Guoyin Wang

Glyce: Glyph-vectors for Chinese Character Representations

2019 · arXiv (Cornell University)

It is intuitive that NLP tasks for logographic languages like Chinese should benefit from the use of the glyph information in those languages. However, due to the lack of rich pictographic evidence in glyphs and …

GPT-NER: Named Entity Recognition via Large Language Models

2023 · arXiv (Cornell University)

Despite the fact that large-scale Language Models (LLM) have achieved SOTA performances on a variety of NLP tasks, its performance on NER is still significantly below supervised baselines. This is due to the gap between …

Pushing the Limits of ChatGPT on NLP Tasks

2023 · arXiv (Cornell University)

Despite the success of ChatGPT, its performances on most NLP tasks are still well below the supervised baselines. In this work, we looked into the causes, and discovered that its subpar performance was caused by …

Ranking-Enhanced Unsupervised Sentence Representation Learning

2023

Yeon Seonwoo, Guoyin Wang, Changmin Seo, Sajal Choudhary, Jiwei Li, Xiang Li, Puyang Xu, Sunghyun Park, Alice Oh. Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2023.

A Fast Granular-Ball-Based Density Peaks Clustering Algorithm for Large-Scale Data

2023 · IEEE Transactions on Neural Networks and Learning Systems

Density peaks clustering algorithm (DP) has difficulty in clustering large-scale data, because it requires the distance matrix to compute the density and -distance for each object, which has time complexity. Granular ball (GB) is a …

Are Human-generated Demonstrations Necessary for In-context Learning?

2023 · arXiv (Cornell University)

Despite the promising few-shot ability of large language models (LLMs), the standard paradigm of In-context Learning (ICL) suffers the disadvantages of susceptibility to selected demonstrations and the intricacy to generate these demonstrations. In this paper, …

A Cross-Domain Recommendation Model Based on Asymmetric Vertical Federated Learning and Heterogeneous Representation

2025 · IEEE Transactions on Emerging Topics in Computational Intelligence

Cross-domain recommendation meets the personalized needs of users by integrating user preference features from different fields. However, the current cross-domain recommendation algorithm needs to be further strengthened in terms of privacy protection. This paper proposes …

A Multi-Granularity Fireworks Algorithm with Collaboration and Competition for Solving the Influence Maximization Problem

2025

The Influence Maximization (IM) problem in social networks has been extensively studied, with greedy algorithms providing accurate and reliable solutions. However, their high computational cost renders them impractical for large-scale networks. Conversely, structure-based heuristic methods …

Knowledge Sharing Enhanced Clustered Federated Learning for Heterogeneous Client Data

2025 · IEEE Internet of Things Journal

Clustered Federated Learning (CFL) is a machine learning paradigm that balances local and global training to address limited local data and reduce the negative effects of data heterogeneity on the global model. However, data heterogeneity …

Joint Embedding of Words and Labels for Text Classification

2018

Guoyin Wang, Chunyuan Li, Wenlin Wang, Yizhe Zhang, Dinghan Shen, Xinyuan Zhang, Ricardo Henao, Lawrence Carin. Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2018.

Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms

2018

Dinghan Shen, Guoyin Wang, Wenlin Wang, Martin Renqiang Min, Qinliang Su, Yizhe Zhang, Chunyuan Li, Ricardo Henao, Lawrence Carin. Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). …