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20192026
most citedA Survey of Deep Learning Techniques for Neural Machine Translation

99 citations · 141 across the 18 of their papers we have counts for

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5 papers · 1 filter

cs.DC2026

PlaneZip: Lossless Bit-Plane Compression of Training Activations Offloaded over PCIe

Zhufan Gu, Qizhe Tang, Yuxin Wang +2

Training under a device-memory budget relies on tensor rematerialization: an evicted activation is either swapped to host memory or dropped and recomputed. Because GPU compute has…

cs.DC2026

Zellige: Moldable Sequence Placement for Mixed Image-Video DiT Training

Guangyu Xiang, Xueze Kang, Minwei Zhao +4

High-quality video generation requires training Diffusion Transformers (DiTs) jointly on image and video data, posing a mixed-length sequence training problem across GPUs. Existing…

cs.DC2026

Xema: Efficient Diffusion Serving through Fine-Grained Memory Management and Auto-Configuration

Xueze Kang, Guangyu Xiang, Suyi Li +4

Diffusion models are increasingly deployed as production visual-generation services, where serving high-resolution image and long video generation is often limited by GPU memory. P…

cs.DC2026

KernelFlume: Elastic Core-Attention Scaling for Agentic Long-Context Decoding

Guangyu Xiang, Xueze Kang, Lin Zhang +4

LLM serving is increasingly dominated by long and dynamic decode workloads from agents, reasoning models, and extended conversations. When bursty long-context demand exceeds deploy…

cs.LG2026

On the Spectral Flattening of Quantized Embeddings

Junlin Huang, Wenyi Fang, Zhenheng Tang +5

Training Large Language Models (LLMs) at ultra-low precision is critically impeded by instability rooted in the conflict between discrete quantization constraints and the intrinsic…