80 citations · 228 across the 103 of their papers we have counts for
25 papers · 1 filter
BARRAC: Adaptation of an English Aspect-based Sentiment Analysis Approach for Classification Tasks in Arabic Dialects
Ali Almutairi, Gelareh Mohammadi, Imran Razzak +1
With the rapid growth of Arabic NLP, several models, datasets and benchmarks have been reported. This paper asks whether approaches developed for majority languages like English ca…
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…
PRISM: A Personality-Driven Multi-Agent Framework for Social Media Simulation
Zhixiang Lu, Xueyuan Deng, Yiran Liu +4
Traditional agent-based models (ABMs) of opinion dynamics often fail to capture the psychological heterogeneity driving online polarization due to simplistic homogeneity assumption…
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…
RELOOP: Recursive Retrieval with Multi-Hop Reasoner and Planners for Heterogeneous QA
Ruiyi Yang, Hao Xue, Imran Razzak +2
Retrieval-augmented generation (RAG) remains brittle on multi-step questions and heterogeneous evidence sources, trading accuracy against latency and token/tool budgets. This paper…
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…
A Survey of Scientific Large Language Models: From Data Foundations to Agent Frontiers
Ming Hu, Chenglong Ma, Wei Li +117
Scientific Large Language Models (Sci-LLMs) are transforming how knowledge is represented, integrated, and applied in scientific research, yet their progress is shaped by the compl…
Towards Efficient Medical Reasoning with Minimal Fine-Tuning Data
Xinlin Zhuang, Feilong Tang, Haolin Yang +9
Supervised Fine-Tuning (SFT) of the language backbone plays a pivotal role in adapting Vision-Language Models (VLMs) to specialized domains such as medical reasoning. However, exis…
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…
From Generation to Detection: A Multimodal Multi-Task Dataset for Benchmarking Health Misinformation
Zhihao Zhang, Yiran Zhang, Xiyue Zhou +4
Infodemics and health misinformation have significant negative impact on individuals and society, exacerbating confusion and increasing hesitancy in adopting recommended health mea…
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…
MMRC: A Large-Scale Benchmark for Understanding Multimodal Large Language Model in Real-World Conversation
Haochen Xue, Feilong Tang, Ming Hu +13
Recent multimodal large language models (MLLMs) have demonstrated significant potential in open-ended conversation, generating more accurate and personalized responses. However, th…
ByteScience: Bridging Unstructured Scientific Literature and Structured Data with Auto Fine-tuned Large Language Model in Token Granularity
Tong Xie, Hanzhi Zhang, Shaozhou Wang +5
Natural Language Processing (NLP) is widely used to supply summarization ability from long context to structured information. However, extracting structured knowledge from scientif…
Better to Ask in English: Evaluation of Large Language Models on English, Low-resource and Cross-Lingual Settings
Krishno Dey, Prerona Tarannum, Md. Arid Hasan +2
Large Language Models (LLMs) are trained on massive amounts of data, enabling their application across diverse domains and tasks. Despite their remarkable performance, most LLMs ar…
Do Large Language Models Speak All Languages Equally? A Comparative Study in Low-Resource Settings
Md. Arid Hasan, Prerona Tarannum, Krishno Dey +2
Large language models (LLMs) have garnered significant interest in natural language processing (NLP), particularly their remarkable performance in various downstream tasks in resou…
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…
Construction and Application of Materials Knowledge Graph in Multidisciplinary Materials Science via Large Language Model
Yanpeng Ye, Jie Ren, Shaozhou Wang +6
Knowledge in materials science is widely dispersed across extensive scientific literature, posing significant challenges to the efficient discovery and integration of new materials…
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…
DARWIN Series: Domain Specific Large Language Models for Natural Science
Tong Xie, Yuwei Wan, Wei Huang +9
Emerging tools bring forth fresh approaches to work, and the field of natural science is no different. In natural science, traditional manual, serial, and labour-intensive work is…
Uncovering Political Hate Speech During Indian Election Campaign: A New Low-Resource Dataset and Baselines
Farhan Ahmad Jafri, Mohammad Aman Siddiqui, Surendrabikram Thapa +3
The detection of hate speech in political discourse is a critical issue, and this becomes even more challenging in low-resource languages. To address this issue, we introduce a new…
A Novel Approach to Train Diverse Types of Language Models for Health Mention Classification of Tweets
Pervaiz Iqbal Khan, Imran Razzak, Andreas Dengel +1
Health mention classification deals with the disease detection in a given text containing disease words. However, non-health and figurative use of disease words adds challenges to…
A Comprehensive Survey on Word Representation Models: From Classical to State-Of-The-Art Word Representation Language Models
Usman Naseem, Imran Razzak, Shah Khalid Khan +1
Word representation has always been an important research area in the history of natural language processing (NLP). Understanding such complex text data is imperative, given that i…