16 citations · 40 across the 9 of their papers we have counts for
9 papers
MiniMax Sparse Attention
Xunhao Lai, Weiqi Xu, Yufeng Yang +14
Ultra-long-context capability is becoming indispensable for frontier LLMs: agentic workflows, repository-scale code reasoning, and persistent memory all require the model to jointl…
The MiniMax-M2 Series: Mini Activations Unleashing Max Real-World Intelligence
Aili Chen, Aonian Li, Baichuan Zhou +215
We introduce the MiniMax-M2 series, a family of Mixture-of-Experts language models built around the principle that mini activations can unleash maximum real-world intelligence. The…
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…
SmartTrim: Adaptive Tokens and Attention Pruning for Efficient Vision-Language Models
Zekun Wang, Jingchang Chen, Wangchunshu Zhou +7
Despite achieving remarkable performance on various vision-language tasks, Transformer-based Vision-Language Models (VLMs) suffer from redundancy in inputs and parameters, signific…
Learning to Tokenize for Generative Retrieval
Weiwei Sun, Lingyong Yan, Zheng Chen +7
Conventional document retrieval techniques are mainly based on the index-retrieve paradigm. It is challenging to optimize pipelines based on this paradigm in an end-to-end manner.…
Distilled Dual-Encoder Model for Vision-Language Understanding
Zekun Wang, Wenhui Wang, Haichao Zhu +3
We propose a cross-modal attention distillation framework to train a dual-encoder model for vision-language understanding tasks, such as visual reasoning and visual question answer…
HandAugment: A Simple Data Augmentation Method for Depth-Based 3D Hand Pose Estimation
Zhaohui Zhang, Shipeng Xie, Mingxiu Chen +1
Hand pose estimation from 3D depth images, has been explored widely using various kinds of techniques in the field of computer vision. Though, deep learning based method improve th…
Transforming Wikipedia into Augmented Data for Query-Focused Summarization
Haichao Zhu, Li Dong, Furu Wei +2
The limited size of existing query-focused summarization datasets renders training data-driven summarization models challenging. Meanwhile, the manual construction of a query-focus…
Learning to Ask Unanswerable Questions for Machine Reading Comprehension
Haichao Zhu, Li Dong, Furu Wei +3
Machine reading comprehension with unanswerable questions is a challenging task. In this work, we propose a data augmentation technique by automatically generating relevant unanswe…