Informative Viewpoint Selection for Episodic-Memory Embodied Question Answering using Omnidirectional Images

arXiv:2609.33288 · cs.CV, cs.RO · Submitted 2026-09-27 · Read on arXiv

cs.CV, cs.RO

Submitted: 2026-09-27

Updated: 2026-09-27

Terminology

• RAG — 34× in this paper · explained in 3 episodes
• Accuracy — 11× in this paper · explained in 1 episode
• Embodied Question Answering — 11× in this paper
• Fine-Tuning — 9× in this paper · explained in 5 episodes
• Embeddings — 7× in this paper · explained in 2 episodes
• Benchmark — 6× in this paper · explained in 2 episodes
• Visual Question Answering — 5× in this paper
• Conference on Computer Vision and Pattern Recognition — 4× in this paper
• Embodied AI — 4× in this paper · explained in 2 episodes
• Redundancy — 4× in this paper · explained in 2 episodes
• International Conference on Robotics and Automation — 3× in this paper
• Retrieval-Augmented Generation — 3× in this paper
• Ablation — 2× in this paper · explained in 1 episode
• Ablation Studies — 2× in this paper · explained in 1 episode
• Adaptation — 2× in this paper · explained in 1 episode
• Contrastive Learning — 2× in this paper · explained in 5 episodes
• Cosine Similarity — 2× in this paper · explained in 3 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• International Conference on Machine Learning — 2× in this paper
• Retrieval-Augmented Generation (RAG) — 2× in this paper · explained in 16 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• AI Foundation Model — 1× in this paper · explained in 1 episode
• Affordance — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• CVF International Conference on Computer Vision — 1× in this paper
• Foundation Models — 1× in this paper · explained in 7 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Instruction Tuning — 1× in this paper · explained in 2 episodes
• International Conference on Learning Representations — 1× in this paper
• Large Language Model (LLM) — 1× in this paper · explained in 3 episodes
• Low-Rank Adaptation (LoRA) — 1× in this paper · explained in 9 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Semantic Understanding — 1× in this paper · explained in 2 episodes
• Task Planning — 1× in this paper · explained in 2 episodes
• Verification — 1× in this paper · explained in 2 episodes
• Vision-Language Model (VLM) — 1× in this paper · explained in 3 episodes
• Vision-Language Models (VLMs) — 1× in this paper · explained in 6 episodes
• Vision-language models — 1× in this paper · explained in 2 episodes
• alpha — 1× in this paper · explained in 1 episode

Sources

• Qwen2.5-VL Technical Report
• GPT-4 Technical Report
• SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features
• Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution
• Embodied-RAG: General Non-parametric Embodied Memory for Retrieval and Generation
• InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models

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