13 citations · 15 across the 8 of their papers we have counts for
10 papers
Has GPT-6-Astra Achieved Embodied Intelligence?
SenseNova, Joint Research Team, : +60
GPT-6-Astra demonstrates a level of competence in robotic manipulation and navigation that challenges the conventional paradigm of building specialized models for individual tasks…
SignDPO: Multi-level Direct Preference Optimisation for Skeleton-based Gloss-free Sign Language Translation
Muxin Pu, Xiao-Ming Wu, Mei Kuan Lim +3
We present SignDPO, a novel multi-level Direct Preference Optimisation (DPO) framework designed to enhance the alignment of skeleton-based Sign Language Translation. While current…
FileGram: Grounding Agent Personalization in File-System Behavioral Traces
Shuai Liu, Shulin Tian, Kairui Hu +6
Coworking AI agents operating within local file systems are rapidly emerging as a paradigm in human-AI interaction; however, effective personalization remains limited by severe dat…
HippoCamp: Benchmarking Contextual Agents on Personal Computers
Zhe Yang, Shulin Tian, Kairui Hu +9
We present HippoCamp, a new benchmark designed to evaluate agents' capabilities on multimodal file management. Unlike existing agent benchmarks that focus on tasks like web interac…
LA-Sign: Looped Transformers with Geometry-aware Alignment for Skeleton-based Sign Language Recognition
Muxin Pu, Mei Kuan Lim, Chun Yong Chong +1
Skeleton-based isolated sign language recognition (ISLR) demands fine-grained understanding of articulated motion across multiple spatial scales, from subtle finger movements to gl…
VLANeXt Family: A Systematic Study of VLA Models from Core Recipes to Emerging Paradigms
Xiao-Ming Wu, Bin Fan, Kang Liao +6
Following the rise of large foundation models, Vision-Language-Action models (VLAs) emerged, leveraging strong visual and language understanding from Vision-Language Models for gen…
MeViS: A Multi-Modal Dataset for Referring Motion Expression Video Segmentation
Henghui Ding, Chang Liu, Shuting He +4
This paper proposes a large-scale multi-modal dataset for referring motion expression video segmentation, focusing on segmenting and tracking target objects in videos based on lang…
Light-SQ: Structure-aware Shape Abstraction with Superquadrics for Generated Meshes
Yuhan Wang, Weikai Chen, Zeyu Hu +19
In user-generated-content (UGC) applications, non-expert users often rely on image-to-3D generative models to create 3D assets. In this context, primitive-based shape abstraction o…
MARS2 2025 Challenge on Multimodal Reasoning: Datasets, Methods, Results, Discussion, and Outlook
Peng Xu, Shengwu Xiong, Jiajun Zhang +125
This paper reviews the MARS2 2025 Challenge on Multimodal Reasoning. We aim to bring together different approaches in multimodal machine learning and LLMs via a large benchmark. We…
Sigma: Semantically Informative Pre-training for Skeleton-based Sign Language Understanding
Muxin Pu, Mei Kuan Lim, Chun Yong Chong +1
Pre-training has proven effective for learning transferable features in sign language understanding (SLU) tasks. Recently, skeleton-based methods have gained increasing attention b…