MoVISA: Multi-Token Reasoning for Video Object Segmentation

arXiv:2609.28956 · cs.CV · Submitted 2026-09-24 · Read on arXiv

cs.CV

Submitted: 2026-09-24

Updated: 2026-09-24

Code: https://github.com/InternLM/xtuner

Terminology

• Large Language Model — 13× in this paper
• Benchmark — 6× in this paper · explained in 2 episodes
• Core — 6× in this paper · explained in 2 episodes
• Alignment — 5× in this paper · explained in 1 episode
• Embeddings — 5× in this paper · explained in 2 episodes
• Segmentation Masks — 5× in this paper · explained in 2 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Grounding — 4× in this paper · explained in 3 episodes
• Instruction Tuning — 3× in this paper · explained in 2 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Institutional Review Board — 2× in this paper
• Large Language Models (LLMs) — 2× in this paper · explained in 6 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Ablation study — 1× in this paper · explained in 1 episode
• Abstraction — 1× in this paper · explained in 1 episode
• Accuracy — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Embodied AI — 1× in this paper · explained in 2 episodes
• Few-Shot Learning — 1× in this paper · explained in 4 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Large Language Model (LLM) — 1× in this paper · explained in 3 episodes
• Mask Generation — 1× in this paper · explained in 2 episodes
• Temporal Abstraction — 1× in this paper · explained in 2 episodes
• Temporal Reasoning — 1× in this paper · explained in 2 episodes
• Temporal consistency — 1× in this paper · explained in 2 episodes
• Tokenization — 1× in this paper · explained in 2 episodes

Sources

• Otter: A Multi-Modal Model with In-Context Instruction Tuning
• GPT-4 Technical Report
• TrackGPT -- A generative pre-trained transformer for cross-domain entity trajectory forecasting
• mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality
• Sa2VA: Marrying SAM2 with LLaVA for Dense Grounded Understanding of Images and Videos
• MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

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