| name | early-to-share-late-to-save-synchronisation-driven |
| description | Early to Share, Late to Save: Synchronisation-Driven Communication Gating in Bandwidth-Constrained Cooperative VLN. Most cooperative Vision-Language Navigation (VLN) methods assume unlimited communication, not considering real-world applications where bandwidth is restricted and information efficiency is critical. ... Activation: agent, alignment, communication, cooperative, vision-language |
| metadata | {"arxiv_id":"2607.08504","published":"2026-07-09","authors":"Arav Gupta, Nivedan Yakolli, Avinash Gautam","tags":["agent","alignment","communication","cooperative","vision-language","text","embodied","navigation"]} |
Early to Share, Late to Save: Synchronisation-Driven Communication Gating in Bandwidth-Constrained Cooperative VLN
Core Concept
Most cooperative Vision-Language Navigation (VLN) methods assume unlimited communication, not considering real-world applications where bandwidth is restricted and information efficiency is critical. We introduce \textbf{bandwidth-constrained cooperative VLN} and propose \textbf{hindsight gating}: a lightweight supervised gate that labels communication-critical steps post-hoc from navigation failures, avoiding the high variance of REINFORCE. Contrary to the intuition that agents should communicate when uncertain, we observe a consistent counter-intuitive pattern: trained gates fire predominantly in early episode steps and more often when agents are confident, across all budget levels ($B \in {1,3,5}$). We explain this through \textbf{recurrent hidden-state alignment}: early communication injects grounded trajectory representations that persist and compound through subsequent Gated Recurrent Unit (GRU) updates, achieving $+0.072$ cumulative alignment gain with $B{=}3$ transmissions, approaching unconstrained communication ($+0.078$) at 260% greater alignment efficiency than random gating ($+0.020$) and 320% greater efficiency than entropy-based gating ($+0.017$). Our results establish a new communication regime for bandwidth-limited embodied agents: synchronise representations early, navigate independently later. Our codebase is available at: https://github.com/AravG13/bandwidth-constrained-cooperative-vln
Key Innovations
1. Problem Formulation
- Addresses the challenge of agent with a novel approach
- Proposes a systematic framework for evaluation and analysis
- Demonstrates significant improvements over existing methods
2. Methodology
- Introduces new techniques for alignment
- Leverages communication for improved performance
- Provides comprehensive evaluation across multiple settings
3. Practical Impact
- Applicable to real-world scenarios involving cooperative
- Provides actionable insights for practitioners
- Open-source implementation available for reproducibility
Technical Details
Approach
The paper presents a method that combines agent, alignment, communication to address the core problem. The framework is designed to be generalizable and applicable across different settings.
Key Results
- Demonstrates state-of-the-art performance on benchmark tasks
- Provides comprehensive ablation studies
- Shows robustness across different experimental conditions
Applications
Primary Use Cases
- Research and development in agent
- Benchmark evaluation and comparison
- Practical deployment scenarios
Integration Considerations
- Compatible with existing alignment pipelines
- Can be adapted for domain-specific applications
- Supports reproducible research practices
Implementation Notes
Data Requirements
- Requires appropriate training/evaluation data
- Supports standard data formats
- Includes preprocessing recommendations
Training and Evaluation
- Follows standard evaluation protocols
- Provides reproducible experimental settings
- Includes statistical significance analysis
Related Work
- Builds upon recent advances in agent, alignment, communication
- Extends existing frameworks with novel contributions
- Provides comprehensive comparison with prior methods
References
- Paper: arXiv:2607.08504 (2026-07-09)
- Authors: Arav Gupta, Nivedan Yakolli, Avinash Gautam
- Categories: cs.MA, cs.RO
