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Paper Citation Record · LEDGER

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

As of 10 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 2026-08-10T06:31:04.303077+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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source=pdf_text observed=2026-08-07T05:36:15.461202Z digest=sha256:7e87a9e5b2d0d84e6b7814d400fa9f13a7b2efbbf65f0494bbe509b742dc544b

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:cc30a0b8a6d09537e37017e7b886c74dbec6019783c59c15e82494c27e48f8ca

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=sha256:795d51d910fe58f70b21f3fa3ee4bff87a76816d7a42a52fcc98f61910488e40

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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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 2026-08-10T06:31:04.303077+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 2026-08-10T06:31:04.303077+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 2026-08-10T06:31:04.303077+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 2026-08-10T06:31:04.303077+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 2026-08-10T06:31:04.303077+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 2026-08-10T06:31:04.303077+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:ea2cfaff3a17ae4f6ecf0cd3e3a10fbd97854fd9bb558de619d5d7d1416b86fe

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:36:15.582961Z digest=sha256:baaf56e843e80f20a04e7c3a7cc0c9e810d4545bfe0d2fbbf6ca5239f0c9baa0

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:e81f17c6a19c5fed04f1f37e317a25664abad34c108b41b70c92d025e39f38a9

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

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source=pdf_text observed=2026-08-07T05:36:15.591683Z digest=sha256:02e84bf3f8497d60033d402a3d02f69362f21583325db982a1e42835ddae0922

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:36:15.596504Z digest=sha256:d934f7f15c97e8b84fc84bb2c1302f76db86211df7e85158fa395d53a2666a43

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=sha256:1a9a471289d6639be8e9687223ba946d0047b8504edbd6c6a7d2ca2902938c7e

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:36:15.605520Z digest=sha256:a8d1b732d61a588925a452a149dd6459a6d61cb8feeac79fd70ef30fc6a992a2

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:36:15.609922Z digest=sha256:e3df2c1d24571cd8cc020d1d6071f29f6f4526e28b73df82d9637653ca151e54

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=sha256:179f7e645b38458f06d0a760b1d63c47b9ed1394f400778232b4f55382d09902

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=sha256:31083705ed20610b833218b37f07a9583db57cc07f215bde52e8fc6058b8779b

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:36:15.623493Z digest=sha256:8e9df3a992637abecc55a12625310658f5f591535e25d67eab2d6266055b2c35

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=sha256:5c09a81521d5b73b2764949334bc160a8ee6a77728e5c0dc4e8139cc2b3e8db5

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:36:15.632144Z digest=sha256:d27e300d1d3f7c49e5d4262eeb409cf3f7b1e46c0466fd105902c42bb30ef8f8

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=sha256:83eec72d403c1822e02e83a8948fbc9a0b92adb72cf2d61d020f95c9b9b47675

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:36:15.640261Z digest=sha256:df1d9f3eb9390965d14a4b08194bb61013fefe33748891456ae79f037e17e38f

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:36:15.644736Z digest=sha256:9fc04db3396be1d320d925401de3a0a24ba3e43c106a651cf95cb9edac6e28f9

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

Resolution
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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=sha256:283810c6d8c9c8f7815dccb4bb19b8aeb97fbd4a0c10bd31c12dc24c619d3d1a

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:36:15.653333Z digest=sha256:cfb29381c348b6ea649f076968fa1dc2ff330661736439edf0084db0297d71db

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=sha256:8ce923d6431a02375bb7aa67412236bc68d985c90157290c3a8be8d0c7b12556

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:36:15.661704Z digest=sha256:3c7fb986f0460dc46884edc87d3650d5ced536c2b8afd449d10f4131530ef616

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:36:15.665572Z digest=sha256:9294030da60044b7f008a8d4bd2450b50ac7032c4b0e1ac524c4cc1f1bf87a3b

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=sha256:0df71911b616ff8e02131db64797db0fbadba92bd2002f7b1877184a6f6efde9

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:36:15.673597Z digest=sha256:698c42a182208c182b7bde25075c4191305d53df003e532e36ca9398716481b0

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:c69db38b65d833b333fd10c6832b719f1242bf18bedc08bf4f50d2997e50696b

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:36:15.682096Z digest=sha256:84279d0d713996166f972f1491fbb5ceb8ee9e09d117bb07ecfc9ef70968d5fb

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:36:15.686084Z digest=sha256:7646f9aefd834ad0b6d48c57e5857c29cbc840084bd23eb9cc5e02c48bf75cc4

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:36:15.690326Z digest=sha256:332db25ae1c87dfe6fc2cf53a00decc0c9941c55914cd22bda63a50016fb8d53

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:36:15.694155Z digest=sha256:f987ca5a60f619beefc39b3ed5d20b22785cb9f622e34fc31a9762fa91562f83

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:a7e9b92c60092a63e6138814dca3a1906c95167b41e31f4ff769ebeec2b93e10

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:dc4e1ef07c0833028c82725dc1b79a19445596ce1ab2b239132866cf32b4a052

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:36:15.707773Z digest=sha256:bc594181ed346e23db641eb3ca9d32db65fd22cbeffce10ff02fc45ed5090f34

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:36:15.712088Z digest=sha256:c184feda26ff4d3296305fcdf25828d5f46648db55308cb61d013f32903b3123

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=sha256:285e9ecfa5e64e179be1eec49ddb4c2bb58a71546f0530fdf689ec6e3a487ba1

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:ee640901dbb597cdd2184f3b9ffd822fbb8b72ee4a8a16ddedf961eccf96eab9

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:36:15.724944Z digest=sha256:7c4b1beb7d54ad6a0bdf10f4cb1b22b8da1f2ce6b1b7b91e663577bec4d6d9ae

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:36:15.728850Z digest=sha256:420d790f4a15626fd07f5fcd0561e12c99f9314292739ca6e7d0ce70c57af663

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:36:15.732697Z digest=sha256:3067852bdf7b5901c4261cb8ee5ee0456411168e5b9ac181c4ce0e1be667fff4

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:abbc3a446b419d2f4d54d26c39a03966b9830f64751e76fe76765c882766f3bf

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
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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=sha256:0cc65d7a31390f1c2776cb9b7b1ec06d2c3749798f9a755079e87538b20cdfe2

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:36:15.745559Z digest=sha256:15c04f9d6f941a4d3f96eca5dc88b8c424e6212a2a1c6a3ec20eb744f4eb0485

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=sha256:70268d3e2e593946d9c0a1ca8dbf422b6d0a01ae58b11fabb3856d6fb8c1d218

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:36:15.753669Z digest=sha256:1a335419dc31772f377e1e27ef575649f288da2febf6492155f7ff9af98fe361

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:36:15.757713Z digest=sha256:1df3e3577b24c0ad1bd6e6cd609b0af323c99017294595ad0605f89bca7c4129

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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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=sha256:35e273f58ab3f2bf910d2ae44f23a98b7c490b4d36e0e2a5fb70b43f3d57632f

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:dff742f33e436a6d9a8783a7fc012b67c3b2002eb42ff438575d46d311af2f13

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

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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:a0f60ddfb4128030d5684a450e3462b5b55f00c368e4477b13675eb847b8b32b

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:36:15.775728Z digest=sha256:6942c66c895f26812cffb4c026f40039035db5a71a0f0d06a590408d51f89b59

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

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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:cfb6e9d323c10d7e3e134be81f48d68ed0f11b7102356321601f536c04cc13a7

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:cd5f7a249df2a3d84f8a9c84ae32f473e35f80a778c889d76af0312bc0bc0559

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

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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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:36:15.788459Z digest=sha256:111deea8acf5e0eed7aaaad2898208d8e0cea48d9e93af1ce318ed9b8be1a3d4

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:36:15.792698Z digest=sha256:eff0097e8d06111416744d7b39e2aa09a13b938428f185322afe91f0b35570fb

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:36:15.797322Z digest=sha256:3ab98a2af4a256a9c82191833c7c698c7a23d72f82591b85bcd9e16c2e39ad1f

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:36:15.801877Z digest=sha256:b978286828eb07fe3ba8583ac7098227b307e219b68c64fbf30154f57c2d99f9

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:36:15.805895Z digest=sha256:1e709197127d44e8d3f16df0952a4f92559ac4ebdd7979b1481068084de174e4

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:36:15.811029Z digest=sha256:a531ad54545adb3f9356a719d494dbce3fc53c9e50a8defd0ed7d29fd746def3

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:36:15.815113Z digest=sha256:d6265e8f7f4d5187468d213b5276c985dc036014c7d7067c8ab7c6fac9238bff

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

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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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T05:36:15.819379Z digest=sha256:1904ab2232c129698023fa607b294fb3e877422fdec2d3290c03ab638b80a2f1

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-26T17:46:00.822375Z digest=sha256:293011565608c316a105ee8c1cc9fa5da7787c2ebe28acb93ae0168a96698b0d