80 citations · 311 across the 38 of their papers we have counts for
13 papers · 1 filter
CALM: Culturally Self-Aware Language Models
Lingzhi Shen, Xiaohao Cai, Yunfei Long +3
Cultural awareness in language models is the capacity to understand and adapt to diverse cultural contexts. However, most existing approaches treat culture as static background kno…
HIPPD: Brain-Inspired Hierarchical Information Processing for Personality Detection
Guanming Chen, Lingzhi Shen, Xiaohao Cai +2
Personality detection from text aims to infer an individual's personality traits based on linguistic patterns. However, existing machine learning approaches often struggle to captu…
EmoPerso: Enhancing Personality Detection with Self-Supervised Emotion-Aware Modelling
Lingzhi Shen, Xiaohao Cai, Yunfei Long +3
Personality detection from text is commonly performed by analysing users' social media posts. However, existing methods heavily rely on large-scale annotated datasets, making it ch…
Flick: Few Labels Text Classification using K-Aware Intermediate Learning in Multi-Task Low-Resource Languages
Ali Almutairi, Abdullah Alsuhaibani, Shoaib Jameel +3
Training deep learning networks with minimal supervision has gained significant research attention due to its potential to reduce reliance on extensive labelled data. While self-tr…
TAGS: A Test-Time Generalist-Specialist Framework with Retrieval-Augmented Reasoning and Verification
Jianghao Wu, Feilong Tang, Yulong Li +5
Recent advances such as Chain-of-Thought prompting have significantly improved large language models (LLMs) in zero-shot medical reasoning. However, prompting-based methods often r…
Less but Better: Parameter-Efficient Fine-Tuning of Large Language Models for Personality Detection
Lingzhi Shen, Yunfei Long, Xiaohao Cai +3
Personality detection automatically identifies an individual's personality from various data sources, such as social media texts. However, as the parameter scale of language models…
LL4G: Self-Supervised Dynamic Optimization for Graph-Based Personality Detection
Lingzhi Shen, Yunfei Long, Xiaohao Cai +4
Graph-based personality detection constructs graph structures from textual data, particularly social media posts. Current methods often struggle with sparse or noisy data and rely…
NarrationDep: Narratives on Social Media For Automatic Depression Detection
Hamad Zogan, Imran Razzak, Shoaib Jameel +1
Social media posts provide valuable insight into the narrative of users and their intentions, including providing an opportunity to automatically model whether a social media user…
From Explainable to Interpretable Deep Learning for Natural Language Processing in Healthcare: How Far from Reality?
Guangming Huang, Yingya Li, Shoaib Jameel +2
Deep learning (DL) has substantially enhanced natural language processing (NLP) in healthcare research. However, the increasing complexity of DL-based NLP necessitates transparent…
IDoFew: Intermediate Training Using Dual-Clustering in Language Models for Few Labels Text Classification
Abdullah Alsuhaibani, Hamad Zogan, Imran Razzak +2
Language models such as Bidirectional Encoder Representations from Transformers (BERT) have been very effective in various Natural Language Processing (NLP) and text mining tasks i…
Topics in Contextualised Attention Embeddings
Mozhgan Talebpour, Alba Garcia Seco de Herrera, Shoaib Jameel
Contextualised word vectors obtained via pre-trained language models encode a variety of knowledge that has already been exploited in applications. Complementary to these language…
Modeling Semantic Relatedness using Global Relation Vectors
Shoaib Jameel, Zied Bouraoui, Steven Schockaert
Word embedding models such as GloVe rely on co-occurrence statistics from a large corpus to learn vector representations of word meaning. These vectors have proven to capture surpr…
Jointly Learning Word Embeddings and Latent Topics
Bei Shi, Wai Lam, Shoaib Jameel +2
Word embedding models such as Skip-gram learn a vector-space representation for each word, based on the local word collocation patterns that are observed in a text corpus. Latent t…