4 accepted papers
The current Large Language Models (LLMs) face significant challenges in improving their performance on low-resource languagesand urgently need data-efficient methods without costly fine-tuning.From the perspective of language-bridge,we propose a simple yet effective method, namely BridgeX-ICL, to im
Unsupervised bilingual lexicon induction (BLI) task aims to find word translations between languages and has achieved great success in similar language pairs. However, related works mostly rely on a single linear mapping for language alignment and fail on distant or low-resource language pairs, achi…
The functional map framework has proven to be extremely effective for representing dense correspondences between deformable shapes. A key step in this framework is to formulate suitable preservation constraints to encode the geometric information that must be preserved by the unknown map. For this i…
Establishing correspondence between shapes is a very important and active research topic in many domains. Due to the powerful ability of deep learning on geometric data, lots of attractive results have been achieved by convolutional neural networks (CNNs). In this paper, we propose a novel architect…