Search Results for author:
Found 9 papers, 6 papers with code
Gradient-Boosted Decision Tree for Listwise Context Model in Multimodal Review Helpfulness Prediction
Multimodal Review Helpfulness Prediction (MRHP) aims to rank product reviews based on predicted helpfulness scores and has been widely applied in e-commerce via presenting customers with useful reviews.
READ-PVLA: Recurrent Adapter with Partial Video-Language Alignment for Parameter-Efficient Transfer Learning in Low-Resource Video-Language Modeling
Fully fine-tuning pretrained large-scale transformer models has become a popular paradigm for video-language modeling tasks, such as temporal language grounding and video-language summarization.
Vision-and-Language Pretraining
Moreover, a list of training datasets and downstream tasks is supplied to further polish the perspective into V\&L pretraining.
KDMCSE: Knowledge Distillation Multimodal Sentence Embeddings with Adaptive Angular margin Contrastive Learning
Previous work on multimodal sentence embedding has proposed multimodal contrastive learning and achieved promising results.
Adaptive Contrastive Learning on Multimodal Transformer for Review Helpfulness Predictions
To overcome the aforementioned issues, we propose Multimodal Contrastive Learning for Multimodal Review Helpfulness Prediction (MRHP) problem, concentrating on mutual information between input modalities to explicitly elaborate cross-modal relations.
On the Affinity, Rationality, and Diversity of Hierarchical Topic Modeling
Hierarchical topic modeling aims to discover latent topics from a corpus and organize them into a hierarchy to understand documents with desirable semantic granularity.
Expand BERT Representation with Visual Information via Grounded Language Learning with Multimodal Partial Alignment
Language models have been supervised with both language-only objective and visual grounding in existing studies of visual-grounded language learning.
DemaFormer: Damped Exponential Moving Average Transformer with Energy-Based Modeling for Temporal Language Grounding
Temporal Language Grounding seeks to localize video moments that semantically correspond to a natural language query.
Improving Multimodal Sentiment Analysis: Supervised Angular Margin-based Contrastive Learning for Enhanced Fusion Representation
The effectiveness of a model is heavily reliant on the quality of the fusion representation of multiple modalities in multimodal sentiment analysis.
