9 papers
SA-VLA: State-aware tokenizer for improving Vision-Language-Action Models' performance
Tengyue Jiang, Chunpu Xu, Jiayue Kang +1
Discrete action tokenization provides a compact interface for autoregressive VLA policies, but accurately recovering continuous robot actions from discrete codes remains challengin…
Probing Cultural Awareness in LLMs: A Case Study of Cross-Culture Aesthetic Stylistics
Jiashuo Wang, Fenggang Yu, Jian Wang +6
Large Language Models (LLMs) are increasingly deployed in diverse cultural contexts, yet their ability to master aesthetic stylistics, i.e., the strategic use of language to evoke…
HiVLA: A Visual-Grounded-Centric Hierarchical Embodied Manipulation System
Tianshuo Yang, Guanyu Chen, Yutian Chen +8
While end-to-end Vision-Language-Action (VLA) models offer a promising paradigm for robotic manipulation, fine-tuning them on narrow control data often compromises the profound rea…
Foresight Optimization for Strategic Reasoning in Large Language Models
Jiashuo Wang, Jiawen Duan, Jian Wang +6
Reasoning capabilities in large language models (LLMs) have generally advanced significantly. However, it is still challenging for existing reasoning-based LLMs to perform effectiv…
SCALE: Selective Resource Allocation for Overcoming Performance Bottlenecks in Mathematical Test-time Scaling
Yang Xiao, Chunpu Xu, Ruifeng Yuan +3
Test-time compute scaling has emerged as a powerful paradigm for enhancing mathematical reasoning in large language models (LLMs) by allocating additional computational resources d…
LIMOPro: Reasoning Refinement for Efficient and Effective Test-time Scaling
Yang Xiao, Jiashuo Wang, Ruifeng Yuan +4
Large language models (LLMs) have demonstrated remarkable reasoning capabilities through test-time scaling approaches, particularly when fine-tuned with chain-of-thought (CoT) data…