Search Results for author:
Found 8 papers, 1 papers with code
Scalable Approach for Normalizing E-commerce Text Attributes (SANTA)
Experiments on a real-world attribute normalization dataset of 50 attributes show that the embeddings trained using our proposed approach obtain 2. 3% improvement over best string matching and 19. 3% improvement over best unsupervised embeddings.
LATEX-Numeric: Language Agnostic Text Attribute Extraction for Numeric Attributes
We propose a multi-task learning architecture to deal with missing labels in the training data, leading to F1 improvement of 9. 2{\%} for numeric attributes over state-of-the-art single-task architecture.
LaTeX-Numeric: Language-agnostic Text attribute eXtraction for E-commerce Numeric Attributes
We propose a multi-task learning architecture to deal with missing labels in the training data, leading to F1 improvement of 9. 2% for numeric attributes over single-task architecture.
Distantly Supervised Transformers For E-Commerce Product QA
Training with CQA pairs helps our model learning semantic QA relevance and distant supervision enables learning of syntactic features as well as the nuances of user querying language.
Improving Answer Selection and Answer Triggering using Hard Negatives
In this paper, we establish the effectiveness of using hard negatives, coupled with a siamese network and a suitable loss function, for the tasks of answer selection and answer triggering.
Multi-Label Cross-Modal Retrieval
In this work, we address the problem of cross-modal retrieval in presence of multi-label annotations.
Scene Classification With Semantic Fisher Vectors
A semantic FV is then computed as a Gaussian Mixture FV in the space of these natural parameters.
The Beauty of Capturing Faces: Rating the Quality of Digital Portraits
Digital portrait photographs are everywhere, and while the number of face pictures keeps growing, not much work has been done to on automatic portrait beauty assessment.
