41 citations · 81 across the 18 of their papers we have counts for
21 papers
PersoPilot: An Adaptive AI-Copilot for Transparent Contextualized Persona Classification and Personalized Response Generation
Saleh Afzoon, Amin Beheshti, Usman Naseem
Understanding and classifying user personas is critical for delivering effective personalization. While persona information offers valuable insights, its full potential is realized…
PersoDPO: Scalable Preference Optimization for Instruction-Adherent, Persona-Grounded Dialogue via Multi-LLM Evaluation
Saleh Afzoon, MohammadHossein Ahmadi, Usman Naseem +1
Personalization and contextual coherence are two essential components in building effective persona-grounded dialogue systems. These aspects play a crucial role in enhancing user e…
Kardia-R1: Unleashing LLMs to Reason toward Understanding and Empathy for Emotional Support via Rubric-as-Judge Reinforcement Learning
Jiahao Yuan, Zhiqing Cui, Hanqing Wang +3
As web platforms evolve towards greater personalization and emotional complexity, conversational agents must transcend superficial empathy to demonstrate identity-aware emotional r…
LLM-Based Multi-Task Bangla Hate Speech Detection: Type, Severity, and Target
Md Arid Hasan, Firoj Alam, Md Fahad Hossain +2
Online social media platforms are central to everyday communication and information seeking. While these platforms serve positive purposes, they also provide fertile ground for the…
Pluralistic Alignment for Healthcare: A Role-Driven Framework
Jiayou Zhong, Anudeex Shetty, Chao Jia +2
As large language models are increasingly deployed in sensitive domains such as healthcare, ensuring their outputs reflect the diverse values and perspectives held across populatio…
ExBigBang: A Dynamic Approach for Explainable Persona Classification through Contextualized Hybrid Transformer Analysis
Saleh Afzoon, Amin Beheshti, Nabi Rezvani +7
In user-centric design, persona development plays a vital role in understanding user behaviour, capturing needs, segmenting audiences, and guiding design decisions. However, the gr…
Evaluating Hierarchical Clinical Document Classification Using Reasoning-Based LLMs
Akram Mustafa, Usman Naseem, Mostafa Rahimi Azghadi
This study evaluates how well large language models (LLMs) can classify ICD-10 codes from hospital discharge summaries, a critical but error-prone task in healthcare. Using 1,500 s…
Modeling and Optimizing User Preferences in AI Copilots: A Comprehensive Survey and Taxonomy
Saleh Afzoon, Ali Shahsavandi, Phuong Thao Huynh +4
AI copilots represent a new generation of AI-powered systems designed to assist users, particularly knowledge workers and developers, in complex, context-rich tasks. As these syste…
Can Pruning Improve Reasoning? Revisiting Long-CoT Compression with Capability in Mind for Better Reasoning
Shangziqi Zhao, Jiahao Yuan, Jinyang Wu +3
Long chain-of-thought (Long-CoT) reasoning improves accuracy in LLMs, yet its verbose, self-reflective style often hinders effective distillation into small language models (SLMs).…
Beyond Retrieval: Joint Supervision and Multimodal Document Ranking for Textbook Question Answering
Hessa Alawwad, Usman Naseem, Areej Alhothali +2
Textbook question answering (TQA) is a complex task, requiring the interpretation of complex multimodal context. Although recent advances have improved overall performance, they of…
Can Reasoning LLMs Enhance Clinical Document Classification?
Akram Mustafa, Usman Naseem, Mostafa Rahimi Azghadi
Clinical document classification is essential for converting unstructured medical texts into standardised ICD-10 diagnoses, yet it faces challenges due to complex medical language,…
ExtremeAIGC: Benchmarking LMM Vulnerability to AI-Generated Extremist Content
Bhavik Chandna, Mariam Aboujenane, Usman Naseem
Large Multimodal Models (LMMs) are increasingly vulnerable to AI-generated extremist content, including photorealistic images and text, which can be used to bypass safety mechanism…
VaxGuard: A Multi-Generator, Multi-Type, and Multi-Role Dataset for Detecting LLM-Generated Vaccine Misinformation
Syed Talal Ahmad, Haohui Lu, Sidong Liu +4
Recent advancements in Large Language Models (LLMs) have significantly improved text generation capabilities. However, they also present challenges, particularly in generating vacc…
MoCFL: Mobile Cluster Federated Learning Framework for Highly Dynamic Network
Kai Fang, Jiangtao Deng, Chengzu Dong +4
Frequent fluctuations of client nodes in highly dynamic mobile clusters can lead to significant changes in feature space distribution and data drift, posing substantial challenges…
VITAL: A New Dataset for Benchmarking Pluralistic Alignment in Healthcare
Anudeex Shetty, Amin Beheshti, Mark Dras +1
Alignment techniques have become central to ensuring that Large Language Models (LLMs) generate outputs consistent with human values. However, existing alignment paradigms often mo…
Cultural Palette: Pluralising Culture Alignment via Multi-agent Palette
Jiahao Yuan, Zixiang Di, Shangzixin Zhao +4
Large language models (LLMs) face challenges in aligning with diverse cultural values despite their remarkable performance in generation, which stems from inherent monocultural bia…
Reversal of Thought: Enhancing Large Language Models with Preference-Guided Reverse Reasoning Warm-up
Jiahao Yuan, Dehui Du, Hao Zhang +2
Large language models (LLMs) have shown remarkable performance in reasoning tasks but face limitations in mathematical and complex logical reasoning. Existing methods to improve LL…
PersoBench: Benchmarking Personalized Response Generation in Large Language Models
Saleh Afzoon, Zahra Jamali, Usman Naseem +1
While large language models (LLMs) have exhibited impressive conversational capabilities, their proficiency in delivering personalized responses remains unclear. Although recent be…
ReflectDiffu:Reflect between Emotion-intent Contagion and Mimicry for Empathetic Response Generation via a RL-Diffusion Framework
Jiahao Yuan, Zixiang Di, Zhiqing Cui +2
Empathetic response generation necessitates the integration of emotional and intentional dynamics to foster meaningful interactions. Existing research either neglects the intricate…
Enhancing textual textbook question answering with large language models and retrieval augmented generation
Hessa Abdulrahman Alawwad, Areej Alhothali, Usman Naseem +2
Textbook question answering (TQA) is a challenging task in artificial intelligence due to the complex nature of context needed to answer complex questions. Although previous resear…
NLP as a Lens for Causal Analysis and Perception Mining to Infer Mental Health on Social Media
Muskan Garg, Chandni Saxena, Usman Naseem +1
Interactions among humans on social media often convey intentions behind their actions, yielding a psychological language resource for Mental Health Analysis (MHA) of online users.…