activity
20172023
most citedOn the Dimensionality of Word Embedding

116 citations · 187 across the 6 of their papers we have counts for

collaborators

6 papers

cs.AI2023★ 7 cited

Emotional Intelligence of Large Language Models

Xuena Wang, Xueting Li, Zi Yin +2

Large Language Models (LLMs) have demonstrated remarkable abilities across numerous disciplines, primarily assessed through tasks in language generation, knowledge utilization, and…

cs.CV2020★ 2 cited

End-to-End Face Parsing via Interlinked Convolutional Neural Networks

Zi Yin, Valentin Yiu, Xiaolin Hu +1

Face parsing is an important computer vision task that requires accurate pixel segmentation of facial parts (such as eyes, nose, mouth, etc.), providing a basis for further face an…

cs.CL2018★ 14 cited

The Global Anchor Method for Quantifying Linguistic Shifts and Domain Adaptation

Zi Yin, Vin Sachidananda, Balaji Prabhakar

Language is dynamic, constantly evolving and adapting with respect to time, domain or topic. The adaptability of language is an active research area, where researchers discover soc…

cs.LG2018★ 116 cited

On the Dimensionality of Word Embedding

Zi Yin, Yuanyuan Shen

In this paper, we provide a theoretical understanding of word embedding and its dimensionality. Motivated by the unitary-invariance of word embedding, we propose the Pairwise Inner…

stat.ML2018★ 3 cited

Understand Functionality and Dimensionality of Vector Embeddings: the Distributional Hypothesis, the Pairwise Inner Product Loss and Its Bias-Variance Trade-off

Zi Yin

Vector embedding is a foundational building block of many deep learning models, especially in natural language processing. In this paper, we present a theoretical framework for und…

stat.ML2017★ 45 cited

DeepProbe: Information Directed Sequence Understanding and Chatbot Design via Recurrent Neural Networks

Zi Yin, Keng-hao Chang, Ruofei Zhang

Information extraction and user intention identification are central topics in modern query understanding and recommendation systems. In this paper, we propose DeepProbe, a generic…