most citedTask Formulation Matters When Learning Continually: A Case Study in Visual Question Answering

3 citations · 9 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2023

Camera-Incremental Object Re-Identification with Identity Knowledge Evolution

Hantao Yao, Lu Yu, Jifei Luo +1

Object Re-identification (ReID) aims to retrieve the probe object from many gallery images with the ReID model inferred based on a stationary camera-free dataset by associating and…

cs.CV2023

Quality-agnostic Image Captioning to Safely Assist People with Vision Impairment

Lu Yu, Malvina Nikandrou, Jiali Jin +1

Automated image captioning has the potential to be a useful tool for people with vision impairments. Images taken by this user group are often noisy, which leads to incorrect and e…

cs.LG2023★ 1 cited

Knowledge Distillation for Efficient Sequences of Training Runs

Xingyu Liu, Alex Leonardi, Lu Yu +3

In many practical scenarios -- like hyperparameter search or continual retraining with new data -- related training runs are performed many times in sequence. Current practice is t…

cs.CV2023★ 2 cited

X-Pruner: eXplainable Pruning for Vision Transformers

Lu Yu, Wei Xiang

Recently vision transformer models have become prominent models for a range of tasks. These models, however, usually suffer from intensive computational costs and heavy memory requ…

cs.CV2022★ 2 cited

Going for GOAL: A Resource for Grounded Football Commentaries

Alessandro Suglia, José Lopes, Emanuele Bastianelli +6

Recent video+language datasets cover domains where the interaction is highly structured, such as instructional videos, or where the interaction is scripted, such as TV shows. Both…

cs.LG2022★ 3 cited

Task Formulation Matters When Learning Continually: A Case Study in Visual Question Answering

Mavina Nikandrou, Lu Yu, Alessandro Suglia +2

Continual learning aims to train a model incrementally on a sequence of tasks without forgetting previous knowledge. Although continual learning has been widely studied in computer…

cs.CV2022★ 1 cited

Adversarial Robustness of Visual Dialog

Lu Yu, Verena Rieser

Adversarial robustness evaluates the worst-case performance scenario of a machine learning model to ensure its safety and reliability. This study is the first to investigate the ro…