11 accepted papers
Reinforcement learning (RL) has become a cornerstone for enhancing the reasoning capabilities of large language models (LLMs), with recent innovations such as Group Relative Policy Optimization (GRPO) demonstrating exceptional effectiveness. In this study, we identify a critical yet underexplored is…
Large language models have demonstrated remarkable capabilities across many tasks, yet face significant challenges when dealing with recursive reasoning problems—those requiring the resolution of nested hierarchical structures. While prior research has extensively studied length generalization (a mo
Recent video foundation models demonstrate impressive visual synthesis but frequently suffer from geometric inconsistencies. While existing methods attempt to inject 3D priors via architectural modifications, they often incur high computational costs and limit scalability. We propose World-R1, a fra…
Shared control is the most commonly used physical human-robot interaction (pHRI) in robot-assisted orthopedic surgery. However, challenges persist in tasks such as robotassisted knee arthroplasty, particularly in terms of motion delays and inadequate three-dimensional (3D) constraints. In this lette
In this letter, an active-passive fusion rehabilitation training method for the ankle fracture rehabilitation robot after surgery is developed. A subject-independent continuous estimation model of ankle torque is proposed based on surface electromyography (sEMG), an online adaptive algorithm for pas
Large language models (LLMs) enable long-context tasks but face efficiency challenges due to the growing key-value (KV) cache. We propose LeanK, a learning-based method that prunes unimportant key (K) cache channels by leveraging static channel sparsity. LeanK reduces GPU memory and accelerates deco
Deep Neural Networks (DNNs) are vulnerable to Adversarial Examples (AEs), hindering their use in safety-critical systems. In this paper, we present **BEYOND**, an innovative AE detection framework designed for reliable predictions. BEYOND identifies AEs by distinguishing the AE’s abnormal relation w…
Parallel robots have passive joints and even passive limbs. Current calibration methods seldom consider the resulted identification and compensation properties and thus accuracy improvement is affected. This letter adopts finite and instantaneous screw (FIS) theory as mathematical tool. A generalize
The performance of large language models (LLMs) is significantly influenced by the quality of the prompts provided. In response, researchers have developed enormous prompt engineering strategies aimed at modifying the prompt text to enhance task performance. In this paper, we introduce a novel techn…
Deep neural networks can model images with rich latent representations, but they cannot naturally conceptualize structures of object categories in a human-perceptible way. This paper addresses the problem of learning object structures in an image modeling process without supervision. We propose an a…
Associating image regions with text queries has been recently explored as a new way to bridge visual and linguistic representations. A few pioneering approaches have been proposed based on recurrent neural language models trained generatively (e.g., generating captions), but achieving somewhat limit…