Fei Cheng

A System for Worldwide COVID-19 Information Aggregation

2020 · arXiv (Cornell University)

The global pandemic of COVID-19 has made the public pay close attention to related news, covering various domains, such as sanitation, treatment, and effects on education. Meanwhile, the COVID-19 condition is very different among the …

Dynamically Updating Event Representations for Temporal Relation Classification with Multi-category Learning

2020

Temporal relation classification is a pair-wise task for identifying the relation of a temporal link (TLINK) between two mentions, i.e. event, time and document creation time (DCT). It leads to two crucial limits: 1) Two …

MultiTool-CoT: GPT-3 Can Use Multiple External Tools with Chain of Thought Prompting

2023 · arXiv (Cornell University)

Large language models (LLMs) have achieved impressive performance on various reasoning tasks. To further improve the performance, we propose MultiTool-CoT, a novel framework that leverages chain-of-thought (CoT) prompting to incorporate multiple external tools, such as …

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 …

From Aleatoric to Epistemic: Exploring Uncertainty Quantification Techniques in Artificial Intelligence

2025 · arXiv (Cornell University)

Uncertainty quantification (UQ) is a critical aspect of artificial intelligence (AI) systems, particularly in high-risk domains such as healthcare, autonomous systems, and financial technology, where decision-making processes must account for uncertainty. This review explores the …

CAPE: Context-Aware Personality Evaluation Framework for Large Language Models

2025 · arXiv (Cornell University)

Psychometric tests, traditionally used to assess humans, are now being applied to Large Language Models (LLMs) to evaluate their behavioral traits. However, existing studies follow a context-free approach, answering each question in isolation to avoid …

Classifying Temporal Relations by Bidirectional LSTM over Dependency Paths

2017

Temporal relation classification is becoming an active research field. Lots of methods have been proposed, while most of them focus on extracting features from external resources. Less attention has been paid to a significant advance …