Search Results for author:
Found 3 papers, 0 papers with code
TGP: Two-modal occupancy prediction with 3D Gaussian and sparse points for 3D Environment Awareness
To address this issue, we propose a dual-modal prediction method based on 3D Gaussian sets and sparse points, which balances both spatial location and volumetric structural information, achieving higher accuracy in semantic occupancy prediction.
APrompt4EM: Augmented Prompt Tuning for Generalized Entity Matching
The first is an augmented contextualized soft token-based prompt tuning method that extracts a guiding soft token benefit for the PLMs' prompt tuning, and the second is a cost-effective information augmentation strategy leveraging large language models (LLMs).
An Empirical Study of NetOps Capability of Pre-Trained Large Language Models
Nowadays, the versatile capabilities of Pre-trained Large Language Models (LLMs) have attracted much attention from the industry.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
