Search Results for author: Usman Naseem

Found 18 papers, 4 papers with code

Incorporating Medical Knowledge to Transformer-based Language Models for Medical Dialogue Generation

no code implementations BioNLP (ACL) 2022 Usman Naseem, Ajay Bandi, Shaina Raza, Junaid Rashid, Bharathi Raja Chakravarthi

In this study, we propose a new method that addresses the challenges of medical dialogue generation by incorporating medical knowledge into transformer-based language models.

Dialogue Generation Medical Diagnosis

Accuracy meets Diversity in a News Recommender System

no code implementations COLING 2022 Shaina Raza, Syed Raza Bashir, Usman Naseem

We customize an augmented vector for each query and news item to introduce information interaction between the two towers.

Recommendation Systems

MSynFD: Multi-hop Syntax aware Fake News Detection

no code implementations18 Feb 2024 Liang Xiao, Qi Zhang, Chongyang Shi, Shoujin Wang, Usman Naseem, Liang Hu

These existing methods fail to handle the complex, subtle twists in news articles, such as syntax-semantics mismatches and prior biases, leading to lower performance and potential failure when modalities or social context are missing.

Fake News Detection

Enhancing ESG Impact Type Identification through Early Fusion and Multilingual Models

no code implementations16 Feb 2024 Hariram Veeramani, Surendrabikram Thapa, Usman Naseem

In the evolving landscape of Environmental, Social, and Corporate Governance (ESG) impact assessment, the ML-ESG-2 shared task proposes identifying ESG impact types.

Decision Making Ensemble Learning

Prompting Large Language Models for Topic Modeling

no code implementations15 Dec 2023 Han Wang, Nirmalendu Prakash, Nguyen Khoi Hoang, Ming Shan Hee, Usman Naseem, Roy Ka-Wei Lee

Topic modeling is a widely used technique for revealing underlying thematic structures within textual data.

Sentence

Causal Intervention for Abstractive Related Work Generation

no code implementations23 May 2023 Jiachang Liu, Qi Zhang, Chongyang Shi, Usman Naseem, Shoujin Wang, Ivor Tsang

Abstractive related work generation has attracted increasing attention in generating coherent related work that better helps readers grasp the background in the current research.

Sentence

Rumor Detection with Hierarchical Representation on Bipartite Adhoc Event Trees

no code implementations27 Apr 2023 Qi Zhang, Yayi Yang, Chongyang Shi, An Lao, Liang Hu, Shoujin Wang, Usman Naseem

Accordingly, we propose a novel rumor detection model with hierarchical representation on the bipartite adhoc event trees called BAET.

NLP as a Lens for Causal Analysis and Perception Mining to Infer Mental Health on Social Media

no code implementations26 Jan 2023 Muskan Garg, Chandni Saxena, Usman Naseem, Bonnie J Dorr

To bridge this gap, we posit two significant dimensions: (1) Causal analysis to illustrate a cause and effect relationship in the user generated text; (2) Perception mining to infer psychological perspectives of social effects on online users intentions.

Relation Extraction

Benchmarking for Biomedical Natural Language Processing Tasks with a Domain Specific ALBERT

1 code implementation9 Jul 2021 Usman Naseem, Adam G. Dunn, Matloob Khushi, Jinman Kim

We present BioALBERT, a domain-specific adaptation of A Lite Bidirectional Encoder Representations from Transformers (ALBERT), trained on biomedical (PubMed and PubMed Central) and clinical (MIMIC-III) corpora and fine tuned for 6 different tasks across 20 benchmark datasets.

Benchmarking Document Classification +7

Classifying vaccine sentiment tweets by modelling domain-specific representation and commonsense knowledge into context-aware attentive GRU

no code implementations17 Jun 2021 Usman Naseem, Matloob Khushi, Jinman Kim, Adam G. Dunn

In this study, to classify vaccine sentiment tweets with limited information, we present a novel end-to-end framework consisting of interconnected components that use domain-specific LM trained on vaccine-related tweets and models commonsense knowledge into a bidirectional gated recurrent network (CK-BiGRU) with context-aware attention.

A Comprehensive Survey on Word Representation Models: From Classical to State-Of-The-Art Word Representation Language Models

no code implementations28 Oct 2020 Usman Naseem, Imran Razzak, Shah Khalid Khan, Mukesh Prasad

In this survey, we explore different word representation models and its power of expression, from the classical to modern-day state-of-the-art word representation language models (LMS).

Word Embeddings

BioALBERT: A Simple and Effective Pre-trained Language Model for Biomedical Named Entity Recognition

no code implementations19 Sep 2020 Usman Naseem, Matloob Khushi, Vinay Reddy, Sakthivel Rajendran, Imran Razzak, Jinman Kim

In recent years, with the growing amount of biomedical documents, coupled with advancement in natural language processing algorithms, the research on biomedical named entity recognition (BioNER) has increased exponentially.

Language Modelling named-entity-recognition +3

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