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.
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.
no code implementations • 18 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.
no code implementations • 16 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.
no code implementations • 5 Feb 2024 • Hessa Abdulrahman Alawwad, Areej Alhothali, Usman Naseem, Ali Alkhathlan, Amani Jamal
Textbook question answering (TQA) is a challenging task in artificial intelligence due to the complex nature of context and multimodal data.
no code implementations • 15 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.
1 code implementation • 26 Jun 2023 • Farhan Ahmad Jafri, Mohammad Aman Siddiqui, Surendrabikram Thapa, Kritesh Rauniyar, Usman Naseem, Imran Razzak
The detection of hate speech in political discourse is a critical issue, and this becomes even more challenging in low-resource languages.
1 code implementation • IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshop 2023 • Aashish Bhandari, Siddhant B. Shah, Surendrabikram Thapa, Usman Naseem, Mehwish Nasim
Text-embedded images are frequently used on social media to convey opinions and emotions, but they can also be a medium for disseminating hate speech, propaganda, and extremist ideologies.
no code implementations • 23 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.
no code implementations • 27 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.
no code implementations • 26 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.
1 code implementation • 8 Jul 2022 • Shaina Raza, Deepak John Reji, Dora D. Liu, Syed Raza Bashir, Usman Naseem
This paper introduces Dbias, which is a Python package to ensure fairness in news articles.
no code implementations • nlppower (ACL) 2022 • Usman Naseem, Byoung Chan Lee, Matloob Khushi, Jinman Kim, Adam G. Dunn
We present and release PHS-BERT, a transformer-based PLM, to identify tasks related to public health surveillance on social media.
1 code implementation • 9 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.
no code implementations • 17 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.
no code implementations • 13 Mar 2021 • Mukul Jaggi, Priyanka Mandal, Shreya Narang, Usman Naseem, Matloob Khushi
These datasets were labelled with three labelling techniques based on stock price changes.
no code implementations • 28 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).
no code implementations • 19 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.