activity
20182026
most citedWeakly-Supervised Neural Text Classification

184 citations · 863 across the 46 of their papers we have counts for

collaborators
Showing 2023Show all

13 papers · 1 filter

cs.CL2023

SCStory: Self-supervised and Continual Online Story Discovery

Susik Yoon, Yu Meng, Dongha Lee +1

We present a framework SCStory for online story discovery, that helps people digest rapidly published news article streams in real-time without human annotations. To organize news…

cs.CL2023★ 11 cited

Evaluating Large Language Models at Evaluating Instruction Following

Zhiyuan Zeng, Jiatong Yu, Tianyu Gao +3

As research in large language models (LLMs) continues to accelerate, LLM-based evaluation has emerged as a scalable and cost-effective alternative to human evaluations for comparin…

cs.CL2023

Learning Multiplex Representations on Text-Attributed Graphs with One Language Model Encoder

Bowen Jin, Wentao Zhang, Yu Zhang +3

In real-world scenarios, texts in a graph are often linked by multiple semantic relations (e.g., papers in an academic graph are referenced by other publications, written by the sa…

cs.CL2023

Weakly Supervised Multi-Label Classification of Full-Text Scientific Papers

Yu Zhang, Bowen Jin, Xiusi Chen +4

Instead of relying on human-annotated training samples to build a classifier, weakly supervised scientific paper classification aims to classify papers only using category descript…

cs.SI2023★ 23 cited

Social network modeling and applications, a tutorial

Lisette Espín-Noboa, Tiago Peixoto, Fariba Karimi

Social networks have been widely studied over the last century from multiple disciplines to understand societal issues such as inequality in employment rates, managerial performanc…

cs.CL2023★ 72 cited

Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias

Yue Yu, Yuchen Zhuang, Jieyu Zhang +5

Large language models (LLMs) have been recently leveraged as training data generators for various natural language processing (NLP) tasks. While previous research has explored diff…

cs.CL2023★ 1 cited

Patton: Language Model Pretraining on Text-Rich Networks

Bowen Jin, Wentao Zhang, Yu Zhang +4

A real-world text corpus sometimes comprises not only text documents but also semantic links between them (e.g., academic papers in a bibliographic network are linked by citations…

cs.CL2023★ 2 cited

ReGen: Zero-Shot Text Classification via Training Data Generation with Progressive Dense Retrieval

Yue Yu, Yuchen Zhuang, Rongzhi Zhang +3

With the development of large language models (LLMs), zero-shot learning has attracted much attention for various NLP tasks. Different from prior works that generate training data…

cs.CL2023★ 1 cited

PIEClass: Weakly-Supervised Text Classification with Prompting and Noise-Robust Iterative Ensemble Training

Yunyi Zhang, Minhao Jiang, Yu Meng +2

Weakly-supervised text classification trains a classifier using the label name of each target class as the only supervision, which largely reduces human annotation efforts. Most ex…

cs.LG2023★ 5 cited

Edgeformers: Graph-Empowered Transformers for Representation Learning on Textual-Edge Networks

Bowen Jin, Yu Zhang, Yu Meng +1

Edges in many real-world social/information networks are associated with rich text information (e.g., user-user communications or user-product reviews). However, mainstream network…

cs.DL2023

The Effect of Metadata on Scientific Literature Tagging: A Cross-Field Cross-Model Study

Yu Zhang, Bowen Jin, Qi Zhu +2

Due to the exponential growth of scientific publications on the Web, there is a pressing need to tag each paper with fine-grained topics so that researchers can track their interes…

cs.CL2023★ 3 cited

Representation Deficiency in Masked Language Modeling

Yu Meng, Jitin Krishnan, Sinong Wang +6

Masked Language Modeling (MLM) has been one of the most prominent approaches for pretraining bidirectional text encoders due to its simplicity and effectiveness. One notable concer…

cs.CL2023★ 1 cited

Effective Seed-Guided Topic Discovery by Integrating Multiple Types of Contexts

Yu Zhang, Yunyi Zhang, Martin Michalski +3

Instead of mining coherent topics from a given text corpus in a completely unsupervised manner, seed-guided topic discovery methods leverage user-provided seed words to extract dis…