Search-to-World: Evaluation of 3D World Delivery from User Request through Web Search

arXiv:2609.07605 · cs.CV · Submitted 2026-09-07 · Read on arXiv

cs.CV

Submitted: 2026-09-07

Updated: 2026-09-17

Project page: https://serper.dev

Terminology

• Grounding — 46× in this paper · explained in 3 episodes
• Benchmark — 36× in this paper · explained in 2 episodes
• Core — 25× in this paper · explained in 2 episodes
• Alignment — 18× in this paper · explained in 1 episode
• World Model — 13× in this paper · explained in 7 episodes
• Agentic System — 9× in this paper · explained in 2 episodes
• Consistency — 9× in this paper · explained in 3 episodes
• Conference on Computer Vision and Pattern Recognition — 8× in this paper
• Ablation — 6× in this paper · explained in 1 episode
• Benchmarking — 6× in this paper · explained in 4 episodes
• Verification — 6× in this paper · explained in 2 episodes
• World Delivery Rate — 6× in this paper
• Fine-Tuning — 5× in this paper · explained in 5 episodes
• Observed Retrieval Rate — 5× in this paper
• Trace — 4× in this paper · explained in 2 episodes
• LoRA Adapters — 3× in this paper · explained in 3 episodes
• alpha — 3× in this paper · explained in 1 episode
• Fidelity — 2× in this paper · explained in 2 episodes
• Gaussian Splatting — 2× in this paper · explained in 4 episodes
• Provenance — 2× in this paper · explained in 4 episodes
• Supervised Fine-Tuning (SFT) — 2× in this paper · explained in 8 episodes
• AI Agents — 1× in this paper · explained in 2 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Agentic Search — 1× in this paper · explained in 1 episode
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• LLM judge — 1× in this paper · explained in 2 episodes
• Latent Diffusion Model — 1× in this paper · explained in 2 episodes
• Latent Diffusion Models — 1× in this paper · explained in 2 episodes
• Sparse Attention — 1× in this paper · explained in 5 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes
• Vision-Language Model — 1× in this paper
• Vision-Language Model (VLM) — 1× in this paper · explained in 3 episodes
• Visual Grounding — 1× in this paper · explained in 2 episodes

Sources

• AI Flow: Perspectives, Scenarios, and Approaches
• Full-4D: Generating Full-Scope 4D Scenes from a Single-View Video
• Cascade-Zero123: One Image to Highly Consistent 3D with Self-Prompted Nearby Views
• LiftImage3D: Lifting Any Single Image to 3D Gaussians with Video Generation Priors
• TeleWorld: Towards Dynamic Multimodal Synthesis with a 4D World Model
• DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence
• PlayWorld: Benchmarking World Models with Agent Players over Long-Horizon Objectives
• Towards Long-horizon Agentic Multimodal Search
• GeoT2V-Bench: Benchmarking 3D Consistency in Text-to-Video Models via 3D Reconstruction
• CineWeaver: Training-Free Reference-Controllable Multi-Shot Long Video Generation for Cinematic Storytelling
• AI Agents That Matter
• Qwen3-VL-Embedding and Qwen3-VL-Reranker: A Unified Framework for State-of-the-Art Multimodal Retrieval and Ranking
• Video-Browser: Towards Agentic Open-web Video Browsing
• Watching, Reasoning, and Searching: A Video Deep Research Benchmark on Open Web for Agentic Video Reasoning
• AgentBoard: An Analytical Evaluation Board of Multi-turn LLM Agents
• AI Flow at the Network Edge
• MMSearch-Plus: Benchmarking Provenance-Aware Search for Multimodal Browsing Agents
• BrowseComp: A Simple Yet Challenging Benchmark for Browsing Agents
• Metric-Solver: Sliding Anchored Metric Depth Estimation from a Single Image

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