9 citations · 9 across the 3 of their papers we have counts for
6 papers · 1 filter
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…
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…
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…
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…
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…
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…