Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes | Paper Citation Record

Observation b0c9700c-a4ad-406e-936b-e89049b8bc40 · outbound

This paper cites SINdex: Semantic INconsistency Index for Hallucination Detection in LLMs.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes SINdex: Semantic INconsistency Index for Hallucination Detection in LLMs

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Observation b7eeed88-6ce6-442c-9d88-98573f2fc07f · outbound

This paper cites Rajendra Acharya, Vladimir Makarenkov, and Saeid Nahavandi.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Rajendra Acharya, Vladimir Makarenkov, and Saeid Nahavandi

Reference 2

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Observation 54534581-3340-4cac-85b4-0f8f96c6f0c1 · outbound

This paper cites Rethinking Uncertainty Estimation in LLMs: A Principled Single-Sequence Measure.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Rethinking Uncertainty Estimation in LLMs: A Principled Single-Sequence Measure

Reference 3

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Observation 5e1098a3-0757-42e2-8c2d-d2f4af67b312 · outbound

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

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes The internal state of an LLM knows when it’s lying

Reference 4

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Observation e353a58c-9b92-4bdf-b20e-e531ea7aea91 · outbound

This paper cites Qwen2.5-VL Technical Report.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Qwen2.5-VL Technical Report

Reference 5

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This paper cites an unresolved cited work.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Unresolved cited work

Reference 6

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Observation 360158e6-52b8-4f05-926a-e6555a3e06b9 · outbound

This paper cites Post-hoc probabilistic vision-language models.arXiv preprint arXiv:2412.06014, 2024.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Post-hoc probabilistic vision-language models.arXiv preprint arXiv:2412.06014, 2024

Reference 7

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Observation 3826f353-3e14-4fe6-b3f0-aac1249beaaa · outbound

This paper cites Hallucination detec- tion in LLMs using spectral features of attention maps.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Hallucination detec- tion in LLMs using spectral features of attention maps

Reference 8

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Observation 72d189c4-10b0-44e7-a32f-948226217121 · outbound

This paper cites Weight uncertainty in neural network.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Weight uncertainty in neural network

Reference 9

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Observation a10a3650-57d0-4a0b-9061-92c48c7d848e · outbound

This paper cites Popqa: A ques- tion answering benchmark for evaluating the factual consis- tency of language models.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Popqa: A ques- tion answering benchmark for evaluating the factual consis- tency of language models

Reference 10

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Observation ec0a24f4-68de-4526-9cd4-ed24e4b29c7a · outbound

This paper cites INSIDE: LLMs’ internal states retain the power of hallucination detection.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes INSIDE: LLMs’ internal states retain the power of hallucination detection

Reference 11

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Observation 9841133e-9d66-4186-b6f0-dca6ea37f65c · outbound

This paper cites Uncertainty Quantification of Large Language Models through Multi-Dimensional Responses.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Uncertainty Quantification of Large Language Models through Multi-Dimensional Responses

Reference 12

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Observation 496cfc6b-5752-4b0e-aa44-627033009b16 · outbound

This paper cites LM vs LM: Detecting factual errors via cross examination.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes LM vs LM: Detecting factual errors via cross examination

Reference 13

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Observation 34d8a1a7-63af-4e0d-8b4a-13830c536574 · outbound

This paper cites I don't know: Explicit modeling of uncertainty with an [idk] token.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes I don't know: Explicit modeling of uncertainty with an [idk] token

Reference 14

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Observation 18478781-4ca3-4296-a5e7-d133536add54 · outbound

This paper cites Laplace redux-effortless bayesian deep learning.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Laplace redux-effortless bayesian deep learning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:22.954205Z

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Observation 32281d1d-f100-4f2a-bde9-d446e0f10afd · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Imagenet: A large-scale hierarchical image database

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:23.099747Z

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Observation 2fe13635-ccf4-4228-af33-0a5a825a5ac9 · outbound

This paper cites Eigentrack: Spectral activation feature track- ing for hallucination and out-of-distribution detection in llms and vlms.arXiv preprint arXiv:2509.15735, 2025.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Eigentrack: Spectral activation feature track- ing for hallucination and out-of-distribution detection in llms and vlms.arXiv preprint arXiv:2509.15735, 2025

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:23.218633Z

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Observation 4201b8c2-b9ae-4542-8831-c2fbde28d222 · outbound

This paper cites Detecting hallucinations in large language models using semantic entropy.Nature, 2024.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Detecting hallucinations in large language models using semantic entropy.Nature, 2024

Reference 18

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Observation c6f07be8-92ce-4bc6-95b5-65af9401b1b1 · outbound

This paper cites Tradi: Tracking deep neu- ral network weight distributions.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Tradi: Tracking deep neu- ral network weight distributions

Reference 19

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Observation af415ce9-f837-410c-8a7d-403b514cadc6 · outbound

This paper cites Ensembling Pruned Attention Heads For Uncertainty-Aware Efficient Transformers.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Ensembling Pruned Attention Heads For Uncertainty-Aware Efficient Transformers

Reference 20

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Observation 58e4be37-9001-4c48-b36c-f5e82c989c4a · outbound

This paper cites Dropout as a bayesian approximation: Representing model uncertainty in deep learning.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Dropout as a bayesian approximation: Representing model uncertainty in deep learning

Reference 21

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Observation 778e70e9-2606-4e84-a2e5-fde3120c12c4 · outbound

This paper cites SPUQ: Perturbation-based uncertainty quantification for large language models.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes SPUQ: Perturbation-based uncertainty quantification for large language models

Reference 22

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Observation 7f24faa4-1c2d-4d4c-a4d1-fdc7cb4758ce · outbound

This paper cites Improving Uncertainty Quantification in Large Language Models via Semantic Embeddings.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Improving Uncertainty Quantification in Large Language Models via Semantic Embeddings

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:23.746023Z

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Observation bdd0c645-3f98-4f67-9d22-93605edf3501 · outbound

This paper cites On calibration of modern neural networks.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes On calibration of modern neural networks

Reference 24

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Observation 3bbf4a04-9d7e-4180-8ae4-ed6793ba3494 · outbound

This paper cites Deepseek-r1 incentivizes reasoning in llms through reinforcement learning.Nature, 2025.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Deepseek-r1 incentivizes reasoning in llms through reinforcement learning.Nature, 2025

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:23.934381Z

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Observation 66033dec-0519-49f9-810b-9f0daa93bda6 · outbound

This paper cites Vizwiz grand challenge: Answering visual questions from blind people.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Vizwiz grand challenge: Answering visual questions from blind people

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:24.016921Z

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Observation 709eea2d-18ab-4a36-a35b-82ca92cf8608 · outbound

This paper cites {DEBERTA}: {DECODING}-{enhanced} {bert} {with} {disentangled} {attention}.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes {DEBERTA}: {DECODING}-{enhanced} {bert} {with} {disentangled} {attention}

Reference 27

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Observation 0973be2d-dedc-4844-837b-5cadc709035e · outbound

This paper cites A baseline for detect- ing misclassified and out-of-distribution examples in neural networks.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes A baseline for detect- ing misclassified and out-of-distribution examples in neural networks

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:24.266299Z

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Observation 08f10653-3a82-4b7c-b617-4f9b60ca1876 · outbound

This paper cites Prob- abilistic backpropagation for scalable learning of bayesian neural networks.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Prob- abilistic backpropagation for scalable learning of bayesian neural networks

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:24.360703Z

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Observation 0b2f794b-3c55-4c52-8b8b-181050720ad4 · outbound

This paper cites Imagenette: A smaller subset of 10 eas- ily classified classes from imagenet.https://github.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Imagenette: A smaller subset of 10 eas- ily classified classes from imagenet.https://github

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:24.511191Z

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Observation ff395072-fb5d-4cbb-9169-f99c5cfda1ba · outbound

This paper cites A survey on hallucination in large language models: Principles, tax- onomy, challenges, and open questions.TIS, 2025.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes A survey on hallucination in large language models: Principles, tax- onomy, challenges, and open questions.TIS, 2025

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:24.603545Z

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Observation a362761c-b29d-454b-8933-ebf5bcd80a71 · outbound

This paper cites The illusion of progress: Re-evaluating hallucination detec- tion in LLMs.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes The illusion of progress: Re-evaluating hallucination detec- tion in LLMs

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:24.684928Z

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Observation b112cfd7-1fad-4824-9b68-1cfa7a06d868 · outbound

This paper cites Survey of hallucination in natural language generation.CS, 2023.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Survey of hallucination in natural language generation.CS, 2023

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:24.725918Z

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Observation 893f21b0-b576-46a0-9219-dd3775a00322 · outbound

This paper cites Calibrating Verbal Uncertainty as a Linear Feature to Reduce Hallucinations.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Calibrating Verbal Uncertainty as a Linear Feature to Reduce Hallucinations

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:24.791454Z

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Observation 8a8e8ea9-edb5-4f9c-93d2-7067cc6f88d4 · outbound

This paper cites Cleanse: Uncertainty estima- tion approach using clustering-based semantic consistency in LLMs.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Cleanse: Uncertainty estima- tion approach using clustering-based semantic consistency in LLMs

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:24.877745Z

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Observation 49e8be7f-7c10-462a-8c6a-93e93d236c27 · outbound

This paper cites Weld, and Luke Zettle- moyer.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Weld, and Luke Zettle- moyer

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:24.972611Z

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Observation b533b47d-7096-4cf7-85a9-c5820250a364 · outbound

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

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Language Models (Mostly) Know What They Know

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:25.063991Z

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Observation d5c87d45-0a8b-4241-858b-dc75fff2538e · outbound

This paper cites Semantic Entropy Probes: Robust and Cheap Hallucination Detection in LLMs.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Semantic Entropy Probes: Robust and Cheap Hallucination Detection in LLMs

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:25.158930Z

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Observation 2fff7be3-2778-48ff-98f7-cc4231af66a3 · outbound

This paper cites Learning multiple layers of features from tiny images.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Learning multiple layers of features from tiny images

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:25.254217Z

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Observation 94e5ff29-3d83-4604-a4b7-090ce2ca452c · outbound

This paper cites Semantic uncertainty: Linguistic invariances for uncertainty estima- tion in natural language generation.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Semantic uncertainty: Linguistic invariances for uncertainty estima- tion in natural language generation

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:25.376625Z

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Observation 71cae03a-d998-4c63-8122-a99d077ccc23 · outbound

This paper cites Semantic uncertainty: Linguistic invariances for uncertainty estima- tion in natural language generation.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Semantic uncertainty: Linguistic invariances for uncertainty estima- tion in natural language generation

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:25.441914Z

Source-reported events for the cited work

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Observation a365ed00-bd3f-4b71-8a42-65bd45e1e022 · outbound

This paper cites Simple and scalable predictive uncertainty esti- mation using deep ensembles.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Simple and scalable predictive uncertainty esti- mation using deep ensembles

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:25.527448Z

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Observation d10e84d0-2e0c-4047-9489-02ce87219560 · outbound

This paper cites Uncertainty quantification for multimodal large language models with coherence-adjusted semantic volume, 2025.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Uncertainty quantification for multimodal large language models with coherence-adjusted semantic volume, 2025

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:25.628972Z

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Observation 028908eb-6941-4e8f-8842-fc3aec64fe60 · outbound

This paper cites A dataset of clinically generated visual questions and answers about radiology images.Scientific data, 2018.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes A dataset of clinically generated visual questions and answers about radiology images.Scientific data, 2018

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:25.721726Z

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Observation 2f62abd4-107f-4c9a-8a0c-d5a0abbcc252 · outbound

This paper cites What matters when building vision-language models? InNeurIPS, 2024.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes What matters when building vision-language models? InNeurIPS, 2024

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:25.811727Z

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Observation 46a5c1ee-de64-401a-b0f7-82156e0698e5 · outbound

This paper cites Packed-ensembles for efficient uncertainty estima- tion.arXiv preprint arXiv:2210.09184, 2022.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Packed-ensembles for efficient uncertainty estima- tion.arXiv preprint arXiv:2210.09184, 2022

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:25.903527Z

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Observation dcc5ceb8-191b-404b-b3b1-49c3a10802f8 · outbound

This paper cites A Symmetry-Aware Exploration of Bayesian Neural Network Posteriors.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes A Symmetry-Aware Exploration of Bayesian Neural Network Posteriors

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:25.979639Z

Source-reported events for the cited work

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Observation dce41224-c056-406f-8aa3-15998ab2ceeb · outbound

This paper cites Efficient latent semantic clustering for scaling test-time computation of llms, 2025.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Efficient latent semantic clustering for scaling test-time computation of llms, 2025

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:26.111409Z

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Observation 7b1f80fe-c4de-4a15-86d5-a633cdf78047 · outbound

This paper cites Retrieval-augmented generation for knowledge-intensive nlp tasks.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Retrieval-augmented generation for knowledge-intensive nlp tasks

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:26.198286Z

Source-reported events for the cited work

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Observation e33e783d-9020-4c85-9ac2-0a350de44272 · outbound

This paper cites Inference-time intervention: Elic- iting truthful answers from a language model.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Inference-time intervention: Elic- iting truthful answers from a language model

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:26.297311Z

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Observation 321f23f8-ea24-4898-9fd5-770fe2629d51 · outbound

This paper cites Adversarial vqa: A new benchmark for evaluating the robustness of vqa models.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Adversarial vqa: A new benchmark for evaluating the robustness of vqa models

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:26.355177Z

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Observation e5a463f9-663b-4e53-804f-85fbe9d05c42 · outbound

This paper cites Seman- tic volume: Quantifying and detecting both external and in- ternal uncertainty in llms.arXiv preprint arXiv:2502.21239,.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Seman- tic volume: Quantifying and detecting both external and in- ternal uncertainty in llms.arXiv preprint arXiv:2502.21239,

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:26.466825Z

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Observation 9632db36-4977-47f5-bb89-87b0cf58e120 · outbound

This paper cites Teaching models to express their uncertainty in words.TMLR, 2022.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Teaching models to express their uncertainty in words.TMLR, 2022

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:26.589802Z

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Observation 31e376ff-b879-4141-b48d-74a7331659b9 · outbound

This paper cites Generat- ing with confidence: Uncertainty quantification for black- box large language models.TMLR, 2024.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Generat- ing with confidence: Uncertainty quantification for black- box large language models.TMLR, 2024

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:26.653848Z

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Observation cd88ef64-63b1-46ba-b151-0334e0ba6af1 · outbound

This paper cites Improved baselines with visual instruction tuning.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Improved baselines with visual instruction tuning

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:26.712358Z

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Observation a4dcbfc0-3deb-4b35-a28f-7cc2ba78b289 · outbound

This paper cites A Survey on Hallucination in Large Vision-Language Models.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes A Survey on Hallucination in Large Vision-Language Models

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:26.799581Z

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Unavailable: canonical work link unavailable.

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This paper cites Probable networks and plausible predictions-a review of practical bayesian methods for su- pervised neural networks.Network: computation in neural systems, 1995.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Probable networks and plausible predictions-a review of practical bayesian methods for su- pervised neural networks.Network: computation in neural systems, 1995

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:26.896036Z

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Observation 40b9759f-93f6-42e2-b134-11600927c376 · outbound

This paper cites CalTech, 1992.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes CalTech, 1992

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:26.954293Z

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Unavailable: canonical work link unavailable.

Observation 91fb43e0-74fa-40e9-ac44-0eecff6a719d · outbound

This paper cites A simple baseline for bayesian uncertainty in deep learning.NeurIPS, 2019.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes A simple baseline for bayesian uncertainty in deep learning.NeurIPS, 2019

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:27.041521Z

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Unavailable: canonical work link unavailable.

Observation 4382f77e-ae6e-4b91-8c4f-cababc934955 · outbound

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Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Uncertainty estimation in autoregressive structured prediction

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:27.129117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9ffcc773-dfa3-4108-9c84-d36931c65cfd · outbound

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Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Self- CheckGPT: Zero-resource black-box hallucination detection for generative large language models

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:27.196512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4de0ca17-7e48-4d37-8df2-c25280477c31 · outbound

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Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Ok-vqa: A visual question answering benchmark requiring external knowledge

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:27.284839Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eabc67e2-1dda-43e4-8fa3-7c63e880f529 · outbound

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Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes MIT press, 2012

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:27.409384Z

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Observation fc0f1240-f4f0-438b-9291-5bd9ba2498df · outbound

This paper cites Correcting length bias in neural machine translation.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Correcting length bias in neural machine translation

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:27.571589Z

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Unavailable: canonical work link unavailable.

Observation 0d888058-b429-4096-8c84-6c3676562a34 · outbound

This paper cites Springer Science & Business Media, 2012.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Springer Science & Business Media, 2012

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:27.702032Z

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Observation 992f638b-922b-41ea-9c64-0e0ee937a1b0 · outbound

This paper cites Be- yond semantic entropy: Boosting LLM uncertainty quantifi- cation with pairwise semantic similarity.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Be- yond semantic entropy: Boosting LLM uncertainty quantifi- cation with pairwise semantic similarity

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:27.823732Z

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Observation 03959f3f-2bf3-42d0-a2cf-dc7a67fae6e0 · outbound

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Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Kernel language entropy: Fine-grained uncer- tainty quantification for llms from semantic similarities

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:27.950615Z

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Observation b0bf1ece-995b-4979-a518-174ea8a1bb72 · outbound

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Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes AlphaEvolve: A coding agent for scientific and algorithmic discovery

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:28.071045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 30ae742d-a613-4cf1-baec-ed5ccf662896 · outbound

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Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes LLMs know more than they show: On the intrinsic representation of LLM hallucinations

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:28.148467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b51f9ad9-3528-44cd-9740-20b265342546 · outbound

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Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Semantic density: Uncer- tainty quantification for large language models through con- fidence measurement in semantic space

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:28.185630Z

Source-reported events for the cited work

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Observation bdd12321-995b-4516-b848-d3ccc21007da · outbound

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Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Unresolved cited work

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:28.263911Z

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Unavailable: canonical work link unavailable.

Observation 7e4051b0-0ce9-4896-baa9-c0bf61a6ce34 · outbound

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Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:28.321101Z

Source-reported events for the cited work

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Observation 0ba794d8-1d7c-488f-81df-397d15ade06b · outbound

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Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Out- of-distribution detection and selective generation for condi- tional language models

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:28.377108Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2260ddcf-1c0c-419a-8a02-4dc9baeac514 · outbound

This paper cites A scal- able laplace approximation for neural networks.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes A scal- able laplace approximation for neural networks

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:28.459485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 447541a6-007c-479e-9d01-e56c791cc039 · outbound

This paper cites MIT press, 2002.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes MIT press, 2002

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:28.543535Z

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Observation 826793cd-52f3-40f5-bc27-e36029b7823e · outbound

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Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Unresolved cited work

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:28.660474Z

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Unavailable: canonical work link unavailable.

Observation 3087c9ff-47ee-4c9b-9d25-3088d998fe25 · outbound

This paper cites Layer by layer: Uncovering hidden representations in lan- guage models.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Layer by layer: Uncovering hidden representations in lan- guage models

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:28.778702Z

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Observation d7f626fc-e4cf-4264-89ff-9e1a5c29a575 · outbound

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Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Llm-check: Investigating detection of hallucinations in large language models

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:28.890011Z

Source-reported events for the cited work

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Observation f6200473-a878-4e94-98fe-58b882e82127 · outbound

This paper cites Gemini 1.5: Unlocking multimodal under- standing across millions of tokens of context, 2024.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Gemini 1.5: Unlocking multimodal under- standing across millions of tokens of context, 2024

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:28.921878Z

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Observation 1fc7176a-5d23-409d-92ed-f55af11ab4b1 · outbound

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Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes The llama 3 herd of models, 2024

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:29.000472Z

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Observation 2dc8aef9-f3f7-4613-a524-a03edd9dd65a · outbound

This paper cites Gpt-4 technical report, 2024.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Gpt-4 technical report, 2024

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:29.057172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd092140-f360-4002-83cf-d1ce772606f3 · outbound

This paper cites gpt-oss-120b and gpt-oss-20b model card,.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes gpt-oss-120b and gpt-oss-20b model card,

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:29.114528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e475cadb-9789-4dea-befd-89aa333b84c5 · outbound

This paper cites DeepSeek-OCR: Contexts Optical Compression.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes DeepSeek-OCR: Contexts Optical Compression

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:29.169533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 266b14a9-d601-48cb-8d8e-172d50bca622 · outbound

This paper cites Batchensemble: an alternative approach to efficient ensemble and lifelong learning, 2020.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Batchensemble: an alternative approach to efficient ensemble and lifelong learning, 2020

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:29.228439Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36cf4c3e-e28f-4906-a2e1-bde6fff37870 · outbound

This paper cites Gaussian processes for machine learning.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Gaussian processes for machine learning

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:29.278432Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ae43fc6-b5c2-47fc-8660-7071f8d2c299 · outbound

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Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Unresolved cited work

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:29.331733Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7ef378b-40fd-4f59-a19e-25d06754ba4c · outbound

This paper cites TokUR: Token-Level Uncertainty Estimation for Large Language Model Reasoning.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes TokUR: Token-Level Uncertainty Estimation for Large Language Model Reasoning

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:29.383723Z

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Observation fd845a0b-2a58-4f19-91dc-d4c24bb261a9 · outbound

This paper cites Understanding Neural Networks with Logarithm Determinant Entropy Estimator.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Understanding Neural Networks with Logarithm Determinant Entropy Estimator

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:29.437805Z

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Observation 8c7e85e9-dcfe-4c81-8964-16adf6bab588 · outbound

This paper cites Understanding neural net- works with logarithm determinant entropy estimator.Neuro- computing, 2025.

Improving Semantic Uncertainty Quantification in LVLMs with Semantic Gaussian Processes Understanding neural net- works with logarithm determinant entropy estimator.Neuro- computing, 2025

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-03T16:16:29.497121Z

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