3 citations · 8 across the 9 of their papers we have counts for
10 papers
Factorization-Guided Training and Inference for Diffusion-Drafted Speculative Decoding
Jiakun Fan, Min Xiao, Qiang Wang +5
Speculative decoding accelerates large language model inference through parallel verification of tokens proposed by a drafter. Diffusion drafters further parallelize proposal gener…
QALM: Escaping Local Minima via Interleaved Exploration and Exploitation in Quantum Circuit Optimization
Aidan Wagner, Mingkuan Xu, Pengyu Liu +2
Quantum circuit optimizers face a fundamental limitation in how they tolerate temporary cost increases. At one extreme, greedy rule-based optimizers immediately apply any cost-redu…
Vortex: Efficient and Programmable Sparse Attention Serving for AI Agents
Zhuoming Chen, Xinrui Zhong, Qilong Feng +5
Sparse attention is becoming increasingly important for serving large language models (LLMs) as generation lengths continue to grow. However, deploying and evaluating new sparse at…
Event Tensor: A Unified Abstraction for Compiling Dynamic Megakernel
Hongyi Jin, Bohan Hou, Guanjie Wang +18
Modern GPU workloads, especially large language model (LLM) inference, suffer from kernel launch overheads and coarse synchronization that limit inter-kernel parallelism. Recent me…
Prism: Symbolic Superoptimization of Tensor Programs
Mengdi Wu, Xiaoyu Jiang, Oded Padon +1
This paper presents Prism, the first symbolic superoptimizer for tensor programs. The key idea is sGraph, a symbolic, hierarchical representation that compactly encodes large class…
CAT Pruning: Cluster-Aware Token Pruning For Text-to-Image Diffusion Models
Xinle Cheng, Zhuoming Chen, Zhihao Jia
Diffusion models have revolutionized generative tasks, especially in the domain of text-to-image synthesis; however, their iterative denoising process demands substantial computati…
AdaServe: Accelerating Multi-SLO LLM Serving with SLO-Customized Speculative Decoding
Zikun Li, Zhuofu Chen, Remi Delacourt +11
Modern large language model (LLM) applications exhibit diverse service-level objectives (SLOs), from low-latency requirements in interactive coding assistants to more relaxed const…
MagicPIG: LSH Sampling for Efficient LLM Generation
Zhuoming Chen, Ranajoy Sadhukhan, Zihao Ye +8
Large language models (LLMs) with long context windows have gained significant attention. However, the KV cache, stored to avoid re-computation, becomes a bottleneck. Various dynam…
SpecExec: Massively Parallel Speculative Decoding for Interactive LLM Inference on Consumer Devices
Ruslan Svirschevski, Avner May, Zhuoming Chen +3
As large language models gain widespread adoption, running them efficiently becomes crucial. Recent works on LLM inference use speculative decoding to achieve extreme speedups. How…
Sequoia: Scalable, Robust, and Hardware-aware Speculative Decoding
Zhuoming Chen, Avner May, Ruslan Svirschevski +4
As the usage of large language models (LLMs) grows, performing efficient inference with these models becomes increasingly important. While speculative decoding has recently emerged…