4 papers
DenseGrounding: Improving Dense Language-Vision Semantics for Ego-Centric 3D Visual Grounding
Henry Zheng, Hao Shi, Qihang Peng +5
Enabling intelligent agents to comprehend and interact with 3D environments through natural language is crucial for advancing robotics and human-computer interaction. A fundamental…
Traversal Verification for Speculative Tree Decoding
Yepeng Weng, Qiao Hu, Xujie Chen +5
Speculative decoding is a promising approach for accelerating large language models. The primary idea is to use a lightweight draft model to speculate the output of the target mode…
CORAL: Learning Consistent Representations across Multi-step Training with Lighter Speculative Drafter
Yepeng Weng, Dianwen Mei, Huishi Qiu +4
Speculative decoding is a powerful technique that accelerates Large Language Model (LLM) inference by leveraging a lightweight speculative draft model. However, existing designs su…
ARB-LLM: Alternating Refined Binarizations for Large Language Models
Zhiteng Li, Xianglong Yan, Tianao Zhang +7
Large Language Models (LLMs) have greatly pushed forward advancements in natural language processing, yet their high memory and computational demands hinder practical deployment. B…