1 citations · 4 across the 18 of their papers we have counts for
19 papers
HySparse2: Hybrid Sparse Attention with Two-Level KV Sharing
Jianyu Wei, Yizhao Gao, Qihao Zhang +12
Long-horizon and multi-turn agents typically generate short actions and process long observations from tools and environments. This growing context demands efficient prefill, compa…
HAM-RAG: Hierarchy-Aware Multimodal RAG for Structure-Faithful Interleaved Generation
Yin Li, Ziyang Hu, Zhiyu Guo +7
Existing multimodal RAG methods often flatten structured documents into isolated text and image units, weakening the source organization and local text-image logic needed for faith…
402Pilot: An x402 Decision Layer for Autonomous Agent Micropayments
Yin Li, Yanbo He, Boo-Ho Yang +5
Programmable-payment protocols such as x402 enable per-request micropayments, but they do not determine which payable service an autonomous agent should buy under a finite wallet.…
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…
Beyond VLM-Based Rewards: Diffusion-Native Latent Reward Modeling
Gongye Liu, Bo Yang, Yida Zhi +8
Preference optimization for diffusion and flow-matching models relies on reward functions that are both discriminatively robust and computationally efficient. Vision-Language Model…
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…
ContestTrade: A Multi-Agent Trading System Based on Internal Contest Mechanism
Li Zhao, Rui Sun, Zuoyou Jiang +5
In financial trading, large language model (LLM)-based agents demonstrate significant potential, but their decisions can be sensitive to noisy and non-stationary market information…
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…
Hybrid Real- and Complex-valued Neural Network Architecture
Alex Young, Luan Vinícius Fiorio, Bo Yang +3
We propose a \emph{hybrid} real- and complex-valued \emph{neural network} (HNN) architecture, designed to combine the computational efficiency of real-valued processing with the ab…
CE-U: Cross Entropy Unlearning
Bo Yang
Large language models memorize sensitive data from their pretraining corpora. In this work, we propose CE-U (Cross Entropy Unlearning), a loss function for unlearning. CE-U address…
SwiLTra-Bench: The Swiss Legal Translation Benchmark
Joel Niklaus, Jakob Merane, Luka Nenadic +16
In Switzerland legal translation is uniquely important due to the country's four official languages and requirements for multilingual legal documentation. However, this process tra…
Exploring the Impact of Temperature Scaling in Softmax for Classification and Adversarial Robustness
Hao Xuan, Bokai Yang, Xingyu Li
The softmax function is a fundamental component in deep learning. This study delves into the often-overlooked parameter within the softmax function, known as "temperature," providi…
MiniMax-01: Scaling Foundation Models with Lightning Attention
MiniMax, Aonian Li, Bangwei Gong +87
We introduce MiniMax-01 series, including MiniMax-Text-01 and MiniMax-VL-01, which are comparable to top-tier models while offering superior capabilities in processing longer conte…
Predictable Emergent Abilities of LLMs: Proxy Tasks Are All You Need
Bo-Wen Zhang, Yan Yan, Boxiang Yang +2
While scaling laws optimize training configurations for large language models (LLMs) through experiments on smaller or early-stage models, they fail to predict emergent abilities d…
MCCoder: Streamlining Motion Control with LLM-Assisted Code Generation and Rigorous Verification
Yin Li, Liangwei Wang, Shiyuan Piao +4
Large Language Models (LLMs) have demonstrated significant potential in code generation. However, in the factory automation sector, particularly motion control, manual programming,…
Fine-Grained Prototypes Distillation for Few-Shot Object Detection
Zichen Wang, Bo Yang, Haonan Yue +1
Few-shot object detection (FSOD) aims at extending a generic detector for novel object detection with only a few training examples. It attracts great concerns recently due to the p…