2 citations · 3 across the 13 of their papers we have counts for
8 papers · 1 filter
Causal Fine-Tuning under Latent Confounded Shift
Jialin Yu, Yuxiang Zhou, Haoxuan Li +6
Adapting to latent confounded shift remains a core challenge in modern AI. This setting is driven by hidden variables that induce spurious correlations between inputs and outputs d…
ExDDI: Explaining Drug-Drug Interaction Predictions with Natural Language
Zhaoyue Sun, Jiazheng Li, Gabriele Pergola +1
Predicting unknown drug-drug interactions (DDIs) is crucial for improving medication safety. Previous efforts in DDI prediction have typically focused on binary classification or p…
DrugWatch: A Comprehensive Multi-Source Data Visualisation Platform for Drug Safety Information
Artem Bobrov, Domantas Saltenis, Zhaoyue Sun +2
Drug safety research is crucial for maintaining public health, often requiring comprehensive data support. However, the resources currently available to the public are limited and…
Calibrating LLMs with Preference Optimization on Thought Trees for Generating Rationale in Science Question Scoring
Jiazheng Li, Hainiu Xu, Zhaoyue Sun +4
Generating rationales that justify scoring decisions has been a promising way to facilitate explainability in automated scoring systems. However, existing methods do not match the…
Cascading Large Language Models for Salient Event Graph Generation
Xingwei Tan, Yuxiang Zhou, Gabriele Pergola +1
Generating event graphs from long documents is challenging due to the inherent complexity of multiple tasks involved such as detecting events, identifying their relationships, and…
Set-Aligning Framework for Auto-Regressive Event Temporal Graph Generation
Xingwei Tan, Yuxiang Zhou, Gabriele Pergola +1
Event temporal graphs have been shown as convenient and effective representations of complex temporal relations between events in text. Recent studies, which employ pre-trained lan…
Leveraging ChatGPT in Pharmacovigilance Event Extraction: An Empirical Study
Zhaoyue Sun, Gabriele Pergola, Byron C. Wallace +1
With the advent of large language models (LLMs), there has been growing interest in exploring their potential for medical applications. This research aims to investigate the abilit…
Large Language Models Fall Short: Understanding Complex Relationships in Detective Narratives
Runcong Zhao, Qinglin Zhu, Hainiu Xu +4
Existing datasets for narrative understanding often fail to represent the complexity and uncertainty of relationships in real-life social scenarios. To address this gap, we introdu…