VLAs combine pretrained vision-language representations with action generation to enable language-guided control across diverse tasks, becoming a mainstream paradigm in embodied intelligence. However, multiple studies have reported VLA's substantial declines in task success under camera shifts, revealing a key vulnerab...
Tian-Hang Pan, Xuan Wang, Yi-Wen Pang et al.· 0 citations
TokenCast is proposed, which learns a composable cost representation for each execution segment, recording its own consumption and the context growth it introduces, and captures the extra input cost incurred when context from earlier segments is re-read by every later call.
Chao-Qian Ouyang, Ling Yue, Li-Bin Zheng et al.· 0 citations
This work proposes a novel framework, Multi-Path Causal Optimization (MuPlon), which combines a dual causal intervention strategy, consisting of the back-door path and front-door path, and demonstrates that MuPlon outperforms existing methods and achieves state-of-the-art performance.
Hanghui Guo, Shi-Min Di, P. D. Meo et al.· arXiv.org· 0 citations
A new harness self-evolution method, named DREvo, is proposed, which integrates function-level evidence anchoring, state-dependent evidence recalibration, and role-conditioned search intent distillation to determine which historical evidence remains valid and where the harness should evolve next.
This work proposes Urban-Agent, a tool-augmented agent framework for cross-system urban tasks that couples the cognitive and reasoning capabilities of a large language model with a tool-set supporting code execution, API calls, and Model Context Protocol.
Jiayu Cao, Xing-Yuan Zeng, Fei-Yue Li et al.· 0 citations
SafeIMG is introduced, a safety-oriented benchmark spanning 12 public- and individual-safety scenarios generated using GPT Image 2.0 that provides human annotations that localise suspicious regions and explain local artefacts and higher-level commonsense or physical inconsistencies.
Yizhi Wang, Yichen Xiao, Linan Yue et al.· 0 citations
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