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Paper Citation Record · LEDGER

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models

As of 7 August 2026, this Paper Citation Record lists 90 of 90 outbound references and 1 inbound Pith citation observation for arXiv:2506.07575.

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

pith.paper-citation-record.v1
2506.07575 v1

Coverage vector

measured 90 of 90 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:36:15.819379Z

measured 91 of 91 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-26T17:46:00.822375Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T03:39:30.608876Z

Reference resolution

90 of 90 outbound references displayed

  • verified exact5
  • verified fuzzy32
  • unresolved52
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 70721b71-9a16-4c3f-991a-9fbf08de0d47 · outbound

This paper cites GPT-4 Technical Report.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models GPT-4 Technical Report

Reference 1

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Observation dd960f05-75e3-4b49-a081-7afd2d699de5 · outbound

This paper cites How many opinions does your llm have? improving uncertainty estimation in nlg.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models How many opinions does your llm have? improving uncertainty estimation in nlg

Reference 2

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Observation 9ab4718f-62d3-46dd-b731-b3e6c9d34225 · outbound

This paper cites Multimodal Automated Fact-Checking: A Survey.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Multimodal Automated Fact-Checking: A Survey

Reference 3

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Observation e39b9aa9-92d2-4f03-9716-e2b4b419173d · outbound

This paper cites Knowledge of Knowledge: Exploring Known-Unknowns Uncertainty with Large Language Models.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Knowledge of Knowledge: Exploring Known-Unknowns Uncertainty with Large Language Models

Reference 4

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source=pdf_text observed=2026-08-07T05:36:15.445213Z digest=sha256:1e7cb191ebe55236da36ba243a2db8651b27ef90ee81ae298029ea86e7f35422

Observation a6bc3eba-a7d4-4d35-9603-09149144f8b9 · outbound

This paper cites Predicting and understanding human action decisions during skillful joint-action using supervised machine learning and explainable-ai.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Predicting and understanding human action decisions during skillful joint-action using supervised machine learning and explainable-ai

Reference 5

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source=pdf_text observed=2026-08-07T05:36:15.450516Z digest=sha256:e24019c7f5ec17ff5b8b8433329c54ecea810d6e7eeaf7d6ed62e221282443f9

Observation 5b218547-f80c-47a5-a32e-b5b5f7b2d477 · outbound

This paper cites Qwen-vl: A versatile vision-language model for un- derstanding, localization, text reading, and beyond, 2023.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Qwen-vl: A versatile vision-language model for un- derstanding, localization, text reading, and beyond, 2023

Reference 6

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source=pdf_text observed=2026-08-07T05:36:15.455158Z digest=sha256:28ad90395449a2b489962694612121a31897c97ccdf044a7c64456787b09f668

Observation c5614c95-8b66-486c-9645-aac77201f808 · outbound

This paper cites Hallucination of Multimodal Large Language Models: A Survey.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Hallucination of Multimodal Large Language Models: A Survey

Reference 7

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source=pdf_text observed=2026-08-07T05:36:15.461202Z digest=sha256:53295eb33b1092397bef7f868708594cad32936fc15ed5e1e2d892418b1f4066

Observation 5db89a14-a179-4fcf-82e6-514f3fea699e · outbound

This paper cites Lan- guage models are few-shot learners.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Lan- guage models are few-shot learners

Reference 8

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Observation 7793d10b-c01a-4ba6-b99c-5e5d07611216 · outbound

This paper cites The revolution of multimodal large language models: a survey.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models The revolution of multimodal large language models: a survey

Reference 9

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source=pdf_text observed=2026-08-07T05:36:15.471048Z digest=sha256:3dba19fa43514b095155d408fdf8eea86f84bf4f96c61b719c7356095ed9138e

Observation dcc92c32-0aee-4b3b-a192-185d53e1dbd8 · outbound

This paper cites Rational use of cognitive resources in human planning.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Rational use of cognitive resources in human planning

Reference 10

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Observation 71f318e2-1579-4182-b768-4d14b299a69d · outbound

This paper cites A Review of Multi-Modal Large Language and Vision Models.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models A Review of Multi-Modal Large Language and Vision Models

Reference 11

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Observation 778e27d7-e173-4975-b03c-8f1f85040522 · outbound

This paper cites ShapeNet: An Information-Rich 3D Model Repository.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models ShapeNet: An Information-Rich 3D Model Repository

Reference 12

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source=pdf_text observed=2026-08-07T05:36:15.484473Z digest=sha256:fc1a27b3614ec73ad6ab52fec3706d9f58f6204ce6aaa169f2a089370b2c61f7

Observation 8e19de4c-965d-4307-a9e4-d5dd6321d415 · outbound

This paper cites Microsoft COCO Captions: Data Collection and Evaluation Server.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Microsoft COCO Captions: Data Collection and Evaluation Server

Reference 13

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source=pdf_text observed=2026-08-07T05:36:15.489481Z digest=sha256:f472be6c9b0ac35d9a726bc9bf6a52f1d18fb694db611766787a0aa4809c95d9

Observation 376f40cc-73b1-4818-95c8-fbb7dec15dbc · outbound

This paper cites Unified Hallucination Detection for Multimodal Large Language Models.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Unified Hallucination Detection for Multimodal Large Language Models

Reference 14

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Observation ebdf2bfd-a829-47a8-b447-09ce69d6f26a · outbound

This paper cites Unveiling Uncertainty: A Deep Dive into Calibration and Performance of Multimodal Large Language Models.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Unveiling Uncertainty: A Deep Dive into Calibration and Performance of Multimodal Large Language Models

Reference 15

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source=pdf_text observed=2026-08-07T05:36:15.499186Z digest=sha256:5eb7abec7c2ead8d0d43b35fbf0e2317f09cbd8d26f9f5e68b79d2205fcefdfd

Observation 325846ed-c0dd-43d1-93f4-c8591d9a2503 · outbound

This paper cites Internvl: Scaling up vision foundation mod- els and aligning for generic visual-linguistic tasks.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Internvl: Scaling up vision foundation mod- els and aligning for generic visual-linguistic tasks

Reference 16

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Observation e3efa6ed-bb55-4cda-9db9-f157a4f2a760 · outbound

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

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models I don’t know: Explicit modeling of uncertainty with an [idk] token

Reference 17

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Observation ca946fa2-aa29-4d04-ab07-3c5d5c2bb9ce · outbound

This paper cites Human uncertainty in concept-based ai systems.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Human uncertainty in concept-based ai systems

Reference 18

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Observation ed92ce87-3568-4fcf-a237-420118f28b56 · outbound

This paper cites Objaverse: A universe of annotated 3d objects.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Objaverse: A universe of annotated 3d objects

Reference 19

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Observation 97b9a2c7-0104-4af2-9a91-389aedb00c99 · outbound

This paper cites Retrieve only when it needs: Adaptive re- trieval augmentation for hallucination mitigation in large lan- guage models.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Retrieve only when it needs: Adaptive re- trieval augmentation for hallucination mitigation in large lan- guage models

Reference 20

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Observation 7af75ba0-58a5-4ae3-a999-229f03909fb8 · outbound

This paper cites Clotho: An audio captioning dataset.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Clotho: An audio captioning dataset

Reference 21

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Observation e38279b1-d0d4-49ef-bde6-99226a0032bb · outbound

This paper cites PUMA: Empowering Unified MLLM with Multi-granular Visual Generation.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models PUMA: Empowering Unified MLLM with Multi-granular Visual Generation

Reference 22

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Observation 0b6b566e-5ccb-4483-b7ed-342084bcd31f · outbound

This paper cites From uncertainty to trust: Enhancing re- liability in vision-language models with uncertainty-guided dropout decoding.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models From uncertainty to trust: Enhancing re- liability in vision-language models with uncertainty-guided dropout decoding

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation e806c30d-0123-4821-90e1-c11fae348f40 · outbound

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

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Detecting hallucinations in large language models using semantic entropy

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 2347e678-cf70-4e00-b626-809cef25365c · outbound

This paper cites Video-of-Thought: Step-by-Step Video Reasoning from Perception to Cognition.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Video-of-Thought: Step-by-Step Video Reasoning from Perception to Cognition

Reference 25

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Observation 237fe246-e200-4e68-aaf0-7fab4d12797f · outbound

This paper cites Vitron: A Unified Pixel-level Vision LLM for Understanding, Generating, Segmenting, Editing.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Vitron: A Unified Pixel-level Vision LLM for Understanding, Generating, Segmenting, Editing

Reference 26

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Observation fb6d6d4e-0c6d-4329-bc25-88955f8ba0c2 · outbound

This paper cites Enhancing video-language representations with structural spatio-temporal alignment.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Enhancing video-language representations with structural spatio-temporal alignment

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation df0cea6e-45ab-46c4-8b2b-f957556efdca · outbound

This paper cites Imagebind: One embedding space to bind them all.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Imagebind: One embedding space to bind them all

Reference 28

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raw_fallback, observed 2026-08-07T05:36:17.117688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation c1842dab-1c97-42e8-bd92-e5701d9ac166 · outbound

This paper cites Large language models respond to influence like humans.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Large language models respond to influence like humans

Reference 29

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raw_fallback, observed 2026-08-07T05:36:17.102771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 81acf36e-e34b-44a2-be82-0777b77a5356 · outbound

This paper cites Onellm: One framework to align all modalities with language.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Onellm: One framework to align all modalities with language

Reference 30

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raw_fallback, observed 2026-08-07T05:36:17.087585Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation d5bb6bb3-9efb-4b11-92e7-c5a62c1a9e69 · outbound

This paper cites Denoising dif- fusion probabilistic models.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Denoising dif- fusion probabilistic models

Reference 31

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Observation c2252e6d-8f3a-4ad4-81d6-87a0f853c88b · outbound

This paper cites A Survey on Evaluation of Multimodal Large Language Models.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models A Survey on Evaluation of Multimodal Large Language Models

Reference 32

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Observation 467d2227-2375-4c1c-98e8-3e3dbcb4cde6 · outbound

This paper cites Visual Hallucinations of Multi-modal Large Language Models.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Visual Hallucinations of Multi-modal Large Language Models

Reference 33

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source=pdf_text observed=2026-08-07T05:36:15.573134Z digest=sha256:3711e1eaefaadeb23952e9ee3a6dbc1463dcc5a2dd5e9b2574a743b7cbc8b04a

Observation 6677854a-7a7f-4690-9f27-78863eb71b10 · outbound

This paper cites GPT-4o System Card.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models GPT-4o System Card

Reference 34

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source=pdf_text observed=2026-08-07T05:36:15.578298Z digest=sha256:8ac855e50865059271d237901962471eaa6ffbe1855627a29d0ef2d0040d7ba4

Observation c84a9f05-7ab1-4223-8e26-233241932b2d · outbound

This paper cites MAP: Multimodal Uncertainty-Aware Vision-Language Pre-training Model.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models MAP: Multimodal Uncertainty-Aware Vision-Language Pre-training Model

Reference 35

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verified exact
local_arxiv, observed 2026-08-07T05:36:16.179278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:36:15.582961Z digest=sha256:0e31fd9148c02298f97fb7e4defcf1e76fd43eede4c476023b775105d8b48b3a

Observation 01ea5bc5-5f9c-4ccd-9054-63993b4d147f · outbound

This paper cites Mimic-cxr, a de- identified publicly available database of chest radiographs with free-text reports.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Mimic-cxr, a de- identified publicly available database of chest radiographs with free-text reports

Reference 36

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:36:15.587156Z digest=sha256:398ddb8dc3d11f8d0e3923950a00483952db475c2903115cab1939da2350fe20

Observation bcf371ae-1231-4d40-aa0c-495b7b9177e1 · outbound

This paper cites Exploring the Frontiers of LLMs in Psychological Applications: A Comprehensive Review.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Exploring the Frontiers of LLMs in Psychological Applications: A Comprehensive Review

Reference 37

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no resolver link, observed 2026-08-07T05:36:15.591683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:36:15.591683Z digest=sha256:884a15fd9f9d88fe9188df3ff6fd834f8b6331e6b062c44dc4e8552512822a84

Observation 75ec342a-cbb9-4f81-b4e8-667fd903db5d · outbound

This paper cites Audiocaps: Generating captions for audios in the wild.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Audiocaps: Generating captions for audios in the wild

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:36:17.054522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:36:15.596504Z digest=sha256:8bf9995cd2767298ed19ea46db86dd8f7b721eb4b9c35c18126cd0517051ab47

Observation 4e14ef2e-2a4b-44a6-abc1-7ad47759d318 · outbound

This paper cites AudioGen: Textually Guided Audio Generation.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models AudioGen: Textually Guided Audio Generation

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T05:36:15.600823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:36:15.600823Z digest=sha256:4e67dcb1a63f1e6076b134aada6f57fb8a8ee82ddc3f3e7837ebc86e784ee652

Observation 5fe5e464-8070-4b80-bcc6-c7ed9502e635 · outbound

This paper cites RGB2Point: 3D Point Cloud Generation from Single RGB Images.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models RGB2Point: 3D Point Cloud Generation from Single RGB Images

Reference 40

Resolution
verified exact
local_arxiv, observed 2026-08-07T05:36:16.132027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:36:15.605520Z digest=sha256:274a079c439e1b55ddb968cf01556157b3a5a99ded5297879e7954ff1d8b13f2

Observation 8d212d59-c7e4-41a7-8a5a-fbfbdaee565d · outbound

This paper cites UNIMO-G: Unified Image Generation through Multimodal Conditional Diffusion.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models UNIMO-G: Unified Image Generation through Multimodal Conditional Diffusion

Reference 41

Resolution
verified exact
local_arxiv, observed 2026-08-07T05:36:16.113155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:36:15.609922Z digest=sha256:f4d4415619858814350bce5e40ab9d785879ab658bbc95629b9cc9f76e7a2499

Observation d1f731e9-3188-434b-9555-0abe0b85a997 · outbound

This paper cites Evaluating Object Hallucination in Large Vision-Language Models.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Evaluating Object Hallucination in Large Vision-Language Models

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T05:36:15.614324Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:36:15.614324Z digest=sha256:4b60ed195921dcb0eaf57076df60029738bad681b404952ff42e0857aab1cae2

Observation ec0414f0-53ca-4d81-9263-dc1580cfc322 · outbound

This paper cites Video-LLaVA: Learning United Visual Representation by Alignment Before Projection.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Video-LLaVA: Learning United Visual Representation by Alignment Before Projection

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T05:36:15.619085Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:36:15.619085Z digest=sha256:088e763b41b4a0bbff50b3b252951a9b944e6e1cc3af77f0812ad9992aea665e

Observation bf64d6b2-be98-4356-a98e-0283d0c71af2 · outbound

This paper cites Clotho-aqa: A crowd- sourced dataset for audio question answering.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Clotho-aqa: A crowd- sourced dataset for audio question answering

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:36:17.040842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:36:15.623493Z digest=sha256:f1bae67021d347ab990ba2164ced55204dc53328c2cf09873081bff589dd1be1

Observation 8b24cdc6-a01c-4e9a-8db5-3475d99d59cc · outbound

This paper cites Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-07T05:36:15.627411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:36:15.627411Z digest=sha256:336c364d1cd63c5b112397892b87d8bdc74236da3c28dc4731fd6a8e67e15583

Observation 2dd78eba-5d68-4e87-ae0e-31bd69f75c75 · outbound

This paper cites Visual instruction tuning.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Visual instruction tuning

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:36:17.027803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:36:15.632144Z digest=sha256:a13cf07ed3a85eac70da919867ce424631261a85c1911c48234642f54fc24b14

Observation ae0d8297-91b7-4cc9-9557-3208a3e74c0d · outbound

This paper cites VideoFusion: Decomposed Diffusion Models for High-Quality Video Generation.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models VideoFusion: Decomposed Diffusion Models for High-Quality Video Generation

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-07T05:36:15.636162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:36:15.636162Z digest=sha256:fa2e9239102e0d4cc5aa51ad0d2813b43a49cb0b8ec7d295a1d98ab9b8394dd9

Observation cac0082e-be49-4cd1-b3af-e2c5b8aaacd0 · outbound

This paper cites Unibind: Llm-augmented unified and balanced representa- tion space to bind them all.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Unibind: Llm-augmented unified and balanced representa- tion space to bind them all

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:36:17.014887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:36:15.640261Z digest=sha256:47483aafb8238c5d2107131b856cb2933292e511c879019645325377beeb9ca3

Observation daefd627-3d13-41eb-a34c-88f115b96a00 · outbound

This paper cites Openeqa: Embodied question answering in the era of foun- dation models.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Openeqa: Embodied question answering in the era of foun- dation models

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:36:17.000738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:36:15.644736Z digest=sha256:f91b251da051c0724bed80363a1d371dc0030b92010354db344e110e409c0684

Observation 8a27a624-c870-4bdd-bafd-a7999d2625b2 · outbound

This paper cites Point-E: A System for Generating 3D Point Clouds from Complex Prompts.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Point-E: A System for Generating 3D Point Clouds from Complex Prompts

Reference 50

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no resolver link, observed 2026-08-07T05:36:15.648822Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:36:15.648822Z digest=sha256:abc6d5f8bbd8cbcb432ea55659aa4175198d87ab67b3185cd19b2c92342d35c4

Observation af333303-2975-4ef3-846b-bf441ccd6fd3 · outbound

This paper cites Human uncertainty makes clas- sification more robust.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Human uncertainty makes clas- sification more robust

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:36:16.986280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:36:15.653333Z digest=sha256:3b1ba4e70258ae1274bcd5f0e8db2525feebcd427d3670ac5990a34818e6ad36

Observation 54ad4906-8783-4811-9f0b-c3012997d958 · outbound

This paper cites MLLM-Protector: Ensuring MLLM's Safety without Hurting Performance.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models MLLM-Protector: Ensuring MLLM's Safety without Hurting Performance

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-07T05:36:15.657440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:36:15.657440Z digest=sha256:90eef783968f57f237ebbefbfd816c12481b20112eaa9f94fe4062ec8b50b362

Observation 7e38aa81-7496-4998-b151-13add24a20ee · outbound

This paper cites Flickr30k entities: Collecting region-to-phrase corre- spondences for richer image-to-sentence models.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Flickr30k entities: Collecting region-to-phrase corre- spondences for richer image-to-sentence models

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:36:16.972679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:36:15.661704Z digest=sha256:5470dff415dbe858e6799fba643b8ac8ac74f7bb16ecf6fed1cc5eaa64701af6

Observation 0440a7a7-ffff-4e94-8d09-61ab9705dc2c · outbound

This paper cites Robust speech recognition via large-scale weak supervision.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Robust speech recognition via large-scale weak supervision

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:36:16.958347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:36:15.665572Z digest=sha256:3f59412414757b6a5116f01e3c5ad9b3c86f258a0443c9e5d8686f430d68fe59

Observation 07b9fbbe-98d3-49d7-ba6f-307a9daff762 · outbound

This paper cites Object Hallucination in Image Captioning.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Object Hallucination in Image Captioning

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-07T05:36:15.669523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:36:15.669523Z digest=sha256:7eb9d58d2cd77be3363fe737557604a2cdd0fab47655afa3eb1799fefac2d42b

Observation faefea57-4f5e-4ad6-9d7d-de744989a0d0 · outbound

This paper cites High-resolution image syn- thesis with latent diffusion models.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models High-resolution image syn- thesis with latent diffusion models

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:36:16.944222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:36:15.673597Z digest=sha256:e67dbebb13f42073e86687b2fd10c3eff09b0594cd9e7f6620315af629c1f063

Observation eca5bd21-10f8-4cc3-91c8-1e66359ac523 · outbound

This paper cites A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directions.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directions

Reference 57

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no resolver link, observed 2026-08-07T05:36:15.677482Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:36:15.677482Z digest=sha256:6ed341a577636bbc718f644365cd7821f25ddabe23ea4e6d488547802bf45dac

Observation 5a5ddccc-f0da-48e1-ab39-cea1af7510ee · outbound

This paper cites Moma: Multimodal llm adapter for fast personalized image generation.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Moma: Multimodal llm adapter for fast personalized image generation

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:36:16.927402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:36:15.682096Z digest=sha256:bd9c551dbafd13aaa0bb699e9ada2ccffea293e8ddbf8c6eb4e67cdeb1bf548f

Observation 6bbc8983-0700-42fc-adbe-2898be57e7a3 · outbound

This paper cites Pix3d: Dataset and methods for single-image 3d shape modeling.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Pix3d: Dataset and methods for single-image 3d shape modeling

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:36:16.913292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:36:15.686084Z digest=sha256:00f922c6a3bb08dabfda26da8f7863eb17d24b755007a873dbfdfe625e610295

Observation dd0d44dc-603d-40b7-8a28-579308a563b1 · outbound

This paper cites Any-to-any generation via composable diffu- sion.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Any-to-any generation via composable diffu- sion

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:36:16.898734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:36:15.690326Z digest=sha256:850d8ffda0db28c802d3cdd1ea41c358efdd3136d08d55566098c99a6c94caed

Observation 49d04c41-9cc9-4a29-9a9a-9659e12366b7 · outbound

This paper cites Codi-2: In-context in- terleaved and interactive any-to-any generation.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Codi-2: In-context in- terleaved and interactive any-to-any generation

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:36:16.883874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:36:15.694155Z digest=sha256:9be172c4c69955655a6d2035ba91779ce11d9d6f3a0aac9de67b2dcc0579c6bd

Observation 476d3ee4-1bd3-480e-8dfe-036b1e821b17 · outbound

This paper cites Evaluating the Evaluation of Diversity in Natural Language Generation.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Evaluating the Evaluation of Diversity in Natural Language Generation

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-07T05:36:15.698346Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:36:15.698346Z digest=sha256:6dca157406f1c4702d14b2764a9346bf018857a51bdd1f5eaf673042eed0890e

Observation 8e9d0d8f-51dc-419f-a014-a59245f18cdf · outbound

This paper cites Evaluation and Analysis of Hallucination in Large Vision-Language Models.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Evaluation and Analysis of Hallucination in Large Vision-Language Models

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-07T05:36:15.702798Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:36:15.702798Z digest=sha256:bdafca29682a9045075709a3c77e62ff456aa4b323c65b504a871a5eae79295c

Observation ae3f04ff-f2a2-460f-8022-02163d43b24e · outbound

This paper cites Uncertainty Aware Learning for Language Model Alignment.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Uncertainty Aware Learning for Language Model Alignment

Reference 64

Resolution
verified exact
local_arxiv, observed 2026-08-07T05:36:15.955675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:36:15.707773Z digest=sha256:00cb1c369a4bd15e848348a8e89a6fddd4c4632b5aabd16969d4f8fba95d6d70

Observation 8e788e5a-7fc5-4718-a811-dd04f9b82aea · outbound

This paper cites Multimodal large language models: A sur- vey.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Multimodal large language models: A sur- vey

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:36:16.870372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:36:15.712088Z digest=sha256:c357a66c8d971873ae4cfce5fa9b8fb809d8832a6588b062aa3cc8d2fd2f9beb

Observation 7aaf53df-d37c-4d31-b5c1-7996665ae2f2 · outbound

This paper cites Visual Prompting in Multimodal Large Language Models: A Survey.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Visual Prompting in Multimodal Large Language Models: A Survey

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-07T05:36:15.716207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:36:15.716207Z digest=sha256:717376ac710640a57cd1fcf53b7a0509fcc627d72c349d0ca34ce1e3b884567c

Observation 12192345-6dc4-4ee5-8aa6-b83f32a2c336 · outbound

This paper cites Next-gpt: Any-to-any multimodal llm.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Next-gpt: Any-to-any multimodal llm

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-07T05:36:15.720986Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:36:15.720986Z digest=sha256:995824e70a24c20d7417eac42e9d2ca28ff5e81afa6660f3dba0fa3370d13c08

Observation 3020b22e-730f-449a-a1b0-7c92dec595ea · outbound

This paper cites Self-correcting llm-controlled diffusion models.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Self-correcting llm-controlled diffusion models

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:36:16.847851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:36:15.724944Z digest=sha256:9d4ca627dfbeb6aa02bd28965ec69cb52bbd10beb3186d20cef4ec96c07bde2f

Observation 1d991fb0-35ef-43ac-8b4d-0d762251ead3 · outbound

This paper cites Can graph learning improve planning in llm-based agents? In The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Can graph learning improve planning in llm-based agents? In The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:36:16.834135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:36:15.728850Z digest=sha256:3618107687e1dd1df4940f69347a02f8c0aa56c572cc140f0523ee5d060a5b1b

Observation 2548339c-b73b-4fa1-af65-6be55726c9a3 · outbound

This paper cites 3d shapenets: A deep representation for volumetric shapes.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models 3d shapenets: A deep representation for volumetric shapes

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:36:16.819142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:36:15.732697Z digest=sha256:c02dbfbf7872a803daf73fd94ee9e6e8a37ace816826f8c815807dbf0fe80797

Observation 2ae6169d-5f76-4e1c-8488-ab0d4516dd1c · outbound

This paper cites Next-qa: Next phase of question-answering to explaining temporal actions.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Next-qa: Next phase of question-answering to explaining temporal actions

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-07T05:36:15.737268Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:36:15.737268Z digest=sha256:3fa29cfe0a92df3f416dbea9440dbafe092c461bc4eedb45b6c6e96fc33ed739

Observation 68d2ece3-1225-4022-bb25-888c3f0296f0 · outbound

This paper cites Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs

Reference 72

Resolution
unresolved
no resolver link, observed 2026-08-07T05:36:15.741481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:36:15.741481Z digest=sha256:e57591582c2b9e828a195d212df83704ebe28f0199d657c6541df96cba0a6bcd

Observation d77d7aba-9da5-4367-b1f5-502704668300 · outbound

This paper cites Video question answer- ing via gradually refined attention over appearance and mo- tion.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Video question answer- ing via gradually refined attention over appearance and mo- tion

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:36:16.797287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:36:15.745559Z digest=sha256:b712bbeaaf6eaa43de47eb4c1a8f660e47ce8971e21b0062560fa142d6227191

Observation 17999f8c-8899-4ab5-b676-2c98cabc63c4 · outbound

This paper cites Msr-vtt: A large video description dataset for bridging video and language.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Msr-vtt: A large video description dataset for bridging video and language

Reference 74

Resolution
unresolved
no resolver link, observed 2026-08-07T05:36:15.749730Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:36:15.749730Z digest=sha256:ac98c4bb9d08528b4c5a512f427aae9f712fa12bb6b79facb3b57c6ea80a96a1

Observation 7af7cedc-e546-45e1-930f-9a1318550ad7 · outbound

This paper cites Pointllm: Empowering large lan- guage models to understand point clouds.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Pointllm: Empowering large lan- guage models to understand point clouds

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:36:16.774727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:36:15.753669Z digest=sha256:6a10e06540e3372150942ffc9a7ff3cd16233204de3d0a86849a716273200d96

Observation 094700cd-9f89-41d9-a81a-2f388c89175c · outbound

This paper cites Cstr vctk corpus: English multi-speaker corpus for cstr voice cloning toolkit (version 0.92).

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Cstr vctk corpus: English multi-speaker corpus for cstr voice cloning toolkit (version 0.92)

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:36:16.760808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:36:15.757713Z digest=sha256:4925e44caaf6e7d7a98fcd651f0cef7de8c4dc76452b729fc0c0da16f11a31db

Observation a5cad0f1-76b9-4ebd-a0dd-7ac05c6960c3 · outbound

This paper cites MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities

Reference 77

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unresolved
no resolver link, observed 2026-08-07T05:36:15.761382Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:36:15.761382Z digest=sha256:2f432a831a63deb231038c99694130514a9f86194f627acda437fe39cf1643d7

Observation acd1e886-8c71-4176-9c05-ff8507bccb95 · outbound

This paper cites AnyGPT: Unified Multimodal LLM with Discrete Sequence Modeling.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models AnyGPT: Unified Multimodal LLM with Discrete Sequence Modeling

Reference 78

Resolution
unresolved
no resolver link, observed 2026-08-07T05:36:15.766361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:36:15.766361Z digest=sha256:e2b003a45c3f401129dce2dfe87fd18331f2f7114f633aab5e1789d5158a2f6a

Observation 45cee82c-6fd7-4084-85f8-f5d2d5618ef3 · outbound

This paper cites Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding

Reference 79

Resolution
unresolved
no resolver link, observed 2026-08-07T05:36:15.771552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:36:15.771552Z digest=sha256:85aafd55b845c387af20ac30ea857fca4af38daaf98872bb144e96cf6805be48

Observation 7611bbc7-6cac-430a-b7d1-240cca9eed78 · outbound

This paper cites Approaching outside: scaling unsupervised 3d object detec- tion from 2d scene.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Approaching outside: scaling unsupervised 3d object detec- tion from 2d scene

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:36:16.747296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:36:15.775728Z digest=sha256:0f3ad71a95467b38f32703d8b6e7f03639f9bc586c857dfc3e510fff7e9bf81b

Observation 50519c5e-2aab-46ab-9f8b-fea6a440e93e · outbound

This paper cites Harnessing Uncertainty-aware Bounding Boxes for Unsupervised 3D Object Detection.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Harnessing Uncertainty-aware Bounding Boxes for Unsupervised 3D Object Detection

Reference 81

Resolution
unresolved
no resolver link, observed 2026-08-07T05:36:15.779306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:36:15.779306Z digest=sha256:d1ec610e690038e3b28623ff5b796e2d1bb7cde0cc6093817a0ebb30d4f731a6

Observation a5cf42fd-d216-42ae-a7d1-3d8de849d069 · outbound

This paper cites VL-Uncertainty: Detecting Hallucination in Large Vision-Language Model via Uncertainty Estimation.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models VL-Uncertainty: Detecting Hallucination in Large Vision-Language Model via Uncertainty Estimation

Reference 82

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no resolver link, observed 2026-08-07T05:36:15.783537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:36:15.783537Z digest=sha256:72ab2dfdc87afc130f336e8205c1533fb1a171e528db5a8e005f308d59c614d5

Observation 51bd2dbd-eea2-411e-b2b7-7b3920ad1b1b · outbound

This paper cites Prompt highlighter: Interactive control for multi- modal llms.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Prompt highlighter: Interactive control for multi- modal llms

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:36:16.732868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:36:15.788459Z digest=sha256:db35eda5609fdc4ea56de5b6f0206c2ddfa155537acc972641b848a690586074

Observation bc126e85-5740-401c-b7a4-a282d1e3069e · outbound

This paper cites As a result, any fluctuation in answers of LMM directly reflects its uncertainty.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models As a result, any fluctuation in answers of LMM directly reflects its uncertainty

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:36:16.719241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:36:15.792698Z digest=sha256:6a61febe0aa316eeeb998e9534b1c52240f29040d7aaa1be0577bb77536685a0

Observation 59e14804-32b7-419f-aa1b-2e1e6a5dc455 · outbound

This paper cites We conduct experiments with 18 benchmarks.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models We conduct experiments with 18 benchmarks

Reference 85

Resolution
malformed identifier
raw_fallback, observed 2026-08-07T05:36:16.703460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:36:15.797322Z digest=sha256:3b9508d1a7a389978ae3dcc4675f9e9736942175a5491a914b2fcb7784fc54ad

Observation 2c3f1bf3-685f-42ab-8bcc-49e730a33205 · outbound

This paper cites We report the ablation of text clustering methods (see Tab.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models We report the ablation of text clustering methods (see Tab

Reference 86

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:36:16.687117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:36:15.801877Z digest=sha256:cbed041297d1c3f7969d2e5a29545f0e6a32c033a8939e31be97ed1ae62c4431

Observation a29543ef-6ce6-4957-a66d-3b7cd3d2b15a · outbound

This paper cites Definitions and Assumptions.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Definitions and Assumptions

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:36:16.671652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:36:15.805895Z digest=sha256:da70362ccf4dbbc747b197977c3333f399316df92a9dd7611751507c8460cfab

Observation 7c2f0cd5-22ec-45d7-8c1e-9acca061a8f3 · outbound

This paper cites For those input prompts, the predictions from the large model is yi = M (xi), and yj = M (xj), respectively.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models For those input prompts, the predictions from the large model is yi = M (xi), and yj = M (xj), respectively

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:36:16.657634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:36:15.811029Z digest=sha256:47ab0ec22dc429613580f66e8692075da75f1a44f98c371bf56ad3f8698242fd

Observation f4f9f391-c9db-42c5-93a9-ecf227b8ab9e · outbound

This paper cites Assume the large model parameters θ are random variables with a prior distribution P (θ).

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Assume the large model parameters θ are random variables with a prior distribution P (θ)

Reference 89

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T05:36:16.643193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:36:15.815113Z digest=sha256:3be0fa4d5a16415ab6a7c5019477adab323189e7b1111031c6de0d9c2d36fc86

Observation b780146d-e00e-45f0-8537-459bcb0c434f · outbound

This paper cites an unresolved cited work.

Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models Unresolved cited work

Reference 90

Resolution
unresolved
raw_fallback, observed 2026-08-07T05:36:16.629270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T05:36:15.819379Z digest=sha256:10b1bc12f8d9fd2d9207539fd2762e193402dd78412ca708e9cd8f779097714c

Pith citing papers

Observation 3e5cf70d-aa8e-41f0-8b38-dbe3e1ebd562 · inbound

A Systematic Evaluation of Black-Box Uncertainty Estimation Methods for Large Language Models cites this paper.

A Systematic Evaluation of Black-Box Uncertainty Estimation Methods for Large Language Models Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-07-04T03:39:30.610855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-26T17:46:00.822375Z digest=sha256:35199bb8161ac19463db163ddadc37b5fe9415adc9feaa1888ccd14995225574