Zhiwen Fan

From Self-Confidence to Statistical Accuracy: Scaling Human-in-the-Loop Evaluation with Direct and LLM-Assisted Auditing

Harine Choi, Chenchen Kuai, Zihao Li, et al.

What Matters in Quality-Aware VLA Pretraining: A Benchmark and Empirical Study

Mingxuan Yan, Litian Gong, Dihong Huang, et al.

Can Induced Emotion Bias LLM Behaviors in Sequential Decision Making?

Minh Khoi Ho, Zihao Zhu, Runchuan Zhu, et al.

NavTrust: Benchmarking Trustworthiness for Embodied Navigation

Huaide Jiang, Yash Chaudhary, Yuping Wang, et al.

NavTrust is a new benchmark that tests how well AI navigation systems handle real-world problems like blurry images, sensor noise, and unclear instructions. The researchers found that current state-of-the-art navigation systems perform much worse when exposed to these corruptions, and they tested four strategies to make these systems more reliable. They also validated their findings on an actual robot to confirm the improvements work in practice.