activity
20172026
most citedDeep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologies

160 citations · 246 across the 35 of their papers we have counts for

collaborators
Showing 2024Show all

8 papers · 1 filter

cs.CL2024

Aristotle: Mastering Logical Reasoning with A Logic-Complete Decompose-Search-Resolve Framework

Jundong Xu, Hao Fei, Meng Luo +6

In the context of large language models (LLMs), current advanced reasoning methods have made impressive strides in various reasoning tasks. However, when it comes to logical reason…

cs.CL2024★ 1 cited

ChronoFact: Timeline-based Temporal Fact Verification

Anab Maulana Barik, Wynne Hsu, Mong Li Lee

Temporal claims, often riddled with inaccuracies, are a significant challenge in the digital misinformation landscape. Fact-checking systems that can accurately verify such claims…

cs.CL2024

PanoSent: A Panoptic Sextuple Extraction Benchmark for Multimodal Conversational Aspect-based Sentiment Analysis

Meng Luo, Hao Fei, Bobo Li +6

While existing Aspect-based Sentiment Analysis (ABSA) has received extensive effort and advancement, there are still gaps in defining a more holistic research target seamlessly int…

cs.IR2024★ 1 cited

Evidence-Based Temporal Fact Verification

Anab Maulana Barik, Wynne Hsu, Mong Li Lee

Automated fact verification plays an essential role in fostering trust in the digital space. Despite the growing interest, the verification of temporal facts has not received much…

cs.CL2024★ 4 cited

Faithful Logical Reasoning via Symbolic Chain-of-Thought

Jundong Xu, Hao Fei, Liangming Pan +3

While the recent Chain-of-Thought (CoT) technique enhances the reasoning ability of large language models (LLMs) with the theory of mind, it might still struggle in handling logica…

cs.CV2024★ 7 cited

Cross-Domain Feature Augmentation for Domain Generalization

Yingnan Liu, Yingtian Zou, Rui Qiao +3

Domain generalization aims to develop models that are robust to distribution shifts. Existing methods focus on learning invariance across domains to enhance model robustness, and d…