collaborators

21 papers

cs.DC2026

AFD-Ledger: Deployment Provisioning for Attention--FFN Disaggregation

Chengyu Qiu, Xiao Fu, Fengcun Li +6

Attention--Feed-Forward Network (FFN) Disaggregation (AFD) is emerging as a promising architecture for serving Mixture-of-Experts (MoE) language models. While existing AFD systems…

cs.AI2026

LongCat Sparse Attention: Taming the Lightning via Streaming-aware Hierarchical Cross-Layer Indexing

Wen Zan, Jiaqi Zhang, Jianchao Tan +11

DeepSeek Sparse Attention (DSA) enables efficient long-context modeling through its Lightning Indexer. However, practical deployment remains constrained by the indexer's expensive…

cs.LG2026

SCOPE: Signal-Calibrated On-Policy Distillation Enhancement with Dual-Path Adaptive Weighting

Binbin Zheng, Xing Ma, Yiheng Liang +6

On-policy reinforcement learning has become the dominant paradigm for reasoning alignment in large language models, yet its sparse, outcome-level rewards make token-level credit as…

cs.LG2026

FG-GDN: Enhancing Long-Context Gated Delta Networks with Doubly Fine-Grained Control

Pingwei Sun, Yuxuan Hu, Jianchao Tan +6

Linear attention mechanisms have emerged as promising alternatives to softmax attention, offering linear-time complexity during inference. Recent advances such as Gated DeltaNet (G…

cs.LG2026

SnapMLA: Efficient Long-Context MLA Decoding via Hardware-Aware FP8 Quantized Pipelining

Yifan Zhang, Zunhai Su, Shuhao Hu +5

While FP8 attention has shown substantial promise in innovations like FlashAttention-3, its integration into the decoding phase of the DeepSeek Multi-head Latent Attention (MLA) ar…

cs.LG2026

SparseBalance: Load-Balanced Long Context Training with Dynamic Sparse Attention

Hongtao Xu, Jianchao Tan, Yuxuan Hu +8

While sparse attention mitigates the computational bottleneck of long-context LLM training, its distributed training process exhibits extreme heterogeneity in both \textit{1)} sequ…