46 citations · 90 across the 9 of their papers we have counts for
9 papers
Mechanism-Aligned Observability for Training Instability of Large Language Models
Ruixuan Huang, Yipei Wang, Hantao Huang +7
Frontier large language model training consumes massive accelerator fleets over long wall-clock times, making stability failures extremely costly. However, global symptoms such as…
AsyncHZP: Hierarchical ZeRO Parallelism with Asynchronous Scheduling for Scalable LLM Training
Huawei Bai, Yifan Huang, Wenqi Shi +4
The training efficiency and scalability of language models on massive clusters currently remain a critical bottleneck. Mainstream approaches like ND parallelism are often cumbersom…
AsyncFlow: An Asynchronous Streaming RL Framework for Efficient LLM Post-Training
Zhenyu Han, Ansheng You, Haibo Wang +16
Reinforcement learning (RL) has become a pivotal technology in the post-training phase of large language models (LLMs). Traditional task-collocated RL frameworks suffer from signif…
Towards Controllable and Photorealistic Region-wise Image Manipulation
Ansheng You, Chenglin Zhou, Qixuan Zhang +1
Adaptive and flexible image editing is a desirable function of modern generative models. In this work, we present a generative model with auto-encoder architecture for per-region s…
Towards Efficient Scene Understanding via Squeeze Reasoning
Xiangtai Li, Xia Li, Ansheng You +5
Graph-based convolutional model such as non-local block has shown to be effective for strengthening the context modeling ability in convolutional neural networks (CNNs). However, i…
Semantically Multi-modal Image Synthesis
Zhen Zhu, Zhiliang Xu, Ansheng You +1
In this paper, we focus on semantically multi-modal image synthesis (SMIS) task, namely, generating multi-modal images at the semantic level. Previous work seeks to use multiple cl…
Semantic Flow for Fast and Accurate Scene Parsing
Xiangtai Li, Ansheng You, Zhen Zhu +4
In this paper, we focus on designing effective method for fast and accurate scene parsing. A common practice to improve the performance is to attain high resolution feature maps wi…
Global Aggregation then Local Distribution in Fully Convolutional Networks
Xiangtai Li, Li Zhang, Ansheng You +3
It has been widely proven that modelling long-range dependencies in fully convolutional networks (FCNs) via global aggregation modules is critical for complex scene understanding t…
Reprojection R-CNN: A Fast and Accurate Object Detector for 360° Images
Pengyu Zhao, Ansheng You, Yuanxing Zhang +3
360° images are usually represented in either equirectangular projection (ERP) or multiple perspective projections. Different from the flat 2D images, the detection task is challen…