mllm

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“Cube Bench is a benchmark for spatial visual reasoning in MLLMs.”

“The paper is from ArXiv.”

“The study reveals a spatial reasoning gap in MLLMs.”

“The paper focuses on debiasing importance and promoting structural diversity in the token selection process.”

“The paper introduces IPCV, an information-preserving compression method.”

“The research focuses on learning cost-aware MLLM agents.”

“The article likely discusses a method to extend the visual context available to MLLMs.”

“The article's source is ArXiv, indicating a research paper.”

“CodeDance is a Dynamic Tool-integrated MLLM for Executable Visual Reasoning.”

“The article likely discusses a technique named 'Sketch-in-Latents'.”

“The article is sourced from ArXiv.”

“DrivePI utilizes spatial-aware 4D MLLMs for unified autonomous driving understanding, perception, prediction, and planning.”

“The research is based on ArXiv, suggesting a peer-reviewed or preliminary stage of academic development.”

“The research is sourced from ArXiv.”

“The research focuses on machine unlearning for multimodal LLMs.”

“The paper introduces IF-Bench and generative visual prompting for infrared image analysis with MLLMs.”

“The research focuses on the inconsistency in MLLMs.”

“HalluShift++: Bridging Language and Vision through Internal Representation Shifts for Hierarchical Hallucinations in MLLMs”

“The research focuses on enhancing the proactive interaction of Video MLLMs.”

“The research is published on ArXiv.”

“The paper leverages Temporal-Aware Multi-Task Reinforcement Learning to enhance temporal understanding.”

“The paper focuses on contrastive region masking within the context of MLLMs.”

“The research focuses on sequential embodied MLLM reasoning and exploration.”

“The research focuses on scaling Many-to-Many Speech-to-Text Translation with MLLMs to 70 languages.”

“The research focuses on boosting spatial reasoning capability of MLLMs for 3D Visual Grounding.”

“ESMC leverages MLLMs for embedding selection.”

“The paper is published on ArXiv.”

“The research uses an iterative framework combining LLMs, T2I models, and MLLMs.”

“The article's core focus is on aligning MLLMs with human cognitive perception of images.”