10 papers · 1 filter
LiFT: How to Enable In-Context Learning for Longitudinal Modelling
Iqra Ali, Talia Tseriotou, Mahmud Elahi Akhter +2
Longitudinal NLP tasks such as mental health monitoring and stance evolution require modeling temporally ordered text to track persistence and detect change. Such tasks also suffer…
Automated Data Enrichment using Confidence-Aware Fine-Grained Debate among Open-Source LLMs for Mental Health and Online Safety
Junyu Mao, Anthony Hills, Talia Tseriotou +10
Real-world indicators play an important role in many Natural Language Processing (NLP) applications, such as life events for mental health analysis and risky behaviours for online…
Investigating LLM Capabilities on Long Context Comprehension for Medical Question Answering
Feras AlMannaa, Talia Tseriotou, Jenny Chim +1
This study is the first to investigate LLM comprehension capabilities over long-context (LC), clinically relevant medical Question Answering (QA) beyond MCQA. Our comprehensive app…
Temporal reasoning for timeline summarisation in social media
Jiayu Song, Mahmud Elahi Akhter, Dana Atzil Slonim +1
This paper explores whether enhancing temporal reasoning capabilities in Large Language Models (LLMs) can improve the quality of timeline summarisation, the task of summarising lon…
Assessing the Reasoning Capabilities of LLMs in the context of Evidence-based Claim Verification
John Dougrez-Lewis, Mahmud Elahi Akhter, Federico Ruggeri +3
Although LLMs have shown great performance on Mathematics and Coding related reasoning tasks, the reasoning capabilities of LLMs regarding other forms of reasoning are still an ope…
Less for More: Enhanced Feedback-aligned Mixed LLMs for Molecule Caption Generation and Fine-Grained NLI Evaluation
Dimitris Gkoumas, Maria Liakata
Scientific language models drive research innovation but require extensive fine-tuning on large datasets. This work enhances such models by improving their inference and evaluation…