5 citations · 17 across the 13 of their papers we have counts for
15 papers
Representation Learning of Structured Data for Medical Foundation Models
Vijay Prakash Dwivedi, Viktor Schlegel, Andy T. Liu +6
Large Language Models (LLMs) have demonstrated remarkable performance across various domains, including healthcare. However, their ability to effectively represent structured non-t…
MEDSAGE: Enhancing Robustness of Medical Dialogue Summarization to ASR Errors with LLM-generated Synthetic Dialogues
Kuluhan Binici, Abhinav Ramesh Kashyap, Viktor Schlegel +6
Automatic Speech Recognition (ASR) systems are pivotal in transcribing speech into text, yet the errors they introduce can significantly degrade the performance of downstream tasks…
M-QALM: A Benchmark to Assess Clinical Reading Comprehension and Knowledge Recall in Large Language Models via Question Answering
Anand Subramanian, Viktor Schlegel, Abhinav Ramesh Kashyap +3
There is vivid research on adapting Large Language Models (LLMs) to perform a variety of tasks in high-stakes domains such as healthcare. Despite their popularity, there is a lack…
Automated Clinical Coding for Outpatient Departments
Viktor Schlegel, Abhinav Ramesh Kashyap, Thanh-Tung Nguyen +5
Computerised clinical coding approaches aim to automate the process of assigning a set of codes to medical records. While there is active research pushing the state of the art on c…
PULSAR at MEDIQA-Sum 2023: Large Language Models Augmented by Synthetic Dialogue Convert Patient Dialogues to Medical Records
Viktor Schlegel, Hao Li, Yuping Wu +8
This paper describes PULSAR, our system submission at the ImageClef 2023 MediQA-Sum task on summarising patient-doctor dialogues into clinical records. The proposed framework relie…
PULSAR: Pre-training with Extracted Healthcare Terms for Summarising Patients' Problems and Data Augmentation with Black-box Large Language Models
Hao Li, Yuping Wu, Viktor Schlegel +7
Medical progress notes play a crucial role in documenting a patient's hospital journey, including his or her condition, treatment plan, and any updates for healthcare providers. Au…
ADAPTERMIX: Exploring the Efficacy of Mixture of Adapters for Low-Resource TTS Adaptation
Ambuj Mehrish, Abhinav Ramesh Kashyap, Li Yingting +2
There are significant challenges for speaker adaptation in text-to-speech for languages that are not widely spoken or for speakers with accents or dialects that are not well-repres…
A Two-Stage Decoder for Efficient ICD Coding
Thanh-Tung Nguyen, Viktor Schlegel, Abhinav Kashyap +1
Clinical notes in healthcare facilities are tagged with the International Classification of Diseases (ICD) code; a list of classification codes for medical diagnoses and procedures…
A Comprehensive Survey of Sentence Representations: From the BERT Epoch to the ChatGPT Era and Beyond
Abhinav Ramesh Kashyap, Thanh-Tung Nguyen, Viktor Schlegel +3
Sentence representations are a critical component in NLP applications such as retrieval, question answering, and text classification. They capture the meaning of a sentence, enabli…
Mimic-IV-ICD: A new benchmark for eXtreme MultiLabel Classification
Thanh-Tung Nguyen, Viktor Schlegel, Abhinav Kashyap +4
Clinical notes are assigned ICD codes - sets of codes for diagnoses and procedures. In the recent years, predictive machine learning models have been built for automatic ICD coding…
UDApter -- Efficient Domain Adaptation Using Adapters
Bhavitvya Malik, Abhinav Ramesh Kashyap, Min-Yen Kan +1
We propose two methods to make unsupervised domain adaptation (UDA) more parameter efficient using adapters, small bottleneck layers interspersed with every layer of the large-scal…
BLOOM: A 176B-Parameter Open-Access Multilingual Language Model
BigScience Workshop, :, Teven Le Scao +391
Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to wi…
So Different Yet So Alike! Constrained Unsupervised Text Style Transfer
Abhinav Ramesh Kashyap, Devamanyu Hazarika, Min-Yen Kan +2
Automatic transfer of text between domains has become popular in recent times. One of its aims is to preserve the semantic content of text being translated from source to target do…
Domain Divergences: a Survey and Empirical Analysis
Abhinav Ramesh Kashyap, Devamanyu Hazarika, Min-Yen Kan +1
Domain divergence plays a significant role in estimating the performance of a model in new domains. While there is a significant literature on divergence measures, researchers find…
SciWING -- A Software Toolkit for Scientific Document Processing
Abhinav Ramesh Kashyap, Min-Yen Kan
We introduce SciWING, an open-source software toolkit which provides access to pre-trained models for scientific document processing tasks, inclusive of citation string parsing and…