most citedZero-shot Temporal Relation Extraction with ChatGPT

5 citations · 9 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2024

Predicting Rewards Alongside Tokens: Non-disruptive Parameter Insertion for Efficient Inference Intervention in Large Language Model

Chenhan Yuan, Fei Huang, Ru Peng +4

Transformer-based large language models (LLMs) exhibit limitations such as generating unsafe responses, unreliable reasoning, etc. Existing inference intervention approaches attemp…

cs.CL20241 cited

Dólares or Dollars? Unraveling the Bilingual Prowess of Financial LLMs Between Spanish and English

Xiao Zhang, Ruoyu Xiang, Chenhan Yuan +8

Despite Spanish's pivotal role in the global finance industry, a pronounced gap exists in Spanish financial natural language processing (NLP) and application studies compared to En…

cs.CL20233 cited

Back to the Future: Towards Explainable Temporal Reasoning with Large Language Models

Chenhan Yuan, Qianqian Xie, Jimin Huang +1

Temporal reasoning is a crucial NLP task, providing a nuanced understanding of time-sensitive contexts within textual data. Although recent advancements in LLMs have demonstrated t…

cs.LG2023

GradXKG: A Universal Explain-per-use Temporal Knowledge Graph Explainer

Chenhan Yuan, Hoda Eldardiry

Temporal knowledge graphs (TKGs) have shown promise for reasoning tasks by incorporating a temporal dimension to represent how facts evolve over time. However, existing TKG reasoni…

cs.CL20235 cited

Zero-shot Temporal Relation Extraction with ChatGPT

Chenhan Yuan, Qianqian Xie, Sophia Ananiadou

The goal of temporal relation extraction is to infer the temporal relation between two events in the document. Supervised models are dominant in this task. In this work, we investi…