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Paper Citation Record · LEDGER

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

As of 18 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 2026-08-18T06:34:40.430872+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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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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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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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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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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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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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=sha256:0aa9f6e87e2179ad2c3089874ba5ca4eced27ca77e37845751bbb6bce4622f47

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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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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source=pdf_text observed=2026-08-07T05:36:15.503666Z digest=sha256:b5aba36dfb9a222b02281a9ab8c3c406593a8f3e8e778b7b62be954cf7c98a7a

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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+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

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+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 2026-08-18T06:34:40.430872+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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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:c26a7405a688b6f76b6155876e575208f2d120c47651d343745a0136f9336d83

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T05:36:15.582961Z digest=sha256:2e0f0db86fc705f4c36dc0f29b12e78015b7cd213f73106a267467f2ac8c8d55

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=sha256:74b0de47713b66c9b36fc11b77853cb5ff533b5ecee91d65b6b432d0bcf89af0

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:36:15.591683Z digest=sha256:64487bbef78d74fab3724429a21c47237af75a48cea5a5981acc532483444b54

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T05:36:15.596504Z digest=sha256:91f8c1d7953c2e9c1165a96393b2e42f05dddde3f8a46a0581ba1d113f6eeb11

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=sha256:49c4037f785c1916d6ed9e1f2e2533bcf6f08f2a8682369b4970f9dab0bdd325

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T05:36:15.605520Z digest=sha256:b0ef263e98be3a5335750735e9db2f661428960dc1868e58e43c0fb749167992

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T05:36:15.609922Z digest=sha256:1dfab80e3b6c22eacc1e6587c41a25a52a3dd18999ac5bdf11de5b1a7433acb2

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=sha256:2b01dd410e9efe71eec3b8c5267562b8a5fd68d089894a37569442a5b8bb6a82

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:cc8726743fbb53389452b1a4df7fffee277fdcc00156fe91ec1a3db74a9a488d

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T05:36:15.623493Z digest=sha256:b37c43b046445e447c01158e1f2d8b2e8719d026acb0d73d7f1693d768619c71

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=sha256:0c8eb49f456553d7c7ac79fdc7121dcd59b6589da7ce6df8f9bd37acfc30abcd

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T05:36:15.632144Z digest=sha256:1c82456fa27f4c68bd56d5fac98675a186b02190e88556217fa3b93617a9e14b

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:b2eca5cef66898dbb52e570452b30bcc72d670f03d9647413b5b215b2c00ffec

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T05:36:15.640261Z digest=sha256:a9e2024da754899a7c1c559d11ff0b9e7b8bc412b41c7e612d0f7b0927257ad3

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T05:36:15.644736Z digest=sha256:4d5ea788ec5551814fc41308d1738c910880b397392969cc171cdcabf51c7e49

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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unresolved
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=sha256:3591997cbee820ec2035c4467844949f4fe8ab6f0f75fd04f3399cb674e340a9

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T05:36:15.653333Z digest=sha256:71d4fc59ccda9050bbdf72ede0fa2aea7271ece718f9694bb71a427c8d036589

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=sha256:60ed17b835a0ddba842b89a637124a747771b1a486f3caf211e783a97f5a11de

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T05:36:15.661704Z digest=sha256:d22f1bfa87948d995e64cc0863c13b68606cf6e23bd0bbd6cb1869b089e2ea03

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T05:36:15.665572Z digest=sha256:de75da7890a68f1a002bd43bee106dcab15147d2fea414f05960481818b73a2e

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:ab654b799779bb6013315e3d718d8fe6cc85c446ba3220291c39ce5d442d2ee9

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T05:36:15.673597Z digest=sha256:8cd34f6f6e4ebb91766c6c5216f5eff5d6587b5421ace64132eb8f9cba9595c1

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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unresolved
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=sha256:21eabe8a950a27e5b740d2b94ce56d514904d4bd18daa7f132c09aa992663b6a

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T05:36:15.682096Z digest=sha256:4b06056de81853c488187c91544276793f9b590270a07d4c364124cb1a347e7c

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T05:36:15.686084Z digest=sha256:40a542ad53ad8b4472a1c15c64d60f0a6a94c05a6d9a16b08b7e2c29a909973c

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T05:36:15.690326Z digest=sha256:5801cfba891a553c1249892f40b38370433176d01726643a6ebd22005201d352

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T05:36:15.694155Z digest=sha256:40e495f306763bd8da46cb1a77b94852e91c2445efb3eac977918bf24a9ff428

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=sha256:8a4f2e3d6c7c8de397f608ad4d363d28867c9a70fbab1cc88e19c06c1d7ca898

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=sha256:37702e092cb8c28898222c658a5333d4e4a9c74d5e25bed2f19b310085949ff5

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T05:36:15.707773Z digest=sha256:6a8161c01fc11ff4ec630e48a777242ae59dd65acae06408b5f77e3d3341d9ef

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T05:36:15.712088Z digest=sha256:d2e66e5c137180d879b3b3738d03ed8d6cf6f4c0a1a8e38501844799705549b4

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=sha256:56e3f0da32c326edf81fad4d974524a08d2247bbb88679c585467f25d8572202

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:e292318e07b26bbbd7e750e1cd0054b1e97685266aa3c39db330c26d482dc5e6

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T05:36:15.724944Z digest=sha256:65c718c8e29c509d093ecd5e558dc3c8fc186b6914464aa688fe7e8e01be646d

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T05:36:15.728850Z digest=sha256:9615c0247df45bd383380d3a76959495e3ff6c88f08351c8c7e81bbf495f6c66

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T05:36:15.732697Z digest=sha256:96da13033a6df6855b11421630687924618a489be80a7421772449f85edeb9db

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=sha256:62540384a00b2e01a917ce36a715d85bea90bc020f5280a1308fd7a04d28cfb8

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:a4bf054dde157a0fb4130342e90430430ca35b39fd17870e763829fd0950dadd

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T05:36:15.745559Z digest=sha256:2299e5665e939015f8a6f8f33389a98fac5f4253d5cd5e7cfa67b0c51aa85e22

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:aedc61da2ebb69ad7dcc452aaed599f6b5df49963bc1bf963520f4c1b59684d1

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T05:36:15.753669Z digest=sha256:16480c98e44471278549ee094a96acae7c4ce1e8dc252bccd266ff1033c5cf46

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T05:36:15.757713Z digest=sha256:e6638c1ac4a88f42f6e3af032af6f6fa133ae6c5d938cc83c6c3c23ec678483f

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=sha256:219b716a9198b2345924e9629223fcbdf377982d7b4558cf0871c52104bcf67a

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=sha256:4bf6c7b99c5cd28c91d0df8fbd0de16b04522fa1fa41b9f3d1573ffdec67367e

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:b98633c5ae3f0724be22a02f9e521fcbc329fce60a93a78942e9667296f63eca

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T05:36:15.775728Z digest=sha256:bfe79aa938c99ade66fc9004d5d4d43124374b5525ed147af8ae3e9385e674db

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=sha256:6e073893195c9967b61dfa19e60dffdc039bb09127fb9ffa1e9daac408b74ec5

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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unresolved
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:a17efbab85d704d9ead4fc6a67450dbe504197a6c55479a556f5f135778143e1

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T05:36:15.788459Z digest=sha256:8d15f0e044bd254019dffb7d1e89c0b98d3ced35a0ce75ef8ab051fe1d356ee3

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T05:36:15.792698Z digest=sha256:70962d2f1c39f02fa0f382f4455f5f29148116c64de681ebe7d610229616afdf

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T05:36:15.797322Z digest=sha256:45d23bc709d1a84986a88c64dfee626ac1b4e10858ec680960324fd29388ca5c

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T05:36:15.801877Z digest=sha256:e41de9f9e8b75b5812faa972f941e9ae3f0a7aa2dd418fd79d2123d178de5e4b

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T05:36:15.805895Z digest=sha256:ae20b40d38c36335bdfd3a91d00952ae5f179890137a11bf51d2ca2f5dde2a10

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T05:36:15.811029Z digest=sha256:4fe29a8be831ac009376c21a815b15035322a39ad9f4b025ffbcb221c6e29a8a

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T05:36:15.815113Z digest=sha256:5d3f1bd2cf0dd3fbd9d2025e248e6f7f3f5cf4e297944a3f4855183190499f36

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T05:36:15.819379Z digest=sha256:7479b906bcc3a635f34511857ae43a4d1a59469e360a687c598667d765962802

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-26T17:46:00.822375Z digest=sha256:dea683f3769a300028553ab073a8601e4ed116ccab28ea552863e30d3100d3da