Paper Citation Record · LEDGER

How Do Vision-Language Models Process Conflicting Information Across Modalities?

As of 13 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 8 inbound Pith citation observations for arXiv:2507.01790.

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

pith.paper-citation-record.v1
2507.01790 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:47:07.903561Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T11:07:46.242486Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T17:15:52.016694Z

Reference resolution

41 of 41 outbound references displayed

verified exact1
verified fuzzy14
unresolved26
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 81f33fad-f608-4169-ab62-9fcec184c70b · outbound

This paper cites Multimodal biomedical ai.

How Do Vision-Language Models Process Conflicting Information Across Modalities? Multimodal biomedical ai

Reference 1

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This paper cites Understanding intermediate layers using linear classifier probes.

How Do Vision-Language Models Process Conflicting Information Across Modalities? Understanding intermediate layers using linear classifier probes

Reference 2

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Observation 8c09864a-642d-4096-b634-7f795a35f720 · outbound

This paper cites Flamingo: a visual language model for few-shot learning.

How Do Vision-Language Models Process Conflicting Information Across Modalities? Flamingo: a visual language model for few-shot learning

Reference 3

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This paper cites Qwen2.5-VL Technical Report.

How Do Vision-Language Models Process Conflicting Information Across Modalities? Qwen2.5-VL Technical Report

Reference 4

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This paper cites Probing classifiers: Promises, shortcomings, and advances.

How Do Vision-Language Models Process Conflicting Information Across Modalities? Probing classifiers: Promises, shortcomings, and advances

Reference 5

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Observation a8ff95b2-42ca-4a9b-a95a-f968dcc63c28 · outbound

This paper cites On the robustness of large multimodal models against image adversarial attacks.

How Do Vision-Language Models Process Conflicting Information Across Modalities? On the robustness of large multimodal models against image adversarial attacks

Reference 6

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Observation 5dd82d92-11e5-4409-87d0-506b45b03509 · outbound

This paper cites an unresolved cited work.

How Do Vision-Language Models Process Conflicting Information Across Modalities? Unresolved cited work

Reference 7

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Observation 921bb0d0-f044-467b-b493-b92e6524b6c4 · outbound

This paper cites Words or Vision: Do Vision-Language Models Have Blind Faith in Text?.

How Do Vision-Language Models Process Conflicting Information Across Modalities? Words or Vision: Do Vision-Language Models Have Blind Faith in Text?

Reference 8

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

How Do Vision-Language Models Process Conflicting Information Across Modalities? Imagenet: A large-scale hierarchical image database

Reference 9

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This paper cites The pascal visual object classes (voc) challenge.

How Do Vision-Language Models Process Conflicting Information Across Modalities? The pascal visual object classes (voc) challenge

Reference 10

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Observation d8e1b6d8-03f9-410f-b75b-59f6b38387d5 · outbound

This paper cites Pixels versus priors: Controlling knowledge priors in vision-language models through visual counterfacts.

How Do Vision-Language Models Process Conflicting Information Across Modalities? Pixels versus priors: Controlling knowledge priors in vision-language models through visual counterfacts

Reference 11

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Observation c58d2bf2-5ac0-4aac-9135-1e7583da58b1 · outbound

This paper cites What do VLM s NOTICE ? a mechanistic interpretability pipeline for G aussian-noise-free text-image corruption and evaluation.

How Do Vision-Language Models Process Conflicting Information Across Modalities? What do VLM s NOTICE ? a mechanistic interpretability pipeline for G aussian-noise-free text-image corruption and evaluation

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:47:11.373646Z

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This paper cites How does GPT -2 compute greater-than?: Interpreting mathematical abilities in a pre-trained language model.

How Do Vision-Language Models Process Conflicting Information Across Modalities? How does GPT -2 compute greater-than?: Interpreting mathematical abilities in a pre-trained language model

Reference 13

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How Do Vision-Language Models Process Conflicting Information Across Modalities? Unresolved cited work

Reference 14

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This paper cites Adam: A Method for Stochastic Optimization.

How Do Vision-Language Models Process Conflicting Information Across Modalities? Adam: A Method for Stochastic Optimization

Reference 15

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Observation 9f6745f4-7f2e-40e3-9df7-942bb196b3cc · outbound

This paper cites Learning multiple layers of features from tiny images.(2009), 2009.

How Do Vision-Language Models Process Conflicting Information Across Modalities? Learning multiple layers of features from tiny images.(2009), 2009

Reference 16

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This paper cites Beyond the doors of perception: Vision transformers represent relations between objects.

How Do Vision-Language Models Process Conflicting Information Across Modalities? Beyond the doors of perception: Vision transformers represent relations between objects

Reference 17

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Observation c6a79849-c175-4e02-a595-9753ee31a037 · outbound

This paper cites LL a VA -onevision: Easy visual task transfer.

How Do Vision-Language Models Process Conflicting Information Across Modalities? LL a VA -onevision: Easy visual task transfer

Reference 18

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Observation a7aab324-ef49-4635-a7d8-1afb4b707de1 · outbound

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

How Do Vision-Language Models Process Conflicting Information Across Modalities? Inference-time intervention: Eliciting truthful answers from a language model

Reference 19

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This paper cites Benchmarking Multi-modal Semantic Segmentation under Sensor Failures: Missing and Noisy Modality Robustness.

How Do Vision-Language Models Process Conflicting Information Across Modalities? Benchmarking Multi-modal Semantic Segmentation under Sensor Failures: Missing and Noisy Modality Robustness

Reference 20

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This paper cites Improved baselines with visual instruction tuning, 2023.

How Do Vision-Language Models Process Conflicting Information Across Modalities? Improved baselines with visual instruction tuning, 2023

Reference 21

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Observation 49b6407e-6b08-4795-83df-bbc8955a76a8 · outbound

This paper cites The quest for the right mediator: A history, survey, and theoretical grounding of causal interpretability.

How Do Vision-Language Models Process Conflicting Information Across Modalities? The quest for the right mediator: A history, survey, and theoretical grounding of causal interpretability

Reference 22

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Observation 835729aa-e31d-4519-90a5-7c51c4c1ff2d · outbound

This paper cites Towards interpreting visual information processing in vision-language models.

How Do Vision-Language Models Process Conflicting Information Across Modalities? Towards interpreting visual information processing in vision-language models

Reference 23

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This paper cites Same task, different circuits: Disentangling modality-specific mechanisms in vlms.

How Do Vision-Language Models Process Conflicting Information Across Modalities? Same task, different circuits: Disentangling modality-specific mechanisms in vlms

Reference 24

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This paper cites Introducing operator.

How Do Vision-Language Models Process Conflicting Information Across Modalities? Introducing operator

Reference 25

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Observation a68d5511-6e85-4683-8fb3-0e6847d566ba · outbound

This paper cites GPT-4 Technical Report.

How Do Vision-Language Models Process Conflicting Information Across Modalities? GPT-4 Technical Report

Reference 26

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This paper cites Interpreting the linear structure of vision-language model embedding spaces.

How Do Vision-Language Models Process Conflicting Information Across Modalities? Interpreting the linear structure of vision-language model embedding spaces

Reference 27

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This paper cites V -measure: A conditional entropy-based external cluster evaluation measure.

How Do Vision-Language Models Process Conflicting Information Across Modalities? V -measure: A conditional entropy-based external cluster evaluation measure

Reference 28

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Observation 490fa9ea-1e47-4873-b46e-c7600c1a4bab · outbound

This paper cites On the Adversarial Robustness of Multi-Modal Foundation Models.

How Do Vision-Language Models Process Conflicting Information Across Modalities? On the Adversarial Robustness of Multi-Modal Foundation Models

Reference 29

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This paper cites What do you learn from context? probing for sentence structure in contextualized word representations.

How Do Vision-Language Models Process Conflicting Information Across Modalities? What do you learn from context? probing for sentence structure in contextualized word representations

Reference 30

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This paper cites Bert rediscovers the classical nlp pipeline.

How Do Vision-Language Models Process Conflicting Information Across Modalities? Bert rediscovers the classical nlp pipeline

Reference 31

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Observation 355d1c63-4f5c-4747-8764-fd6dccae3cb5 · outbound

This paper cites Investigating gender bias in language models using causal mediation analysis.

How Do Vision-Language Models Process Conflicting Information Across Modalities? Investigating gender bias in language models using causal mediation analysis

Reference 32

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This paper cites Analyzing multi-head self-attention: Specialized heads do the heavy lifting, the rest can be pruned.

How Do Vision-Language Models Process Conflicting Information Across Modalities? Analyzing multi-head self-attention: Specialized heads do the heavy lifting, the rest can be pruned

Reference 33

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How Do Vision-Language Models Process Conflicting Information Across Modalities? The caltech-ucsd birds-200-2011 dataset

Reference 34

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This paper cites Interpretability in the Wild: a Circuit for Indirect Object Identification in GPT-2 small.

How Do Vision-Language Models Process Conflicting Information Across Modalities? Interpretability in the Wild: a Circuit for Indirect Object Identification in GPT-2 small

Reference 35

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Observation be17bcbc-6a94-4caf-9ef8-f2d0e315a1ea · outbound

This paper cites Multimodal Inconsistency Reasoning (MMIR): A New Benchmark for Multimodal Reasoning Models.

How Do Vision-Language Models Process Conflicting Information Across Modalities? Multimodal Inconsistency Reasoning (MMIR): A New Benchmark for Multimodal Reasoning Models

Reference 36

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How Do Vision-Language Models Process Conflicting Information Across Modalities? Characterizing mechanisms for factual recall in language models

Reference 37

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This paper cites Does vision-and-language pretraining improve lexical grounding? In Findings of the Association for Computational Linguistics: EMNLP 2021, pages 4357--4366, 2021.

How Do Vision-Language Models Process Conflicting Information Across Modalities? Does vision-and-language pretraining improve lexical grounding? In Findings of the Association for Computational Linguistics: EMNLP 2021, pages 4357--4366, 2021

Reference 38

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This paper cites Emergence of abstract state representations in embodied sequence modeling.

How Do Vision-Language Models Process Conflicting Information Across Modalities? Emergence of abstract state representations in embodied sequence modeling

Reference 39

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Observation 658b2ef7-f1d6-4d56-b06a-25407e037b18 · outbound

This paper cites Calling a spade a heart: Gaslighting multimodal large language models via negation, 2025.

How Do Vision-Language Models Process Conflicting Information Across Modalities? Calling a spade a heart: Gaslighting multimodal large language models via negation, 2025

Reference 40

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This paper cites Unraveling Cross-Modality Knowledge Conflicts in Large Vision-Language Models.

How Do Vision-Language Models Process Conflicting Information Across Modalities? Unraveling Cross-Modality Knowledge Conflicts in Large Vision-Language Models

Reference 41

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Pith citing papers

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Can Large Multimodal Models Actively Recognize Faulty Inputs? A Systematic Evaluation Framework of Their Input Scrutiny Ability cites this paper.

Can Large Multimodal Models Actively Recognize Faulty Inputs? A Systematic Evaluation Framework of Their Input Scrutiny Ability How Do Vision-Language Models Process Conflicting Information Across Modalities?

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TRANSPORTER: Transferring Visual Semantics from VLM Manifolds cites this paper.

TRANSPORTER: Transferring Visual Semantics from VLM Manifolds How Do Vision-Language Models Process Conflicting Information Across Modalities?

Reference 43

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Beyond Text-Dominance: Understanding Modality Preference of Omni-modal Large Language Models cites this paper.

Beyond Text-Dominance: Understanding Modality Preference of Omni-modal Large Language Models How Do Vision-Language Models Process Conflicting Information Across Modalities?

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Vision-Default, Prior-Override: Causal Mechanisms of Perception-Knowledge Conflict in Vision-Language Models cites this paper.

Vision-Default, Prior-Override: Causal Mechanisms of Perception-Knowledge Conflict in Vision-Language Models How Do Vision-Language Models Process Conflicting Information Across Modalities?

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ScAle: Attention Head Scaling as a Minimal Adapter for Spatial Reasoning in Vision Language Models cites this paper.

ScAle: Attention Head Scaling as a Minimal Adapter for Spatial Reasoning in Vision Language Models How Do Vision-Language Models Process Conflicting Information Across Modalities?

Reference 10

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Observation 218f5833-c688-4f6d-b7e9-af96fcff062a · inbound

Attending to Multimodal Generation One Token at a Time cites this paper.

Attending to Multimodal Generation One Token at a Time How Do Vision-Language Models Process Conflicting Information Across Modalities?

Reference 13

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Linguistic Context Recodes Visual Representations in Vision-Language Models cites this paper.

Linguistic Context Recodes Visual Representations in Vision-Language Models How Do Vision-Language Models Process Conflicting Information Across Modalities?

Reference 54

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PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models cites this paper.

PragMatch: Separating Pragmatic Incongruity from Cross-Modal Mismatch in Large Vision-Language Models How Do Vision-Language Models Process Conflicting Information Across Modalities?

Reference 49

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