic reasoning prompts reveal the potential for large language model interpretability in medicine.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Diagnostic reasoning prompts reveal the potential for large language model interpretability in medicine
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:34.099884Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 3b0f4c84-8f2b-4531-b055-895e69a4a2b1 · outbound
This paper cites Large language model influence on diagnostic reasoning: A randomized clinical trial: A randomized clinical trial.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Large language model influence on diagnostic reasoning: A randomized clinical trial: A randomized clinical trial
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:34.081188Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 5759b244-04f0-4827-978f-dd3bf9685cd9 · outbound
This paper cites Generative artificial intelligence to transform inpatient discharge summaries to patient-friendly language and format.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Generative artificial intelligence to transform inpatient discharge summaries to patient-friendly language and format
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:34.064076Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 8beebb4b-a5f3-4825-99f3-78db1659c737 · outbound
This paper cites Reference-free monolithic preference optimization with odds ratio.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Reference-free monolithic preference optimization with odds ratio
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:34.045767Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 99c819c2-e4a7-4739-8f2b-15d23e181b53 · outbound
This paper cites Testing and evaluation of health care applications of large language models: A systematic review: A systematic review.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Testing and evaluation of health care applications of large language models: A systematic review: A systematic review
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:34.025038Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 9bbb55ae-502f-412e-a642-4f5f30e40ace · outbound
This paper cites MAIRA-2: Grounded Radiology Report Generation.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records MAIRA-2: Grounded Radiology Report Generation
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:34.000838Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation f551dcbe-478a-4d47-b2d2-0ccd88f1b728 · outbound
This paper cites Creation and adoption of large language models in medicine.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Creation and adoption of large language models in medicine
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.978398Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 43852ffa-ed45-4d0f-a798-e36d9e60384a · outbound
This paper cites DocLens: Multi-aspect fine-grained medical text evaluation.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records DocLens: Multi-aspect fine-grained medical text evaluation
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.962928Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation cfb66fc9-0bbc-4633-b648-393a5cd54823 · outbound
This paper cites Assessing the limitations of large language models in clinical fact decomposition.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Assessing the limitations of large language models in clinical fact decomposition
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.946309Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 3b844951-4c4d-4e67-89d8-fa15829f689c · outbound
This paper cites The limits of clinician vigilance as an AI safety bulwark.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records The limits of clinician vigilance as an AI safety bulwark
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.928933Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation fdd62e0c-3d6f-4b1c-a593-dfa0ca6d0aeb · outbound
This paper cites Factuality challenges in the era of large language models and opportunities for fact-checking.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Factuality challenges in the era of large language models and opportunities for fact-checking
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.912811Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 7b2757fa-a066-4f5c-a3c4-99144f60131f · outbound
This paper cites Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T11:34:32.607577Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f75f8414-3d37-4023-b4be-6d33b12ca207 · outbound
This paper cites Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T11:34:32.612994Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fabcb260-c652-45a7-950e-29b928fff8a0 · outbound
This paper cites Language models hallucinate, but may excel at fact verification.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Language models hallucinate, but may excel at fact verification
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.896492Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 520bd333-e731-4b17-bec9-4d53e5325451 · outbound
This paper cites Long-form factuality in large language models.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Long-form factuality in large language models
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.879933Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 300aa001-078f-48d3-b6a9-b84dd0dd52ff · outbound
This paper cites FActScore: Fine-grained atomic evaluation of factual precision in long form text generation.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records FActScore: Fine-grained atomic evaluation of factual precision in long form text generation
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.863923Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation bd4e9f55-5543-4335-9b09-62c04fd8c531 · outbound
This paper cites WiCE: Real-world entailment for claims in Wikipedia.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records WiCE: Real-world entailment for claims in Wikipedia
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.848966Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 4fa4b4e3-49d6-4ccc-b801-64e6a9f4d4c8 · outbound
This paper cites Complex claim verification with evidence retrieved in the wild.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Complex claim verification with evidence retrieved in the wild
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.832414Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation a8df4daa-d60c-4e6e-884c-2878aa4df077 · outbound
This paper cites RAGAs: Automated Evaluation of Retrieval Aug- mented Generation.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records RAGAs: Automated Evaluation of Retrieval Aug- mented Generation
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.812545Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation bb95b821-8e56-4844-9632-06d720f4ae63 · outbound
This paper cites MIMIC-III, a freely accessible critical care database.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records MIMIC-III, a freely accessible critical care database
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.795711Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation a5949e19-3378-411e-afac-93d06f380b8e · outbound
This paper cites PhysioNet.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records PhysioNet
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.776872Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation db1471a4-7847-4736-8f00-d6bdedc7efa6 · outbound
This paper cites The philosophy of logical atomism.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records The philosophy of logical atomism
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.760952Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation e0c5532b-c05a-43dc-9daa-06593729a5f8 · outbound
This paper cites A closer look at claim decomposition.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records A closer look at claim decomposition
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.744436Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 70ea13bb-b43b-4a08-a9d8-79839f24ed23 · outbound
This paper cites Logic: The laws of truth.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Logic: The laws of truth
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.726254Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 4655dfe6-2d04-4d76-b9ed-886d50f28486 · outbound
This paper cites Factcheck- bench: Fine-grained evaluation benchmark for automatic fact-checkers.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Factcheck- bench: Fine-grained evaluation benchmark for automatic fact-checkers
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.705133Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 90e4a2f5-4459-448b-9adf-ebe8588d66fe · outbound
This paper cites Dense X retrieval: What retrieval granularity should we use? In: Proceedings of the 2024 Conference on Empirical Meth- ods in Natural Language Processing.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Dense X retrieval: What retrieval granularity should we use? In: Proceedings of the 2024 Conference on Empirical Meth- ods in Natural Language Processing
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.682744Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 12fc1762-5ef0-4f73-8487-d12be45c39b5 · outbound
This paper cites An introduction to the resource description framework.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records An introduction to the resource description framework
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.664148Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation d7451b18-d459-46c3-bb7a-b7ef97775c09 · outbound
This paper cites Introduction to SNOMED CT.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Introduction to SNOMED CT
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.645166Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 983bca91-cb42-49e9-8a5d-156505ef7cf9 · outbound
This paper cites AnEfficiency Studyfor SPLADEModels.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records AnEfficiency Studyfor SPLADEModels
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.621055Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation e1d3f3b1-5cdc-4416-9cc1-0f24d2f0ef97 · outbound
This paper cites AIR-Bench: Automated Heterogeneous Information Retrieval Benchmark.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records AIR-Bench: Automated Heterogeneous Information Retrieval Benchmark
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.598876Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 2f476a37-1b62-4565-8370-5706f9bb90c9 · outbound
This paper cites Passage re-ranking with BERT.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Passage re-ranking with BERT
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.574575Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 5122d8fd-e136-4e7b-bd67-f6033786adee · outbound
This paper cites A thorough comparison of cross-encoders and LLMs for reranking SPLADE.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records A thorough comparison of cross-encoders and LLMs for reranking SPLADE
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.554725Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 07bdbb40-973f-499d-bea9-420e3eecdd84 · outbound
This paper cites M3-Embedding: Multi-Linguality, Multi- Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records M3-Embedding: Multi-Linguality, Multi- Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.536712Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation efc51d57-ab9d-4671-9ef1-c1a726da7520 · outbound
This paper cites BEIR: A Heterogeneous Bench- mark for Zero-shot Evaluation of Information Retrieval Models.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records BEIR: A Heterogeneous Bench- mark for Zero-shot Evaluation of Information Retrieval Models
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.518513Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 511cac86-77c3-41f4-a1f3-cb6974ace463 · outbound
This paper cites SPLADE: Sparse lexical and expansion model for first stage ranking.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records SPLADE: Sparse lexical and expansion model for first stage ranking
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.497897Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 1a6c948a-8608-46a6-87d3-bb9636e79b63 · outbound
This paper cites SparseEmbed: Learning Sparse Lexi- cal Representations with Contextual Embeddings for Retrieval.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records SparseEmbed: Learning Sparse Lexi- cal Representations with Contextual Embeddings for Retrieval
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.475589Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 5dd5025e-0d30-4fa0-b436-c9f45c4bcb93 · outbound
This paper cites Grokked transformers are implicit reasoners: A mechanistic journey to the edge of generalization.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Grokked transformers are implicit reasoners: A mechanistic journey to the edge of generalization
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.460058Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 4b3796b2-598b-43d8-855a-f5c0fd76f222 · outbound
This paper cites Out-of-distribution generalization via composition: a lens through induction heads in Transformers.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Out-of-distribution generalization via composition: a lens through induction heads in Transformers
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.442014Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 0c41036a-f65f-4d4a-91cb-ef67cbda66db · outbound
This paper cites LogicBench: Towards Systematic Evaluation of Logical Reasoning Ability of Large Language Models.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records LogicBench: Towards Systematic Evaluation of Logical Reasoning Ability of Large Language Models
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.422522Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 95a71403-c8c1-4a99-a9d7-b2cdadef1259 · outbound
This paper cites Logic-LM: Empowering large language models with symbolic solvers for faithful logical reasoning.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Logic-LM: Empowering large language models with symbolic solvers for faithful logical reasoning
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.402016Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 465c4dcc-5cb1-477d-af37-6cb0ce1ef470 · outbound
This paper cites LogicAsker: Evaluating and improving the logical reasoning ability of large language models.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records LogicAsker: Evaluating and improving the logical reasoning ability of large language models
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.383637Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation e69f61eb-866a-47f4-9f94-6da388a73d15 · outbound
This paper cites Multi- LogiEval: Towards evaluating multi-step logical reasoning ability of large language models.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Multi- LogiEval: Towards evaluating multi-step logical reasoning ability of large language models
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.364139Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 5a115209-0840-4c76-854a-101d97bce6a8 · outbound
This paper cites Molecular Facts: Desiderata for Decontextualization in LLM Fact Verification.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Molecular Facts: Desiderata for Decontextualization in LLM Fact Verification
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.348664Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 247021d6-08e6-430c-b2a8-5217df9dbe1a · outbound
This paper cites Decontextualization:Making sentences stand-alone.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Decontextualization:Making sentences stand-alone
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.332470Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 928ee4c8-6b4a-4d3e-99f9-8d3c34024a49 · outbound
This paper cites Self-Taught Evaluators.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Self-Taught Evaluators
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.315132Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation d2511b17-0132-420e-adb2-8c208cf5b98e · outbound
This paper cites LLMs instead of Human Judges? A Large Scale Empirical Study across 20 NLP Evaluation Tasks.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records LLMs instead of Human Judges? A Large Scale Empirical Study across 20 NLP Evaluation Tasks
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.295019Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 4a204ab3-51ad-43a2-b5a9-8d518f2214d4 · outbound
This paper cites Frequency and types of patient-reported errors in electronic health record ambulatory care notes.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Frequency and types of patient-reported errors in electronic health record ambulatory care notes
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.278309Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation dcc8a3c1-dd59-45d3-b2f2-35c84859d72d · outbound
This paper cites TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.261255Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 1eb91a48-8e5a-4ac6-819e-e74112e6a679 · outbound
This paper cites Efficient Memory Management for Large Language Model Serving with PagedAttention.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Efficient Memory Management for Large Language Model Serving with PagedAttention
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.242031Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 551eb8ec-f486-4a10-b3b0-21b5657d599f · outbound
This paper cites The Llama 3 herd of models.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records The Llama 3 herd of models
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.216089Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation fc5d8075-3061-4211-8294-d037131e81ac · outbound
This paper cites Transcendence: Generative Models Can Outperform The Experts That Train Them.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Transcendence: Generative Models Can Outperform The Experts That Train Them
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.195831Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 1369096a-3f25-42f5-ad19-a7c938521d90 · outbound
This paper cites Efficient Guided Generation for Large Language Models.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Efficient Guided Generation for Large Language Models
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.177096Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 6d6d7092-f8ec-435c-9654-ed02b37e73a9 · outbound
This paper cites Language models are few-shot learners.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Language models are few-shot learners
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.162243Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation bf3fb1f5-0d8b-42ff-a10c-80f2e77f25e4 · outbound
This paper cites In-context Learning and Induction Heads.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records In-context Learning and Induction Heads
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.145553Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 073d37c1-76e8-4b34-8876-3aa1ea441dd3 · outbound
This paper cites an unresolved cited work.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Unresolved cited work
Reference 58
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T11:34:33.126419Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 7c302f45-4194-4c75-ac33-a7126bfc0c9f · outbound
This paper cites Making large language models A better foundation for dense retrieval.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Making large language models A better foundation for dense retrieval
Reference 59
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.108492Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation deddcf60-d93b-4e6d-aa49-d16bd93285e9 · outbound
This paper cites Natural language processing with python.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Natural language processing with python
Reference 60
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.086684Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 81e513b4-d607-4622-a8f6-cb5ff9e48a2d · outbound
This paper cites an unresolved cited work.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Unresolved cited work
Reference 61
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T11:34:33.068313Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation c4276f77-6797-4439-b53d-9f21beebf6cd · outbound
This paper cites Efficient and robust approximate nearest neighbor search using Hierarchical Navigable Small World graphs.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Efficient and robust approximate nearest neighbor search using Hierarchical Navigable Small World graphs
Reference 62
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.051456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation f325beff-07d2-4fd6-8bc8-bfdc1e2a1e1d · outbound
This paper cites Accessed: 2024-9-18.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Accessed: 2024-9-18
Reference 63
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:33.033358Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation f7fc2db4-3256-49d5-adeb-0012f3f23956 · outbound
This paper cites an unresolved cited work.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Unresolved cited work
Reference 64
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T11:34:33.012380Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 79539ec0-571c-4037-ba4f-24abf6828d97 · outbound
This paper cites Computing inter-rater reliability and its variance in the presence of high agreement.
VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records Computing inter-rater reliability and its variance in the presence of high agreement
Reference 65
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T11:34:32.988494Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Pith citing papers
Observation 97e437a6-e2c9-4bcd-b542-579818cd73b0 · inbound
MedReadCtrl: Personalizing medical text generation with readability-controlled instruction learning cites this paper.
MedReadCtrl: Personalizing medical text generation with readability-controlled instruction learning VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:48:18.709970Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation aa5cde20-c566-4920-bb92-6368ccc680dd · inbound
MedFactEval and MedAgentBrief: A Framework and Workflow for Generating and Evaluating Factual Clinical Summaries cites this paper.
MedFactEval and MedAgentBrief: A Framework and Workflow for Generating and Evaluating Factual Clinical Summaries VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T16:25:04.256622Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7aa94a50-2fe7-4394-a03f-9a64ca92e0e1 · inbound
MedFact: Benchmarking the Fact-Checking Capabilities of Large Language Models on Chinese Medical Texts cites this paper.
MedFact: Benchmarking the Fact-Checking Capabilities of Large Language Models on Chinese Medical Texts VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:43:50.000570Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 709e763c-0e00-4d8c-8d39-bdddf925428c · inbound
Verification Mirage: Mapping the Reliability Boundary of Self-Verification in Medical VQA cites this paper.
Verification Mirage: Mapping the Reliability Boundary of Self-Verification in Medical VQA VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records
Reference 4
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T05:56:25.410030Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation c77b2f72-c840-4663-83b4-1f7a39de0707 · inbound
LLM-as-a-Judge in Healthcare: A Scoping Analysis of Applications, Methods, and Human Alignment cites this paper.
LLM-as-a-Judge in Healthcare: A Scoping Analysis of Applications, Methods, and Human Alignment VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records
Reference 28
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-06-29T23:24:01.760338Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 0a3a4348-bec3-4d6c-879a-7e88425d6cac · inbound
Deployment-Centered Evaluation: Predicting Query-Level Rejection Risk in a Clinical LLM System cites this paper.
Deployment-Centered Evaluation: Predicting Query-Level Rejection Risk in a Clinical LLM System VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records
Reference 8
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-03T11:08:02.947612Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.