3 citations · 9 across the 8 of their papers we have counts for
6 papers · 1 filter
InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output
Pan Zhang, Xiaoyi Dong, Yuhang Zang +24
We present InternLM-XComposer-2.5 (IXC-2.5), a versatile large-vision language model that supports long-contextual input and output. IXC-2.5 excels in various text-image comprehens…
OriGen:Enhancing RTL Code Generation with Code-to-Code Augmentation and Self-Reflection
Fan Cui, Chenyang Yin, Kexing Zhou +9
Recent studies have demonstrated the significant potential of Large Language Models (LLMs) in generating Register Transfer Level (RTL) code, with notable advancements showcased by…
SampleAttention: Near-Lossless Acceleration of Long Context LLM Inference with Adaptive Structured Sparse Attention
Qianchao Zhu, Jiangfei Duan, Chang Chen +6
Large language models (LLMs) now support extremely long context windows, but the quadratic complexity of vanilla attention results in significantly long Time-to-First-Token (TTFT)…
SKVQ: Sliding-window Key and Value Cache Quantization for Large Language Models
Haojie Duanmu, Zhihang Yuan, Xiuhong Li +3
Large language models (LLMs) can now handle longer sequences of tokens, enabling complex tasks like book understanding and generating lengthy novels. However, the key-value (KV) ca…
MuxServe: Flexible Spatial-Temporal Multiplexing for Multiple LLM Serving
Jiangfei Duan, Runyu Lu, Haojie Duanmu +5
Large language models (LLMs) have demonstrated remarkable performance, and organizations are racing to serve LLMs of varying sizes as endpoints for use-cases like chat, programming…
Parcae: Proactive, Liveput-Optimized DNN Training on Preemptible Instances
Jiangfei Duan, Ziang Song, Xupeng Miao +5
Deep neural networks (DNNs) are becoming progressively large and costly to train. This paper aims to reduce DNN training costs by leveraging preemptible instances on modern clouds,…