14 accepted papers
Vision-language-action models (VLAs) use an end-to-end learning architecture, which can realize the integration of visual perception, semantic understanding and motion control. However, when tackling with the dynamic or long-horizon tasks, VLAs have poor robustness and real-time adjustment ability a
Large language models, constrained by the fixed-depth Transformer architecture, struggle to solve complex reasoning tasks in an end-to-end manner. Existing approaches, such as Chain of Thought, improve reasoning depth to some extent but rely heavily on natural language generation, with computational…
Cross-modal alignment aims to learn semantically consistent latent representations across diverse modalities. Prevailing methods rely on a text-guided aggregation paradigm to achieve fine-grained alignment, while they suffer from redundant patch-word correlations and high computational costs. To add
Vision-Language-Action (VLA) models have recently achieved remarkable progress in robotic manipulation, yet they remain limited in failure diagnosis and learning from failures. Additionally, existing failure datasets are mostly generated programmatically in simulation, which limits their generalizat
Large Language Models (LLMs) based agent systems have made great strides in real-world applications beyond traditional NLP tasks. This paper proposes a new LLM-based Multi-Agent System (LLM-MAS) benchmark, Collab-Overcooked, built on the popular Overcooked-AI game with more applicable and challengin
Powered knee prostheses promise to improve the mobility of transfemoral amputees by imitating the biomechanics of the missing knee joint. Unfortunately, the heavy weight and short battery life severely limit the application of powered prostheses. Here, we present a lightweight powered knee prosthesi
In this letter, a novel tendon-driven actuator is presented for anthropomimetic robots, mimicking the functionality of a spindle muscle. This actuator can contract and relax, and its tension output can be measured and controlled. The proposed actuator features an innovative space-saving co-axial win
This letter presents the design and development of a novel compact motor-based non-linear stiffness soft actuator used for tendon-driven joints, i.e. a magnet-integrated soft actuator (MISA). By applying a pair of antagonistic MISAs to a joint, it is capable of achieving joint stiffness adjustment a
Tuning body stiffness like fish to improve swimming efficiency and speed has been adopted by many fish-inspired robotics. However, it is unknown whether the energy saved from improved efficiency can compensate for the energy consumption brought by tuning stiffness itself. To explore this issue, we d
A hybrid knee prosthesis is proposed in this letter, which consists of a polycentric structure in passive mode for low-torque activities and a single-axis structure in active mode for high-torque activities. A novel mode transition mechanism controls self-holding electromagnets for switching modes b
Prompt-tuning has shown appealing performance in few-shot classification by virtue of its capability in effectively exploiting pre-trained knowledge. This motivates us to check the hypothesis that prompt-tuning is also a promising choice for long-tailed classification, since the tail classes are int…
Structural bias has recently been exploited for aspect sentiment triplet extraction (ASTE) and led to improved performance. On the other hand, it is recognized that explicitly incorporating structural bias would have a negative impact on efficiency, whereas pretrained language models (PLMs) can alre…
Prompt tuning learns soft prompts to condition the frozen Pre-trained Language Models (PLMs) for performing downstream tasks in a parameter-efficient manner. While prompt tuning has gradually reached the performance level of fine-tuning as the model scale increases, there is still a large performanc…
Sentiment analysis has attracted increasing attention in e-commerce. The sentiment polarities underlying user reviews are of great value for business intelligence. Aspect category sentiment analysis (ACSA) and review rating prediction (RP) are two essential tasks to detect the fine-to-coarse sentime…