Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images | Paper Citation Record

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images online" 'onlinestring :=

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images write newline

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images MQA-KEAL: Multi-hop Question Answering under Knowledge Editing for Arabic Language

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images Qwen2.5-VL Technical Report

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images Mitigating Open-Vocabulary Caption Hallucinations

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This paper cites CompCap: Improving Multimodal Large Language Models with Composite Captions.

Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images CompCap: Improving Multimodal Large Language Models with Composite Captions

Reference 6

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This paper cites HALC: Object Hallucination Reduction via Adaptive Focal-Contrast Decoding.

Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images HALC: Object Hallucination Reduction via Adaptive Focal-Contrast Decoding

Reference 7

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images COMPKE: Complex Question Answering under Knowledge Editing

Reference 9

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images Multi-hop Question Answering under Temporal Knowledge Editing

Reference 10

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images CODEMENV: Benchmarking Large Language Models on Code Migration

Reference 11

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images Seeing is Believing: Mitigating Hallucination in Large Vision-Language Models via CLIP-Guided Decoding

Reference 12

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis

Reference 13

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This paper cites Visual Writing Prompts: Character-Grounded Story Generation with Curated Image Sequences.

Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images Visual Writing Prompts: Character-Grounded Story Generation with Curated Image Sequences

Reference 14

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images Understanding Reasoning in Chain-of-Thought from the Hopfieldian View

Reference 15

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images Unresolved cited work

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images Unresolved cited work

Reference 17

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images Visual Storytelling

Reference 18

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images VCoder: Versatile Vision Encoders for Multimodal Large Language Models

Reference 19

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images Impact of Co-occurrence on Factual Knowledge of Large Language Models

Reference 20

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images Unresolved cited work

Reference 21

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images Volcano: Mitigating Multimodal Hallucination through Self-Feedback Guided Revision

Reference 22

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images Mitigating Object Hallucinations in Large Vision-Language Models through Visual Contrastive Decoding

Reference 23

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images Unresolved cited work

Reference 24

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images LLaVA-OneVision: Easy Visual Task Transfer

Reference 25

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images Evaluating Object Hallucination in Large Vision-Language Models

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning

Reference 28

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images RAR: Retrieving And Ranking Augmented MLLMs for Visual Recognition

Reference 29

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images Vista-LLaMA: Reducing Hallucination in Video Language Models via Equal Distance to Visual Tokens

Reference 30

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images Object Hallucination in Image Captioning

Reference 31

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images DetectLLM: Leveraging Log Rank Information for Zero-Shot Detection of Machine-Generated Text

Reference 32

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images Aligning Large Multimodal Models with Factually Augmented RLHF

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images Behind the Magic, MERLIM: Multi-modal Evaluation Benchmark for Large Image-Language Models

Reference 34

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images MLLM can see? Dynamic Correction Decoding for Hallucination Mitigation

Reference 35

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images Mitigating Fine-Grained Hallucination by Fine-Tuning Large Vision-Language Models with Caption Rewrites

Reference 36

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 37

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images Mementos: A Comprehensive Benchmark for Multimodal Large Language Model Reasoning over Image Sequences

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images VideoHallucer: Evaluating Intrinsic and Extrinsic Hallucinations in Large Video-Language Models

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images AutoHallusion: Automatic Generation of Hallucination Benchmarks for Vision-Language Models

Reference 40

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images EFUF: Efficient Fine-grained Unlearning Framework for Mitigating Hallucinations in Multimodal Large Language Models

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images An LLM can Fool Itself: A Prompt-Based Adversarial Attack

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images Unresolved cited work

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images MONAL: Model Autophagy Analysis for Modeling Human-AI Interactions

Reference 44

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images Exploring the Personality Traits of LLMs through Latent Features Steering

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images Fraud-R1 : A Multi-Round Benchmark for Assessing the Robustness of LLM Against Augmented Fraud and Phishing Inducements

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images Unresolved cited work

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images A Survey on Multimodal Large Language Models

Reference 49

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images Unresolved cited work

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images HalluciDoctor: Mitigating Hallucinatory Toxicity in Visual Instruction Data

Reference 51

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding

Reference 52

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images Mechanistic Unveiling of Transformer Circuits: Self-Influence as a Key to Model Reasoning

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images VL-Uncertainty: Detecting Hallucination in Large Vision-Language Model via Uncertainty Estimation

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images Locate-then-edit for Multi-hop Factual Recall under Knowledge Editing

Reference 55

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Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images Beyond Hallucinations: Enhancing LVLMs through Hallucination-Aware Direct Preference Optimization

Reference 57

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This paper cites IBD: Alleviating Hallucinations in Large Vision-Language Models via Image-Biased Decoding.

Mitigating Behavioral Hallucination in Multimodal Large Language Models for Sequential Images IBD: Alleviating Hallucinations in Large Vision-Language Models via Image-Biased Decoding

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