activity
20222024
most citedC-ICL: Contrastive In-context Learning for Information Extraction

1 citations · 4 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL2024

Towards Real-world Scenario: Imbalanced New Intent Discovery

Shun Zhang, Chaoran Yan, Jian Yang +5

New Intent Discovery (NID) aims at detecting known and previously undefined categories of user intent by utilizing limited labeled and massive unlabeled data. Most prior works ofte…

cs.CL2024★ 1 cited

C-ICL: Contrastive In-context Learning for Information Extraction

Ying Mo, Jiahao Liu, Jian Yang +4

There has been increasing interest in exploring the capabilities of advanced large language models (LLMs) in the field of information extraction (IE), specifically focusing on task…

cs.CL2023★ 1 cited

mCL-NER: Cross-Lingual Named Entity Recognition via Multi-view Contrastive Learning

Ying Mo, Jian Yang, Jiahao Liu +4

Cross-lingual named entity recognition (CrossNER) faces challenges stemming from uneven performance due to the scarcity of multilingual corpora, especially for non-English data. Wh…

cs.CL2023★ 1 cited

Multi-task Transformer with Relation-attention and Type-attention for Named Entity Recognition

Ying Mo, Hongyin Tang, Jiahao Liu +5

Named entity recognition (NER) is an important research problem in natural language processing. There are three types of NER tasks, including flat, nested and discontinuous entity…

cs.CL2023★ 1 cited

Multilingual Entity and Relation Extraction from Unified to Language-specific Training

Zixiang Wang, Jian Yang, Tongliang Li +5

Entity and relation extraction is a key task in information extraction, where the output can be used for downstream NLP tasks. Existing approaches for entity and relation extractio…

cs.LG2022

Distribution estimation and change-point estimation for time series via DNN-based GANs

Jianya Lu, Yingjun Mo, Zhijie Xiao +2

The generative adversarial networks (GANs) have recently been applied to estimating the distribution of independent and identically distributed data, and have attracted a lot of re…