4 papers · 1 filter
TreeGraft: Adaptive Multi-Drafter Grafting for Tree-Based Speculative Decoding
Jiaming Fan, Daming Cao, Canchen Huang +6
Speculative decoding accelerates large language model inference through a draft-then-verify paradigm. Building on this, tree-structured methods improve inference by organizing prop…
SearchOS-V1: Towards Robust Open-Domain Information-Seeking Agent Collaboration
Yuyao Zhang, Junjie Gao, Zhengxian Wu +11
Recent advances in Tool-Integrated Large Language Models have made web search a core capability of information-seeking agents. However, as interaction histories grow, agents increa…
RedVLA: Physical Red Teaming for Vision-Language-Action Models
Yuhao Zhang, Borong Zhang, Jiaming Fan +4
The real-world deployment of Vision-Language-Action (VLA) models remains limited by the risk of unpredictable and irreversible physical harm. However, we currently lack effective m…
Flatter Tokens are More Valuable for Speculative Draft Model Training
Jiaming Fan, Daming Cao, Xiangzhong Luo +3
Speculative Decoding (SD) is a key technique for accelerating Large Language Model (LLM) inference, but it typically requires training a draft model on a large dataset. We approach…