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--- |
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license: mit |
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extra_gated_prompt: >- |
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You agree to not use the dataset to conduct experiments that cause harm to |
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human subjects. Please note that the data in this dataset may be subject to |
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other agreements. Before using the data, be sure to read the relevant |
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agreements carefully to ensure compliant use. Video copyrights belong to the |
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original video creators or platforms and are for academic research use only. |
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task_categories: |
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- visual-question-answering |
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extra_gated_fields: |
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Name: text |
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Company/Organization: text |
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Country: text |
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E-Mail: text |
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modalities: |
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- Video |
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- Text |
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configs: |
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- config_name: action_sequence |
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data_files: json/action_sequence.json |
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- config_name: moving_count |
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data_files: json/moving_count.json |
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- config_name: action_prediction |
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data_files: json/action_prediction.json |
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- config_name: episodic_reasoning |
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data_files: json/episodic_reasoning.json |
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- config_name: action_antonym |
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data_files: json/action_antonym.json |
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- config_name: action_count |
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data_files: json/action_count.json |
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- config_name: scene_transition |
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data_files: json/scene_transition.json |
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- config_name: object_shuffle |
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data_files: json/object_shuffle.json |
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- config_name: object_existence |
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data_files: json/object_existence.json |
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- config_name: unexpected_action |
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data_files: json/unexpected_action.json |
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- config_name: moving_direction |
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data_files: json/moving_direction.json |
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- config_name: state_change |
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data_files: json/state_change.json |
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- config_name: object_interaction |
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data_files: json/object_interaction.json |
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- config_name: character_order |
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data_files: json/character_order.json |
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- config_name: action_localization |
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data_files: json/action_localization.json |
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- config_name: counterfactual_inference |
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data_files: json/counterfactual_inference.json |
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- config_name: fine_grained_action |
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data_files: json/fine_grained_action.json |
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- config_name: moving_attribute |
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data_files: json/moving_attribute.json |
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- config_name: egocentric_navigation |
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data_files: json/egocentric_navigation.json |
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language: |
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- en |
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size_categories: |
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- 1K<n<10K |
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--- |
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# Proposed MVTamperBench, a novel benchmark that systematically evaluates the adversarial robustness of VLMs against video specific tampering techniques, with a focus on temporal reasoning and multimodal coherence. |
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|
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## Dataset Description |
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MVTamperBench applies five distinct tampering techniques to the original MVBench videos: Dropping, Masking, Substitution, Repetition, and Rotation. Each tampering effect introduces unique adversarial challenges to test VLM robustness under various conditions |
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|
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### Tampering Techniques |
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- **Dropping**: Removes a 1-second segment, creating temporal discontinuity. |
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- **Masking**: Overlays a black rectangle on a 1-second segment, simulating visual data loss. |
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- **Rotation**: Rotates a 1-second segment by 180 degrees, introducing spatial distortion. |
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- **Substitution**: Replaces a 1-second segment with a random clip from another video, disrupting the temporal and contextual flow. |
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- **Repetition**: Repeats a 1-second segment, introducing temporal redundancy. |
