1 citations · 2 across the 8 of their papers we have counts for
12 papers
HySparse: A Hybrid Sparse Attention Architecture with Oracle Token Selection and KV Cache Sharing
Yizhao Gao, Jianyu Wei, Qihao Zhang +11
This work introduces Hybrid Sparse Attention (HySparse), a new architecture that interleaves each full attention layer with several sparse attention layers. While conceptually simp…
Emerging from Ground: Addressing Intent Deviation in Tool-Using Agents via Deriving Real Calls into Virtual Trajectories
Qian Xiong, Yuekai Huang, Bo Yang +7
LLMs have advanced tool-using agents for real-world applications, yet they often lead to unexpected behaviors or results. Beyond obvious failures, the subtle issue of "intent devia…
MiMo-V2-Flash Technical Report
Core Team, Bangjun Xiao, Bingquan Xia +123
We present MiMo-V2-Flash, a Mixture-of-Experts (MoE) model with 309B total parameters and 15B active parameters, designed for fast, strong reasoning and agentic capabilities. MiMo-…
Hybrid Quantum-Classical Neural Networks for Few-Shot Credit Risk Assessment
Zheng-an Wang, Yanbo J. Wang, Jiachi Zhang +11
Quantum Machine Learning (QML) offers a new paradigm for addressing complex financial problems intractable for classical methods. This work specifically tackles the challenge of fe…
SIS-Challenge: Event-based Spatio-temporal Instance Segmentation Challenge at the CVPR 2025 Event-based Vision Workshop
Friedhelm Hamann, Emil Mededovic, Fabian Gülhan +21
We present an overview of the Spatio-temporal Instance Segmentation (SIS) challenge held in conjunction with the CVPR 2025 Event-based Vision Workshop. The task is to predict accur…
MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention
MiniMax, :, Aili Chen +125
We introduce MiniMax-M1, the world's first open-weight, large-scale hybrid-attention reasoning model. MiniMax-M1 is powered by a hybrid Mixture-of-Experts (MoE) architecture combin…