Shah Nawaz

Learning Inward Scaled Hypersphere Embedding: Exploring Projections in Higher Dimensions

2018 · arXiv (Cornell University)

Majority of the current dimensionality reduction or retrieval techniques rely on embedding the learned feature representations onto a computable metric space. Once the learned features are mapped, a distance metric aids the bridging of gaps …

Aiding Intra-Text Representations with Visual Context for Multimodal Named Entity Recognition

2019

With the massive explosion of social media platforms such as Twitter and Instagram, people everyday share billions of multimedia posts, containing images and text. Typically, text in these posts is short, informal and noisy, leading …

Parameter-Efficient Single Collaborative Branch for Recommendation

2025

Recommender Systems (RS) often rely on representations of users and items in a joint embedding space and on a similarity metric to compute relevance scores.In modern RS, the modules to obtain user and item representations …

Robust Harmful Meme Detection under Missing Modalities via Shared Representation Learning

2026

Internet memes are powerful tools for communication, capable of spreading political, psychological, and sociocultural ideas. However, they can be harmful and can be used to disseminate hate toward targeted individuals or groups. Although previous studies …