most citedExploring the Deceptive Power of LLM-Generated Fake News: A Study of Real-World Detection Challenges

9 citations · 10 across the 8 of their papers we have counts for

collaborators

8 papers

cs.AI2024

Rethinking the Uncertainty: A Critical Review and Analysis in the Era of Large Language Models

Mohammad Beigi, Sijia Wang, Ying Shen +9

In recent years, Large Language Models (LLMs) have become fundamental to a broad spectrum of artificial intelligence applications. As the use of LLMs expands, precisely estimating…

cs.LG2024

AMA-LSTM: Pioneering Robust and Fair Financial Audio Analysis for Stock Volatility Prediction

Shengkun Wang, Taoran Ji, Jianfeng He +5

Stock volatility prediction is an important task in the financial industry. Recent advancements in multimodal methodologies, which integrate both textual and auditory data, have de…

cs.CL2024

InternalInspector : Robust Confidence Estimation in LLMs through Internal States

Mohammad Beigi, Ying Shen, Runing Yang +7

Despite their vast capabilities, Large Language Models (LLMs) often struggle with generating reliable outputs, frequently producing high-confidence inaccuracies known as hallucinat…

cs.CL2024

Can We Trust the Performance Evaluation of Uncertainty Estimation Methods in Text Summarization?

Jianfeng He, Runing Yang, Linlin Yu +5

Text summarization, a key natural language generation (NLG) task, is vital in various domains. However, the high cost of inaccurate summaries in risk-critical applications, particu…

cs.CL2024★ 9 cited

Exploring the Deceptive Power of LLM-Generated Fake News: A Study of Real-World Detection Challenges

Yanshen Sun, Jianfeng He, Limeng Cui +2

Recent advancements in Large Language Models (LLMs) have enabled the creation of fake news, particularly in complex fields like healthcare. Studies highlight the gap in the decepti…

cs.CL2024

Don't Go To Extremes: Revealing the Excessive Sensitivity and Calibration Limitations of LLMs in Implicit Hate Speech Detection

Min Zhang, Jianfeng He, Taoran Ji +1

The fairness and trustworthiness of Large Language Models (LLMs) are receiving increasing attention. Implicit hate speech, which employs indirect language to convey hateful intenti…

cs.CL2023★ 1 cited

Can LLM find the green circle? Investigation and Human-guided tool manipulation for compositional generalization

Min Zhang, Jianfeng He, Shuo Lei +3

The meaning of complex phrases in natural language is composed of their individual components. The task of compositional generalization evaluates a model's ability to understand ne…

cs.CL2023

Uncertainty Estimation on Sequential Labeling via Uncertainty Transmission

Jianfeng He, Linlin Yu, Shuo Lei +2

Sequential labeling is a task predicting labels for each token in a sequence, such as Named Entity Recognition (NER). NER tasks aim to extract entities and predict their labels giv…