papers

Publications (6)

cs.IR2025

CSRM-LLM: Embracing Multilingual LLMs for Cold-Start Relevance Matching in Emerging E-commerce Markets

Yujing Wang, Yiren Chen, Huoran Li +18

As global e-commerce platforms continue to expand, companies are entering new markets where they encounter cold-start challenges due to limited human labels and user behaviors. In…

cs.CL2020

Development of a Dataset and a Deep Learning Baseline Named Entity Recognizer for Three Low Resource Languages: Bhojpuri, Maithili and Magahi

Rajesh Kumar Mundotiya, Shantanu Kumar, Ajeet kumar +5

In Natural Language Processing (NLP) pipelines, Named Entity Recognition (NER) is one of the preliminary problems, which marks proper nouns and other named entities such as Locatio…

cs.LG2025

Mixture-of-Personas Language Models for Population Simulation

Ngoc Bui, Hieu Trung Nguyen, Shantanu Kumar +4

Advances in Large Language Models (LLMs) paved the way for their emerging applications in various domains, such as human behavior simulations, where LLMs could augment human-genera…

cs.GR2025

Machine Learning-Driven Volumetric Cloud Rendering: Procedural Shader Optimization and Dynamic Lighting in Unreal Engine for Realistic Atmospheric Simulation

Shruti Singh, Shantanu Kumar

This study advances real-time volumetric cloud rendering in Computer Graphics (CG) by developing a specialized shader in Unreal Engine (UE), focusing on realistic cloud modeling an…

cs.LG2024

Efficient Distributed Training through Gradient Compression with Sparsification and Quantization Techniques

Shruti Singh, Shantanu Kumar

This study investigates the impact of gradient compression on distributed training performance, focusing on sparsification and quantization techniques, including top-k, DGC, and QS…

cs.CL2017

A Survey of Deep Learning Methods for Relation Extraction

Shantanu Kumar

Relation Extraction is an important sub-task of Information Extraction which has the potential of employing deep learning (DL) models with the creation of large datasets using dist…