Look Back, Think Ahead: Visual Memory on Demand for Efficient Multimodal Reasoning

arXiv:2610.12060 · cs.CV · Submitted 2026-10-08 · Read on arXiv

cs.CV

Submitted: 2026-10-08

Updated: 2026-10-08

Terminology

• Trace — 40× in this paper · explained in 2 episodes
• Benchmark — 20× in this paper · explained in 2 episodes
• Accuracy — 15× in this paper · explained in 1 episode
• Aggregation — 10× in this paper · explained in 1 episode
• Computer Vision and Pattern Recognition — 8× in this paper
• Calibration — 6× in this paper · explained in 7 episodes
• Decode — 6× in this paper · explained in 2 episodes
• Pruning — 6× in this paper · explained in 4 episodes
• Multimodal Reasoning — 5× in this paper · explained in 5 episodes
• Distillation — 4× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Adaptation — 3× in this paper · explained in 1 episode
• Deformable Aggregation of Region-wise Tokens — 3× in this paper
• Grounding — 3× in this paper · explained in 3 episodes
• Reinforcement Learning — 3× in this paper · explained in 4 episodes
• Robustness — 3× in this paper · explained in 5 episodes
• Vision-language models — 3× in this paper · explained in 2 episodes
• Core — 2× in this paper · explained in 2 episodes
• Embeddings — 2× in this paper · explained in 2 episodes
• International Conference on Document Analysis and Recognition — 2× in this paper
• Regularization — 2× in this paper · explained in 3 episodes
• Temporal Routing for Adaptive Contextual Evidence — 2× in this paper
• Winter Conference on Applications of Computer Vision — 2× in this paper
• Ablation Studies — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• AdamW Optimizer — 1× in this paper · explained in 1 episode
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Elias — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Hallucination — 1× in this paper · explained in 4 episodes
• Instruction Tuning — 1× in this paper · explained in 2 episodes
• Optimal Transport — 1× in this paper · explained in 5 episodes
• Sparse Attention — 1× in this paper · explained in 5 episodes
• Visual Grounding — 1× in this paper · explained in 2 episodes

Sources

• Towards better understanding of gradient-based attribution methods for Deep Neural Networks
• Layer Normalization
• Qwen3-VL Technical Report
• Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation
• Mamba: Linear-Time Sequence Modeling with Selective State Spaces
• Gaussian Error Linear Units (GELUs)
• Distilling the Knowledge in a Neural Network
• GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning
• TVI-CoT: Text-Visual Interleaved Chain-of-Thought Reasoning for Multimodal Understanding
• Decoupled Weight Decay Regularization
• RoRA: Role-Oriented Regional Allocation for Visual Token Pruning in MLLMs
• Simplified Sparse Attention via Gist Tokens
• VisualPuzzles: Decoupling Multimodal Reasoning Evaluation from Domain Knowledge
• Kimi-VL Technical Report
• InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency
• LogicVista: Multimodal LLM Logical Reasoning Benchmark in Visual Contexts

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