Cover Image

GlitchBench: Can large multimodal models detect video game glitches?

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Taesiri, Mohammad Reza, Feng, Tianjun, Nguyen, Anh, Bezemer, Cor-Paul
Format:	Preprint
Published:	2023
Subjects:	Computer Vision and Pattern Recognition Artificial Intelligence Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

VideoGameBunny: Towards vision assistants for video games
by: Taesiri, Mohammad Reza, et al.
Published: (2024)

VideoGameQA-Bench: Evaluating Vision-Language Models for Video Game Quality Assurance
by: Taesiri, Mohammad Reza, et al.
Published: (2025)

TempGlitch: Evaluating Vision-Language Models for Temporal Glitch Detection in Gameplay Videos
by: Yu, Yakun, et al.
Published: (2026)

RESP: Reference-guided Sequential Prompting for Visual Glitch Detection in Video Games
by: Yu, Yakun, et al.
Published: (2026)

VideoGameBench: Can Vision-Language Models complete popular video games?
by: Zhang, Alex L., et al.
Published: (2025)

Allowing humans to interactively guide machines where to look does not always improve human-AI team's classification accuracy
by: Nguyen, Giang, et al.
Published: (2024)

PCNN: Probable-Class Nearest-Neighbor Explanations Improve Fine-Grained Image Classification Accuracy for AIs and Humans
by: Giang, et al.
Published: (2023)

B-score: Detecting biases in large language models using response history
by: Vo, An, et al.
Published: (2025)

Vision language models are blind: Failing to translate detailed visual features into words
by: Rahmanzadehgervi, Pooyan, et al.
Published: (2024)

When language and vision meet road safety: leveraging multimodal large language models for video-based traffic accident analysis
by: Zhang, Ruixuan, et al.
Published: (2025)

How Far Can VLMs Go for Visual Bug Detection? Studying 19,738 Keyframes from 41 Hours of Gameplay Videos
by: Lu, Wentao, et al.
Published: (2026)

SketchVLM: Vision language models can annotate images to explain thoughts and guide users
by: Collins, Brandon, et al.
Published: (2026)

Vision Language Models are Biased
by: Vo, An, et al.
Published: (2025)

Automatic benchmarking of large multimodal models via iterative experiment programming
by: Conti, Alessandro, et al.
Published: (2024)

Explaining latent representations of generative models with large multimodal models
by: Zhu, Mengdan, et al.
Published: (2024)

MAIRA-1: A specialised large multimodal model for radiology report generation
by: Hyland, Stephanie L., et al.
Published: (2023)

HoT: Highlighted Chain of Thought for Referencing Supporting Facts from Inputs
by: Nguyen, Tin, et al.
Published: (2025)

OmDet: Large-scale vision-language multi-dataset pre-training with multimodal detection network
by: Zhao, Tiancheng, et al.
Published: (2022)

CutPaste&Find: Efficient Multimodal Hallucination Detector with Visual-aid Knowledge Base
by: Nguyen, Cong-Duy, et al.
Published: (2025)

Can Multi-modal (reasoning) LLMs detect document manipulation?
by: Liang, Zisheng, et al.
Published: (2025)

Understanding Generative AI Capabilities in Everyday Image Editing Tasks
by: Taesiri, Mohammad Reza, et al.
Published: (2025)

Assessing the alignment between infants' visual and linguistic experience using multimodal language models
by: Tan, Alvin Wei Ming, et al.
Published: (2025)

Linguistically Informed Multimodal Fusion for Vietnamese Scene-Text Image Captioning: Dataset, Graph Framework, and Phonological Attention
by: Nguyen, Nhi Ngoc-Yen, et al.
Published: (2026)

Human-like object concept representations emerge naturally in multimodal large language models
by: Du, Changde, et al.
Published: (2024)

ProfVLM: A lightweight video-language model for multi-view proficiency estimation
by: Bianchi, Edoardo, et al.
Published: (2025)

BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs
by: Zhang, Sheng, et al.
Published: (2023)

DemaFormer: Damped Exponential Moving Average Transformer with Energy-Based Modeling for Temporal Language Grounding
by: Nguyen, Thong, et al.
Published: (2023)

Scaling medical imaging report generation with multimodal reinforcement learning
by: Liu, Qianchu, et al.
Published: (2026)

Catch Me If You Can Describe Me: Open-Vocabulary Camouflaged Instance Segmentation with Diffusion
by: Vu, Tuan-Anh, et al.
Published: (2023)

Anatomy of a Feeling: Narrating Embodied Emotions via Large Vision-Language Models
by: Saim, Mohammad, et al.
Published: (2025)

Hierarchical Document Parsing via Large Margin Feature Matching and Heuristics
by: Kiet, Duong Anh
Published: (2025)

Can CLIP Count Stars? An Empirical Study on Quantity Bias in CLIP
by: Zhang, Zeliang, et al.
Published: (2024)

Vibe-Eval: A hard evaluation suite for measuring progress of multimodal language models
by: Padlewski, Piotr, et al.
Published: (2024)

READ: Recurrent Adapter with Partial Video-Language Alignment for Parameter-Efficient Transfer Learning in Low-Resource Video-Language Modeling
by: Nguyen, Thong, et al.
Published: (2023)

ColorBench: Can VLMs See and Understand the Colorful World? A Comprehensive Benchmark for Color Perception, Reasoning, and Robustness
by: Liang, Yijun, et al.
Published: (2025)

M$^3$Face: A Unified Multi-Modal Multilingual Framework for Human Face Generation and Editing
by: Mofayezi, Mohammadreza, et al.
Published: (2024)

IV-Bench: A Benchmark for Image-Grounded Video Perception and Reasoning in Multimodal LLMs
by: Ma, David, et al.
Published: (2025)

Language Plays a Pivotal Role in the Object-Attribute Compositional Generalization of CLIP
by: Abbasi, Reza, et al.
Published: (2024)

RandLoRA: Full-rank parameter-efficient fine-tuning of large models
by: Albert, Paul, et al.
Published: (2025)

MAMA: Meta-optimized Angular Margin Contrastive Framework for Video-Language Representation Learning
by: Nguyen, Thong, et al.
Published: (2024)