Papers by Byungseok Roh
Large Language Models are Temporal and Causal Reasoners for Video Question Answering (2023.emnlp-main)
Copied to clipboard
| Challenge: | Large Language Models (LLMs) have shown remarkable performances on a wide range of natural language understanding and generation tasks. |
| Approach: | They propose a framework that exploits linguistic shortcuts and mitigates 'linguistic bias' by flipping the source pair and target label to understand their complex relationships. |
| Outcome: | The proposed framework outperforms both LLMs-based and non-LLMs- based models on five challenging VideoQA benchmarks. |
Efficient Multilingual Multi-modal Pre-training through Triple Contrastive Loss (2022.coling-1)
Copied to clipboard
| Challenge: | Existing approaches to learn visual and textual representations from web-scale image-text pairs are limited due to labeling cost and limited scalability. |
| Approach: | They propose to use web-scale image-text pairs to learn visual and textual representations in the shared space. |
| Outcome: | The proposed enhancement scheme improves multilingual vision-and-language tasks by minimizing a triplet contrastive loss on images and two different language texts with the same meaning. |