163 citations · 720 across the 32 of their papers we have counts for
11 papers · 1 filter
Fewer is More: Boosting LLM Reasoning with Reinforced Context Pruning
Xijie Huang, Li Lyna Zhang, Kwang-Ting Cheng +2
Large Language Models (LLMs) have shown impressive capabilities, yet they still struggle with math reasoning. In this work, we propose CoT-Influx, a novel approach that pushes the…
Tessel: Boosting Distributed Execution of Large DNN Models via Flexible Schedule Search
Zhiqi Lin, Youshan Miao, Guanbin Xu +4
Increasingly complex and diverse deep neural network (DNN) models necessitate distributing the execution across multiple devices for training and inference tasks, and also require…
Model-enhanced Vector Index
Hailin Zhang, Yujing Wang, Qi Chen +16
Embedding-based retrieval methods construct vector indices to search for document representations that are most similar to the query representations. They are widely used in docume…
Adam Accumulation to Reduce Memory Footprints of both Activations and Gradients for Large-scale DNN Training
Yijia Zhang, Yibo Han, Shijie Cao +5
Running out of GPU memory has become a main bottleneck for large-scale DNN training. How to reduce the memory footprint during training has received intensive research attention. W…
Integer or Floating Point? New Outlooks for Low-Bit Quantization on Large Language Models
Yijia Zhang, Lingran Zhao, Shijie Cao +6
Efficient deployment of large language models (LLMs) necessitates low-bit quantization to minimize model size and inference cost. While low-bit integer formats (e.g., INT8/INT4) ha…
OliVe: Accelerating Large Language Models via Hardware-friendly Outlier-Victim Pair Quantization
Cong Guo, Jiaming Tang, Weiming Hu +6
Transformer-based large language models (LLMs) have achieved great success with the growing model size. LLMs' size grows by every two years, which outpaces the hardware…
NUWA-XL: Diffusion over Diffusion for eXtremely Long Video Generation
Shengming Yin, Chenfei Wu, Huan Yang +13
In this paper, we propose NUWA-XL, a novel Diffusion over Diffusion architecture for eXtremely Long video generation. Most current work generates long videos segment by segment seq…
IRGen: Generative Modeling for Image Retrieval
Yidan Zhang, Ting Zhang, Dong Chen +11
While generative modeling has become prevalent across numerous research fields, its integration into the realm of image retrieval remains largely unexplored and underjustified. In…
Learning 3D Photography Videos via Self-supervised Diffusion on Single Images
Xiaodong Wang, Chenfei Wu, Shengming Yin +9
3D photography renders a static image into a video with appealing 3D visual effects. Existing approaches typically first conduct monocular depth estimation, then render the input f…
SuperScaler: Supporting Flexible DNN Parallelization via a Unified Abstraction
Zhiqi Lin, Youshan Miao, Guodong Liu +10
With the growing model size, deep neural networks (DNN) are increasingly trained over massive GPU accelerators, which demands a proper parallelization plan that transforms a DNN mo…
PIT: Optimization of Dynamic Sparse Deep Learning Models via Permutation Invariant Transformation
Ningxin Zheng, Huiqiang Jiang, Quanlu Zhang +8
Dynamic sparsity, where the sparsity patterns are unknown until runtime, poses a significant challenge to deep learning. The state-of-the-art sparsity-aware deep learning solutions…