Research map / Multi-agent systems and games / Human-AI and goal-conditioned
Layout-Aware Dreamer for Embodied Visual Referring Expression Grounding
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add Layout Learner (ablation) | CLIP-feature VLN-DUET baseline · REVERIE Val-unseen | SR: 52.34 -> 56.04 | Helped |
| add Layout Learner (ablation) | CLIP-feature VLN-DUET baseline · REVERIE Val-unseen | RGS: 35.02 -> 37.06 | Helped |
| add Goal Dreamer (ablation) | CLIP-feature VLN-DUET baseline · REVERIE Val-unseen | SR: 52.34 -> 53.45 | Helped |
| add Goal Dreamer (ablation) | CLIP-feature VLN-DUET baseline · REVERIE Val-unseen | RGS: 35.02 -> 34.34 | Hurt |
| add Layout Learner and Goal Dreamer (ablation) | CLIP-feature VLN-DUET baseline · REVERIE Val-unseen | SR: 52.34 -> 57.00 | Helped |
| replace the visual room codebook with a room-type classification head (ablation) | LAD · REVERIE Val-unseen | SR: 57.00 -> 53.73 | Hurt |
| replace the visual room codebook with textual room prompts (ablation) | LAD · REVERIE Val-unseen | SR: 57.00 -> 51.38 | Hurt |
| replace the visual room codebook with textual room prompts (ablation) | LAD · REVERIE Val-unseen | RGS: 37.80 -> 32.38 | Hurt |
| use LAD instead of VLN-DUET | REVERIE · Test-unseen | SR: 52.51 -> 56.53 | Helped |
| use LAD instead of VLN-DUET | REVERIE · Test-unseen | RGS: 31.88 -> 35.31 | Helped |
| use LAD instead of VLN-DUET | SOON · Test Unseen | SR: 33.44 -> 39.59 | Helped |
Closest papers by meaning
- Scene-Intuitive Agent for Remote Embodied Visual Grounding (CVPR 2021 · similarity 0.91)
- Direct Numerical Layout Generation for 3D Indoor Scene Synthesis via Spatial Reasoning (NeurIPS 2025 · similarity 0.86)
- EmbodiedBench: Comprehensive Benchmarking Multi-modal Large Language Models for Vision-Driven Embodied Agents (ICML 2025 · similarity 0.86)
- Navigating the Digital World as Humans Do: Universal Visual Grounding for GUI Agents (ICLR 2025 · similarity 0.86)
- Multi-Modal Grounded Planning and Efficient Replanning for Learning Embodied Agents with a Few Examples (AAAI 2025 · similarity 0.85)
- Distilling LLM Prior to Flow Model for Generalizable Agent’s Imagination in Object Goal Navigation (NeurIPS 2025 · similarity 0.85)
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