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Paper Citation Record · LEDGER

Neural Message-Passing on Attention Graphs for Hallucination Detection

As of 18 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 0 inbound Pith citation observations for arXiv:2509.24770.

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

pith.paper-citation-record.v1
2509.24770 v2

Coverage vector

measured 58 of 58 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T13:52:13.274742Z

measured 58 of 58 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

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measured 0 of 1 external citation measurements

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Reference resolution

58 of 58 outbound references displayed

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Outbound references

Observation 67051ea1-489b-46c2-b573-086d0ce2af7a · outbound

This paper cites On the bottleneck of graph neural networks and its practical implications.International Conference on Learning Representations, 2021.

Neural Message-Passing on Attention Graphs for Hallucination Detection On the bottleneck of graph neural networks and its practical implications.International Conference on Learning Representations, 2021

Reference 1

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Observation a034adb9-a204-4e9b-a27b-40f7ecf590ed · outbound

This paper cites The internal state of an llm knows when it’s lying.

Neural Message-Passing on Attention Graphs for Hallucination Detection The internal state of an llm knows when it’s lying

Reference 2

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Observation 8d61c73f-2000-4dc7-bdc8-33013e975aca · outbound

This paper cites Learning on llm output signatures for gray-box behavior analysis.

Neural Message-Passing on Attention Graphs for Hallucination Detection Learning on llm output signatures for gray-box behavior analysis

Reference 3

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Observation 41b7eb22-b296-4e9c-82a8-777b887f2b78 · outbound

This paper cites Araújo, Alex Vitvitskyi, Razvan Pascanu, and Petar Veličković.

Neural Message-Passing on Attention Graphs for Hallucination Detection Araújo, Alex Vitvitskyi, Razvan Pascanu, and Petar Veličković

Reference 4

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Observation 544ffd13-dee5-4ebc-9c7c-294f60432cfa · outbound

This paper cites Relational inductive biases, deep learning, and graph networks.

Neural Message-Passing on Attention Graphs for Hallucination Detection Relational inductive biases, deep learning, and graph networks

Reference 5

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Observation 01684a3f-958a-45a6-96f1-bf2dba83daf3 · outbound

This paper cites Hallucination Detection in LLMs with Topological Divergence on Attention Graphs.

Neural Message-Passing on Attention Graphs for Hallucination Detection Hallucination Detection in LLMs with Topological Divergence on Attention Graphs

Reference 6

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Observation d083d475-027b-46d2-8b9e-190fe9ee430a · outbound

This paper cites Probing classifiers: Promises, shortcomings, and advances.Computational Linguistics, 48(1):207–219, 2022.

Neural Message-Passing on Attention Graphs for Hallucination Detection Probing classifiers: Promises, shortcomings, and advances.Computational Linguistics, 48(1):207–219, 2022

Reference 7

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Observation 527889fe-5ea1-4bd2-9561-3aa5ef812170 · outbound

This paper cites Experiment tracking with weights and biases, 2020.

Neural Message-Passing on Attention Graphs for Hallucination Detection Experiment tracking with weights and biases, 2020

Reference 8

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Observation 94a610a5-87e0-453e-b1e6-cd99f847f027 · outbound

This paper cites Hallucination detection in llms using spectral features of attention maps.arXiv:2502.17598, 2025.

Neural Message-Passing on Attention Graphs for Hallucination Detection Hallucination detection in llms using spectral features of attention maps.arXiv:2502.17598, 2025

Reference 9

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Observation b9f8d589-fb1d-421f-b447-01e879dbc9e5 · outbound

This paper cites Discovering Latent Knowledge in Language Models Without Supervision.

Neural Message-Passing on Attention Graphs for Hallucination Detection Discovering Latent Knowledge in Language Models Without Supervision

Reference 10

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Observation 454ce29b-0f4b-4898-b2df-d2d63437a3d8 · outbound

This paper cites Hallucinated but factual! inspecting the factuality of hallucinations in abstractive summarization.

Neural Message-Passing on Attention Graphs for Hallucination Detection Hallucinated but factual! inspecting the factuality of hallucinations in abstractive summarization

Reference 11

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Observation 3ca4c8b3-2503-4078-a489-5be42c24c029 · outbound

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

Neural Message-Passing on Attention Graphs for Hallucination Detection INSIDE: LLMs' Internal States Retain the Power of Hallucination Detection

Reference 12

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Observation 47699508-7c9b-426e-83a5-f2416f7180b4 · outbound

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Neural Message-Passing on Attention Graphs for Hallucination Detection Unresolved cited work

Reference 13

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Observation 10732cf6-1bde-4d34-b85d-82ac9954bbfa · outbound

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Neural Message-Passing on Attention Graphs for Hallucination Detection Unresolved cited work

Reference 14

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Observation 2dd7c3c6-31c2-4ef9-ae1e-b12e87ea20c3 · outbound

This paper cites Fast graph representation learning with PyTorch Geometric.

Neural Message-Passing on Attention Graphs for Hallucination Detection Fast graph representation learning with PyTorch Geometric

Reference 15

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Observation 12ad1ab7-8a9c-4d8c-93b7-70b636061da8 · outbound

This paper cites Schoenholz, Patrick F.

Neural Message-Passing on Attention Graphs for Hallucination Detection Schoenholz, Patrick F

Reference 16

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Observation 1196f1a3-fe99-47d2-9783-628be08c082c · outbound

This paper cites Bronstein, and Kirill Veselkov.

Neural Message-Passing on Attention Graphs for Hallucination Detection Bronstein, and Kirill Veselkov

Reference 17

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Observation 9292f352-3d1b-4c4b-9073-a73c98c35c0a · outbound

This paper cites Looking for a Needle in a Haystack: A Comprehensive Study of Hallucinations in Neural Machine Translation.

Neural Message-Passing on Attention Graphs for Hallucination Detection Looking for a Needle in a Haystack: A Comprehensive Study of Hallucinations in Neural Machine Translation

Reference 18

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Observation bebc7ce7-0457-48f9-b219-938b4896d90c · outbound

This paper cites A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions.ACM Transactions on Information Systems, 2023.

Neural Message-Passing on Attention Graphs for Hallucination Detection A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions.ACM Transactions on Information Systems, 2023

Reference 19

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Observation 7d51c7d5-ae77-44e2-81ab-67c99bb17bdb · outbound

This paper cites Look Before You Leap: An Exploratory Study of Uncertainty Measurement for Large Language Models.

Neural Message-Passing on Attention Graphs for Hallucination Detection Look Before You Leap: An Exploratory Study of Uncertainty Measurement for Large Language Models

Reference 20

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Observation ca77e54b-2347-4fe7-a8bd-818c1edf36f8 · outbound

This paper cites Survey of hallucination in natural language generation.

Neural Message-Passing on Attention Graphs for Hallucination Detection Survey of hallucination in natural language generation

Reference 21

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Observation 078b3b65-5f1f-4e88-85e9-cb9464f6b5e8 · outbound

This paper cites Mistral 7B.

Neural Message-Passing on Attention Graphs for Hallucination Detection Mistral 7B

Reference 22

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Observation e3b21d57-1a2d-4fe6-8088-37b439926265 · outbound

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

Neural Message-Passing on Attention Graphs for Hallucination Detection Language Models (Mostly) Know What They Know

Reference 23

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Observation 7d324d16-4866-4d5c-934c-9f592b0ed3fe · outbound

This paper cites Kipf and Max Welling.

Neural Message-Passing on Attention Graphs for Hallucination Detection Kipf and Max Welling

Reference 24

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Observation a607b607-28e7-4e41-9213-a67e89b05133 · outbound

This paper cites Semantic Uncertainty: Linguistic Invariances for Uncertainty Estimation in Natural Language Generation.

Neural Message-Passing on Attention Graphs for Hallucination Detection Semantic Uncertainty: Linguistic Invariances for Uncertainty Estimation in Natural Language Generation

Reference 25

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Observation 69d68ed5-bfad-4f0a-b278-bd5c7a0f940c · outbound

This paper cites Dai, Jakob Uszkoreit, Quoc Le, and Slav Petrov.

Neural Message-Passing on Attention Graphs for Hallucination Detection Dai, Jakob Uszkoreit, Quoc Le, and Slav Petrov

Reference 26

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Observation ff27e560-66fb-4a51-b686-8590dc2b80fa · outbound

This paper cites Inference- time intervention: Eliciting truthful answers from a language model.Advances in Neural Information Processing Systems, 36, 2024.

Neural Message-Passing on Attention Graphs for Hallucination Detection Inference- time intervention: Eliciting truthful answers from a language model.Advances in Neural Information Processing Systems, 36, 2024

Reference 27

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Observation 2e61eb11-c94b-406d-a7e1-8b8415517d00 · outbound

This paper cites Deep learning-guided discovery of an antibiotic targeting acinetobacter baumannii.

Neural Message-Passing on Attention Graphs for Hallucination Detection Deep learning-guided discovery of an antibiotic targeting acinetobacter baumannii

Reference 28

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Observation 79074754-cb63-476b-8a01-0ab07766f9c8 · outbound

This paper cites A Token-level Reference-free Hallucination Detection Benchmark for Free-form Text Generation.

Neural Message-Passing on Attention Graphs for Hallucination Detection A Token-level Reference-free Hallucination Detection Benchmark for Free-form Text Generation

Reference 29

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Observation df394fc1-5251-401d-89fa-7306f0352a74 · outbound

This paper cites Decoupled Weight Decay Regularization.

Neural Message-Passing on Attention Graphs for Hallucination Detection Decoupled Weight Decay Regularization

Reference 30

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Observation 2c142426-4325-4a85-8a35-95ae4100c11d · outbound

This paper cites SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models.

Neural Message-Passing on Attention Graphs for Hallucination Detection SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models

Reference 31

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Observation a3027d7e-7a62-4a24-98a1-3c0f2dc64fae · outbound

This paper cites The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets.

Neural Message-Passing on Attention Graphs for Hallucination Detection The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets

Reference 32

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Observation 3c9dbd59-e287-49cf-8147-913147c7bed1 · outbound

This paper cites Bronstein.

Neural Message-Passing on Attention Graphs for Hallucination Detection Bronstein

Reference 33

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Observation fa1a655e-7fc7-42c6-933c-6a7fab1c6f76 · outbound

This paper cites LLMs Know More Than They Show: On the Intrinsic Representation of LLM Hallucinations.

Neural Message-Passing on Attention Graphs for Hallucination Detection LLMs Know More Than They Show: On the Intrinsic Representation of LLM Hallucinations

Reference 34

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Observation 32c1902c-bbbe-4950-bb15-9c133b5b496d · outbound

This paper cites Understanding factuality in abstractive summarization with FRANK: A benchmark for factuality metrics.

Neural Message-Passing on Attention Graphs for Hallucination Detection Understanding factuality in abstractive summarization with FRANK: A benchmark for factuality metrics

Reference 35

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Observation a330d24c-7eaa-4898-be84-e4bdf9a6859e · outbound

This paper cites Pytorch: An imperative style, high- performance deep learning library.

Neural Message-Passing on Attention Graphs for Hallucination Detection Pytorch: An imperative style, high- performance deep learning library

Reference 36

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source=pdf_text observed=2026-08-04T13:52:11.128353Z digest=sha256:92ab41e49b516a9822a5d16dba5aee025a96f2e8337480489ea7870a09c7a1f1

Observation 17a190b4-c396-41a6-b02e-9f4bbd8c81d1 · outbound

This paper cites Approximation theory of the mlp model in neural networks.Acta Numerica, 8: 143–195, 1999.

Neural Message-Passing on Attention Graphs for Hallucination Detection Approximation theory of the mlp model in neural networks.Acta Numerica, 8: 143–195, 1999

Reference 37

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Observation 1b6e0db6-1359-45d7-ae18-c1b74b85f905 · outbound

This paper cites Learning representations of irregular particle-detector geometry with distance-weighted graph networks.The European Physical Journal C, 79(7), 2019.

Neural Message-Passing on Attention Graphs for Hallucination Detection Learning representations of irregular particle-detector geometry with distance-weighted graph networks.The European Physical Journal C, 79(7), 2019

Reference 38

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source=pdf_text observed=2026-08-04T13:52:11.411461Z digest=sha256:9eabaa5cb5d1b1222c856c08aa89b418630d8376206c4288bbdb53e592961f72

Observation 68102a62-41d1-46ea-a0ce-6be6242898bb · outbound

This paper cites Detecting and mitigating hallucinations in multilingual summarisation.

Neural Message-Passing on Attention Graphs for Hallucination Detection Detecting and mitigating hallucinations in multilingual summarisation

Reference 39

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Observation ed7dc1ea-972c-43d2-b9f1-8f9818292eda · outbound

This paper cites Weakly Supervised Detection of Hallucinations in LLM Activations.

Neural Message-Passing on Attention Graphs for Hallucination Detection Weakly Supervised Detection of Hallucinations in LLM Activations

Reference 40

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source=pdf_text observed=2026-08-04T13:52:11.610404Z digest=sha256:55be9fb2696ef90c7ec4c85f47de75fbd964e363f839e2cae0b0d2fb18858c8c

Observation b0c29b6f-6023-43b0-acb5-de9d174f70b1 · outbound

This paper cites The Troubling Emergence of Hallucination in Large Language Models -- An Extensive Definition, Quantification, and Prescriptive Remediations.

Neural Message-Passing on Attention Graphs for Hallucination Detection The Troubling Emergence of Hallucination in Large Language Models -- An Extensive Definition, Quantification, and Prescriptive Remediations

Reference 41

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source=pdf_text observed=2026-08-04T13:52:11.749018Z digest=sha256:cf7426bb8d429b104576d923f616b22150356aca29ea4f74f4aeddf3a154c386

Observation ff343da3-12e9-49cc-a535-7d60dc2de632 · outbound

This paper cites Liu, and Christopher D.

Neural Message-Passing on Attention Graphs for Hallucination Detection Liu, and Christopher D

Reference 42

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source=pdf_text observed=2026-08-04T13:52:11.876833Z digest=sha256:fab1bd71e5c14bdee1263c9f7e42b0dd3ccce74ba8c0e8abbba1c17fb66ba4c7

Observation c957507e-0d4b-4c15-b5ff-dc7060c34a5a · outbound

This paper cites Constructing Benchmarks and Interventions for Combating Hallucinations in LLMs.

Neural Message-Passing on Attention Graphs for Hallucination Detection Constructing Benchmarks and Interventions for Combating Hallucinations in LLMs

Reference 43

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source=pdf_text observed=2026-08-04T13:52:11.959026Z digest=sha256:de0cbb4a4e8672ac9c10f63cdbc2a9e3ba2cbc98e5f6131c81586f015d568941

Observation 8ff04ac7-c074-4305-9106-b60c13e9ce46 · outbound

This paper cites On early detection of hallucinations in factual question answering.

Neural Message-Passing on Attention Graphs for Hallucination Detection On early detection of hallucinations in factual question answering

Reference 44

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source=pdf_text observed=2026-08-04T13:52:12.038722Z digest=sha256:291a30c0d2f766e44309c475f210a64f7d1e64fa34871b94a4ad52e55071e22c

Observation cbf3f2bc-d0dd-4ca4-95e9-dba7da97983e · outbound

This paper cites Llm-check: Investigating detection of hallucinations in large language models.

Neural Message-Passing on Attention Graphs for Hallucination Detection Llm-check: Investigating detection of hallucinations in large language models

Reference 45

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source=pdf_text observed=2026-08-04T13:52:12.125499Z digest=sha256:4415d98d9be6d7f76b16f92897792c16957973832bbe63220e923874c6210946

Observation 420f41be-6085-444a-962d-45ce088f0093 · outbound

This paper cites Stokes, Kevin Yang, Kyle Swanson, Wengong Jin, Andres Cubillos-Ruiz, Nina M.

Neural Message-Passing on Attention Graphs for Hallucination Detection Stokes, Kevin Yang, Kyle Swanson, Wengong Jin, Andres Cubillos-Ruiz, Nina M

Reference 46

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source=pdf_text observed=2026-08-04T13:52:12.191295Z digest=sha256:7b52a4462c0ee7d8ad779db0ac893de12beacbded5c76d1034ca3775d5fc1af8

Observation 30fd6803-76c7-4009-9a5d-4c3c208ccb52 · outbound

This paper cites Benchmarking Hallucination in Large Language Models based on Unanswerable Math Word Problem.

Neural Message-Passing on Attention Graphs for Hallucination Detection Benchmarking Hallucination in Large Language Models based on Unanswerable Math Word Problem

Reference 47

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source=pdf_text observed=2026-08-04T13:52:12.288648Z digest=sha256:8683fa079570704e6bcab71e3014ccde583efa8932832e678986d4609fbbbd3a

Observation e2fda75e-e813-409e-8596-076fd367d560 · outbound

This paper cites Chamberlain, Xiaowen Dong, and Michael M.

Neural Message-Passing on Attention Graphs for Hallucination Detection Chamberlain, Xiaowen Dong, and Michael M

Reference 48

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source=pdf_text observed=2026-08-04T13:52:12.374196Z digest=sha256:058b53ed102d2e59c6f3a52f445f0fc3e15c479892052948a75991fa0151d521

Observation dd0545ea-6112-4b86-bd84-1976552424f3 · outbound

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

Neural Message-Passing on Attention Graphs for Hallucination Detection Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 49

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source=pdf_text observed=2026-08-04T13:52:12.562585Z digest=sha256:5ddd66ff3412ebcd0fc08a81d35ed03fbbfa86cb17d9f704636f21ae5c221882

Observation 90612cb0-acac-4a68-aa36-b0018849d569 · outbound

This paper cites A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation.

Neural Message-Passing on Attention Graphs for Hallucination Detection A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Reference 50

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source=pdf_text observed=2026-08-04T13:52:12.628427Z digest=sha256:e6aaba67eff08ff3d43c3b84b6cbfe00809be7daffb29e03d6b4dd72960db7c6

Observation 69b240d0-25bc-4b56-9acf-01b45c3eb96c · outbound

This paper cites an unresolved cited work.

Neural Message-Passing on Attention Graphs for Hallucination Detection Unresolved cited work

Reference 51

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source=pdf_text observed=2026-08-04T13:52:12.700464Z digest=sha256:e7548483bc011652ff3bb503142e4641060391cba66cfb297047c558fe1b2511

Observation dca17e22-aae8-4a0a-a392-fda840f479fc · outbound

This paper cites Martindale, and Marine Carpuat.

Neural Message-Passing on Attention Graphs for Hallucination Detection Martindale, and Marine Carpuat

Reference 52

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source=pdf_text observed=2026-08-04T13:52:12.763817Z digest=sha256:dc4f7474c81af1ed8869279187926d5a16af844f9e69a948028551e1d24ed880

Observation 078e2312-3137-4546-9d68-36e378522202 · outbound

This paper cites Characterizing Truthfulness in Large Language Model Generations with Local Intrinsic Dimension.

Neural Message-Passing on Attention Graphs for Hallucination Detection Characterizing Truthfulness in Large Language Model Generations with Local Intrinsic Dimension

Reference 53

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source=pdf_text observed=2026-08-04T13:52:12.846283Z digest=sha256:816b94966056f6fd3df744c2d70204f6b89d0897cf92da7a4e0445192818ed8d

Observation 34bc7b12-c00c-4da3-9b83-30b507bcbfc7 · outbound

This paper cites Attention Satisfies: A Constraint-Satisfaction Lens on Factual Errors of Language Models.

Neural Message-Passing on Attention Graphs for Hallucination Detection Attention Satisfies: A Constraint-Satisfaction Lens on Factual Errors of Language Models

Reference 54

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source=pdf_text observed=2026-08-04T13:52:12.931113Z digest=sha256:42b86084c961b1e51622c65b9ad363518ab475e2ebc684deaeb66c66c679ce7f

Observation 14b2ee32-5c5c-48b5-9474-b292a886ec9f · outbound

This paper cites Enhancing uncertainty-based hallucination detection with stronger focus.

Neural Message-Passing on Attention Graphs for Hallucination Detection Enhancing uncertainty-based hallucination detection with stronger focus

Reference 55

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source=pdf_text observed=2026-08-04T13:52:12.993982Z digest=sha256:7b7257134b609d00a4baa68d41514c1c1ae04ed56bd51996848eeb2e0dc6204a

Observation ba0a7ef0-4ffe-4c59-a318-cc1d006cef52 · outbound

This paper cites Gender bias in coreference resolution: Evaluation and debiasing methods.

Neural Message-Passing on Attention Graphs for Hallucination Detection Gender bias in coreference resolution: Evaluation and debiasing methods

Reference 56

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source=pdf_text observed=2026-08-04T13:52:13.057904Z digest=sha256:7598054486c45ceb06df1ef5e2e95ba9b83ea35da66ded29f3e5c9c2002a1a7c

Observation e4322b94-4934-4008-998d-52081c4f84c9 · outbound

This paper cites Representation Engineering: A Top-Down Approach to AI Transparency.

Neural Message-Passing on Attention Graphs for Hallucination Detection Representation Engineering: A Top-Down Approach to AI Transparency

Reference 57

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source=pdf_text observed=2026-08-04T13:52:13.274742Z digest=sha256:facfe376a2894a48daac836530f92ae718d82b69861d1fda17ddffefe9d9d786

Observation 21ed9831-e69d-4ad7-a0e8-7f7a0dea1f85 · outbound

This paper cites an unresolved cited work.

Neural Message-Passing on Attention Graphs for Hallucination Detection Unresolved cited work

Reference 2018

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