3 papers
cs.LG2026
CateKV: On Sequential Consistency for Long-Context LLM Inference Acceleration
Haoyun Jiang, Haolin Li, Jianwei Zhang +7
Large language models (LLMs) have demonstrated strong capabilities in handling long-context tasks, but processing such long contexts remains challenging due to the substantial memo…
cs.LG2026
Breaking Entropy Bounds: Accelerating RL Training via MTP with Rejection Sampling
Yucheng Li, Huiqiang Jiang, Yang Xu +14
Reinforcement learning (RL) has become a key component in modern large language models, yet the rollout stage remains the key bottleneck in RL training pipelines. Although Multi-To…
cs.AI2026
Overcoming Joint Intractability with Lossless Hierarchical Speculative Decoding
Yuxuan Zhou, Fei Huang, Heng Li +5
Verification is a key bottleneck in improving inference speed while maintaining distribution fidelity in Speculative Decoding. Recent work has shown that sequence-level verificatio…