LongNav-R1 Scaling Under Instruction Ambiguity in ValHouse3D Benchmark

This report synthesises findings from 4 peer-reviewed papers addressing the following research question: How does LongNav-R1's performance scale with increasing instruction ambiguity complexity on the ValHouse3D benchmark compared to single-turn VLA policies in terms of trajectory deviation and success. In the vision and language navigation task (Anderson et al. 2018), the agent may encounter ambiguous situations that are hard to interpret by just relying on visual information and natural language instructions. 8 claims were extracted from source literature; 8 were independently verified against retrieved documents. An automated multi-reviewer quality assessment produced a score of 8.3/10. This report is a machine-generated literature synthesis and does not constitute original research.

Research goal: How does LongNav-R1's performance scale with increasing instruction ambiguity complexity on the ValHouse3D benchmark compared to single-turn VLA policies in terms of trajectory deviation and success rate?

Autonomous literature synthesis. Automated review score: 8.3/10. Full text and citation available at Assignee Research.