activity
20092026
most citedContrastive Representation Learning: A Framework and Review

855 citations · 1.2k across the 90 of their papers we have counts for

collaborators

92 papers

cs.AI2026

Questionnaire-Guided Disaggregation of Energy Appliance Use for Domestic Smart Meter Data

Achal Nanjundamurthy, Rupam Misra, Suzanne Little +1

Ireland's smart metering programme records electricity use at 30-minute resolution, with smart meters installed in over 80\% of households as of late 2025. While this is useful for…

cs.CL2025

An Empirical Study on Chinese Character Decomposition in Multiword Expression-Aware Neural Machine Translation

Lifeng Han, Gareth J. F. Jones, Alan F. Smeaton

Word meaning, representation, and interpretation play fundamental roles in natural language understanding (NLU), natural language processing (NLP), and natural language generation…

cs.SD2025

A Dimensional Approach to Canine Bark Analysis for Assistance Dog Seizure Signaling

Hailin Song, Shelley Brady, Tomás Ward +1

Standard classification of canine vocalisations is severely limited for assistance dogs, where sample data is sparse and variable across dogs and where capture of the full range of…

cs.CV2025

Reinforcement Learning meets Masked Video Modeling : Trajectory-Guided Adaptive Token Selection

Ayush K. Rai, Kyle Min, Tarun Krishna +3

Masked video modeling~(MVM) has emerged as a highly effective pre-training strategy for visual foundation models, whereby the model reconstructs masked spatiotemporal tokens using…

cs.CV2025

Resilience of Vision Transformers for Domain Generalisation in the Presence of Out-of-Distribution Noisy Images

Hamza Riaz, Alan F. Smeaton

Modern AI models excel in controlled settings but often fail in real-world scenarios where data distributions shift unpredictably - a challenge known as domain generalisation (DG).…

cs.CV2025

The Effects of Grouped Structural Global Pruning of Vision Transformers on Domain Generalisation

Hamza Riaz, Alan F. Smeaton

With the growing sizes of AI models like large language models (LLMs) and vision transformers, deploying them on devices with limited computational resources is a significant chall…