arXiv:2605.08084v1 Announce Type: new
Abstract: The pursuit of autonomous driving has produced one of the richest sensor data collections in all of robotics. However, its scale and diversity remain largely untapped. Each dataset adopts different 2D an…
arXiv:2604.19697v2 Announce Type: replace
Abstract: Multimodal large language models (MLLMs) have shown promising reasoning abilities, yet evaluating their performance in specialized domains remains challenging. STEM reasoning is a particularly valuab…
arXiv:2605.07053v1 Announce Type: new
Abstract: Benchmarks like GSM8K are popular measures of mathematical reasoning, but leaderboard gains can overstate true capability due to memorization of fixed test sets. Most robustness variants apply surface-le…
arXiv:2605.07346v1 Announce Type: new
Abstract: Free-Viewpoint Video (FVV) has emerged as a cornerstone of next-generation immersive media systems and attracted widespread attention. Previous methods primarily focus on short video sequences and suffer…
arXiv:2605.07039v1 Announce Type: new
Abstract: Large language models have become drivers of evolutionary search, but most systems rely on a fixed, prompt-elicited policy to sample next candidates. This limits adaptation in practical engineering and r…
arXiv:2604.16579v2 Announce Type: replace-cross
Abstract: Automated multimodal depression estimation in unconstrained environments is inherently challenged by naturalistic noise and complex behavioral variability. Prevailing deterministic methods, how…
arXiv:2604.26509v3 Announce Type: replace
Abstract: Embodied AI and robotic systems increasingly depend on scalable, diverse, and physically grounded 3D content for simulation-based training and real-world deployment. While 3D generative modeling has …
arXiv:2605.06820v1 Announce Type: cross
Abstract: Deep learning-based organs/structures-at-risk(OARs) auto-contouring models can improve radiotherapy workflows, but models trained on adult data often underperform in pediatric patients. Developing robu…
arXiv:2603.06859v2 Announce Type: replace-cross
Abstract: Removing an agent from a cooperative team to measure its contribution seems natural, yet in multi-agent LLM systems this evaluation distorts the result it claims to measure. This failure is not…
arXiv:2605.02881v2 Announce Type: replace
Abstract: Vision-Language-Action (VLA) models aim to provide a single generalist controller for robots, but today’s systems fall short on the criteria that matter for real-world deployment. Frontier models are…