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Paper Citation Record · LEDGER

Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity

As of 8 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 3 inbound Pith citation observations for arXiv:2506.00245.

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

pith.paper-citation-record.v1
2506.00245 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:14:04.226261Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-20T06:53:44.993529Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T06:58:06.244234Z

Reference resolution

30 of 30 outbound references displayed

  • verified exact0
  • verified fuzzy8
  • unresolved21
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6b1b2cdf-17df-4141-aaf1-950fa23df618 · outbound

This paper cites INSIDE: LLMs' Internal States Retain the Power of Hallucination Detection.

Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity INSIDE: LLMs' Internal States Retain the Power of Hallucination Detection

Reference 4

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 78c7e96b-304c-4585-ac32-2a6ed692f78a · outbound

This paper cites Shifting Attention to Relevance: Towards the Predictive Uncertainty Quantification of Free-Form Large Language Models.

Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity Shifting Attention to Relevance: Towards the Predictive Uncertainty Quantification of Free-Form Large Language Models

Reference 5

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Unavailable: canonical work link unavailable.

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Observation febc0c40-23f0-4dac-9cc6-d298ff627e42 · outbound

This paper cites The Llama 3 Herd of Models.

Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity The Llama 3 Herd of Models

Reference 6

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Unavailable: canonical work link unavailable.

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Observation f04d3bd2-fd0e-4273-b135-0a4c61453a6d · outbound

This paper cites InProceed- ings of the 2023 Conference on Empirical Methods in Natural Language Processing: System Demon- strations, pages 446–461, Singapore.

Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity InProceed- ings of the 2023 Conference on Empirical Methods in Natural Language Processing: System Demon- strations, pages 446–461, Singapore

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation d361a085-7952-44c9-9f1f-c9d12e927a1f · outbound

This paper cites How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation.

Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 9

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source=pdf_text observed=2026-08-07T12:14:01.593619Z digest=sha256:c9245cce4a9b6b4b76a9c3a9b2001a34311f181815cbf6683bc64f81f9dd85e1

Observation 45bed704-2429-4b56-9c8f-eab5b58ee23f · outbound

This paper cites A Survey of Uncertainty Estimation in LLMs: Theory Meets Practice.

Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity A Survey of Uncertainty Estimation in LLMs: Theory Meets Practice

Reference 10

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Source-reported events for the cited work

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Observation 01b06a56-b928-475a-84f0-cf2e8b48c6d7 · outbound

This paper cites Mistral 7B.

Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity Mistral 7B

Reference 11

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Observation c15e92ed-92a3-479c-85bc-1edae5b31e09 · outbound

This paper cites Towards General Text Embeddings with Multi-stage Contrastive Learning.

Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity Towards General Text Embeddings with Multi-stage Contrastive Learning

Reference 14

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Observation b0f943a8-6e4e-4e61-ae85-b613b0091edb · outbound

This paper cites Uncertainty Estimation in Autoregressive Structured Prediction.

Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity Uncertainty Estimation in Autoregressive Structured Prediction

Reference 15

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Unavailable: canonical work link unavailable.

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Observation 3e6a156e-0511-4bc6-b147-edae66da369a · outbound

This paper cites InProceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 1906–1919, On- line.

Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity InProceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 1906–1919, On- line

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 7d428fcb-82c8-4a86-bbe6-990bfca93a64 · outbound

This paper cites MTEB: Massive Text Embedding Benchmark.

Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity MTEB: Massive Text Embedding Benchmark

Reference 17

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Observation 6e7b7aa8-7de4-4270-94f4-161759694981 · outbound

This paper cites Kernel Language Entropy: Fine-grained Uncertainty Quantification for LLMs from Semantic Similarities.

Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity Kernel Language Entropy: Fine-grained Uncertainty Quantification for LLMs from Semantic Similarities

Reference 19

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source=pdf_text observed=2026-08-07T12:14:02.784645Z digest=sha256:14a7b5f65b2ece8b06c81c7489dff22d21db2e8d88dee34386f4704b4c89c06c

Observation 2afe8acc-6cac-4d84-a643-6af7da38fb99 · outbound

This paper cites Know What You Don't Know: Unanswerable Questions for SQuAD.

Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity Know What You Don't Know: Unanswerable Questions for SQuAD

Reference 21

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Observation 5d3ca5dc-2bb9-4499-a8ee-0ee2a2701ca5 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 22

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Observation 260cf12a-413c-460e-98d6-9939dc48b083 · outbound

This paper cites LUQ: Long-text Uncertainty Quantification for LLMs.

Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity LUQ: Long-text Uncertainty Quantification for LLMs

Reference 23

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Observation 1ad9e928-22fb-4728-b4a5-d9d01580375f · outbound

This paper cites InInternational Conference on Learning Representations.

Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity InInternational Conference on Learning Representations

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 569f6976-e602-4b9c-b57d-38a598f26fcd · outbound

This paper cites an unresolved cited work.

Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity Unresolved cited work

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 03f85915-842b-4be5-a0a2-394da710681f · outbound

This paper cites Task Instruction QA Answer the following question as briefly as possible.

Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity Task Instruction QA Answer the following question as briefly as possible

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation cebfef87-7f81-4fcb-aef3-7fb477552b1c · outbound

This paper cites We use 5-shot in-context demonstrations for QA tasks and instruct the model to produce short answers following the brief prompt from SE.

Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity We use 5-shot in-context demonstrations for QA tasks and instruct the model to produce short answers following the brief prompt from SE

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 4705346f-cf72-4d92-989d-7c6c5bc21f3d · outbound

This paper cites Ta- ble 5 summarizes the PRR score on TS and MT tasks.

Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity Ta- ble 5 summarizes the PRR score on TS and MT tasks

Reference 30

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 99c81f76-49e9-4ff3-bf40-75ea6aa97aab · outbound

This paper cites Hyperparameter setting.We select the best scale factor τ in Eq 3 and 4 from {0.1,1,10,100}.

Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity Hyperparameter setting.We select the best scale factor τ in Eq 3 and 4 from {0.1,1,10,100}

Reference 2004

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation adbabbea-462b-4dfb-a99c-e82d4c2a2765 · outbound

This paper cites InProceedings of the ninth workshop on statistical machine translation, pages 12–58.

Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity InProceedings of the ninth workshop on statistical machine translation, pages 12–58

Reference 2014

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 9852ef64-5cd3-4e50-9b68-9ab4b6e929cc · outbound

This paper cites TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension.

Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension

Reference 2017

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Observation 9d057d65-f04a-4561-bc44-1cadcd9c8ef4 · outbound

This paper cites Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization.

Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization

Reference 2018

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Observation 60b79f81-342b-41d0-a18b-014899ac40a6 · outbound

This paper cites This Email Could Save Your Life: Introducing the Task of Email Subject Line Generation.

Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity This Email Could Save Your Life: Introducing the Task of Email Subject Line Generation

Reference 2019

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local_arxiv, observed 2026-08-07T12:14:04.397774Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 664072d4-b6a8-4cd1-a6d5-9c72d0645ea2 · outbound

This paper cites DeBERTa: Decoding-enhanced BERT with Disentangled Attention.

Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity DeBERTa: Decoding-enhanced BERT with Disentangled Attention

Reference 2020

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Observation 0fa42ab2-e630-4fa8-8101-2771c49c5248 · outbound

This paper cites Are NLP Models really able to Solve Simple Math Word Problems?.

Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity Are NLP Models really able to Solve Simple Math Word Problems?

Reference 2021

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Observation 3a76e72d-0aea-4ab3-8637-fbcc3fb37bf4 · outbound

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

Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity Language Models (Mostly) Know What They Know

Reference 2022

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Observation be0c7504-2e3a-4376-be14-477db650ba76 · outbound

This paper cites Sparks of Artificial General Intelligence: Early experiments with GPT-4.

Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity Sparks of Artificial General Intelligence: Early experiments with GPT-4

Reference 2023

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Observation 4562b960-3db4-4591-8d6d-c8385c498057 · outbound

This paper cites Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.

Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Reference 2024

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Pith citing papers

Observation 6d9d06cc-de4c-4e7c-b06e-777ce0b80e0f · inbound

When to Trust the Answer: Question-Aligned Semantic Nearest Neighbor Entropy for Safer Surgical VQA cites this paper.

When to Trust the Answer: Question-Aligned Semantic Nearest Neighbor Entropy for Safer Surgical VQA Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity

Reference 7

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arxiv_id, observed 2026-05-18T01:22:15.709164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation b14fcdf4-eef3-437e-a4d0-4c30ef3af759 · inbound

Ensemble-Based Uncertainty Estimation for Code Correctness Estimation cites this paper.

Ensemble-Based Uncertainty Estimation for Code Correctness Estimation Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity

Reference 31

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arxiv_id, observed 2026-05-14T22:53:14.078634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation fededa25-b7d4-4418-8515-93b0c90687a9 · inbound

Position: Uncertainty Quantification in LLMs is Just Unsupervised Clustering cites this paper.

Position: Uncertainty Quantification in LLMs is Just Unsupervised Clustering Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity

Reference 100

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arxiv_id, observed 2026-05-20T06:58:06.245763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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