Research map / Vision-language and multimodal / Robot action and navigation
Interactive Grounded Language Acquisition and Generalization in a 2D World
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Share a concept detection function between language prediction and grounding | Proposed model · XWorld ZS2 | NAV success rate | Helped |
| Disentangle explicit language grounding from downstream computations | Proposed model · XWorld ZS1 | NAV success rate: 84.3% | Helped |
| Disentangle explicit language grounding from downstream computations | Proposed model · XWorld ZS2 | NAV success rate: 85.2% | Helped |
| Use contextual attention instead of the interpreter | Proposed model · XWorld ZS2 | NAV success rate: up to 80% | Hurt |
| Use stacked attention instead of the interpreter | Proposed model · XWorld ZS2 | NAV success rate: up to 80% | Hurt |
| Use contextual attention instead of the interpreter | Proposed model · XWorld ZS2 | QA accuracy: up to 35% | Hurt |
| Use stacked attention instead of the interpreter | Proposed model · XWorld ZS2 | QA accuracy: up to 35% | Hurt |
| Remove the QA pipeline and train only on NAV (ablation) | Proposed model · XWorld NAV training | accumulated discounted reward per session: -0.8 to -3.0 | Hurt |
| Remove spatial attention and attend to the whole image | VIS-LSTM · XWorld NAV | navigation success rate | Hurt |
| Remove spatial attention and attend to the whole image | ConcatEmbed · XWorld NAV | navigation success rate | Hurt |
Closest papers by meaning
- Learning to Model the World With Language (ICML 2024 · similarity 0.89)
- Distilling Internet-Scale Vision-Language Models into Embodied Agents (ICML 2023 · similarity 0.88)
- Just Ask: An Interactive Learning Framework for Vision and Language Navigation (AAAI 2020 · similarity 0.87)
- SILG: The Multi-domain Symbolic Interactive Language Grounding Benchmark (NeurIPS 2021 · similarity 0.87)
- Ground-Compose-Reinforce: Grounding Language in Agentic Behaviours using Limited Data (NeurIPS 2025 · similarity 0.87)
- Prismatic VLMs: Investigating the Design Space of Visually-Conditioned Language Models (ICML 2024 · similarity 0.86)
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