2 citations · 5 across the 8 of their papers we have counts for
8 papers
Learning What to Retain: Gated-Memory Routing for Efficient Collaboration in Multi-Agent LLM Systems
Rakibul Hasan Rajib, Mengxin Zheng, Qian Lou
Large language model (LLM)-based multi-agent systems tackle complex reasoning by orchestrating how multiple agents are configured and how they collaborate. A central challenge is t…
AgentServeSim: Serving-System Simulation and Policy Search for LLM Agent Programs
Rakibul Hasan Rajib, Mengxin Zheng, Qian Lou
Large language model agents execute programs comprising multiple model turns interleaved with external tool calls. Their job completion time depends on how the serving system retai…
pFedBBN: A Personalized Federated Test-Time Adaptation with Balanced Batch Normalization for Class-Imbalanced Data
Md Akil Raihan Iftee, Syed Md. Ahnaf Hasan, Mir Sazzat Hossain +5
Test-time adaptation (TTA) in federated learning (FL) is crucial for handling unseen data distributions across clients, particularly when faced with domain shifts and skewed class…
BD Open LULC Map: High-resolution land use land cover mapping & benchmarking for urban development in Dhaka, Bangladesh
Mir Sazzat Hossain, Ovi Paul, Md Akil Raihan Iftee +7
Land Use Land Cover (LULC) mapping using deep learning significantly enhances the reliability of LULC classification, aiding in understanding geography, socioeconomic conditions, p…
RGC-Bent: A Novel Dataset for Bent Radio Galaxy Classification
Mir Sazzat Hossain, Khan Muhammad Bin Asad, Payaswini Saikia +7
We introduce a novel machine learning dataset tailored for the classification of bent radio active galactic nuclei (AGN) in astronomical observations. Bent radio AGN, distinguished…
FedCTTA: A Collaborative Approach to Continual Test-Time Adaptation in Federated Learning
Rakibul Hasan Rajib, Md Akil Raihan Iftee, Mir Sazzat Hossain +4
Federated Learning (FL) enables collaborative model training across distributed clients without sharing raw data, making it ideal for privacy-sensitive applications. However, FL mo…
Synthetic Speech Classification: IEEE Signal Processing Cup 2022 challenge
Mahieyin Rahmun, Rafat Hasan Khan, Tanjim Taharat Aurpa +5
The aim of this project is to implement and design arobust synthetic speech classifier for the IEEE Signal ProcessingCup 2022 challenge. Here, we learn a synthetic speech attributi…
BD-SAT: High-resolution Land Use Land Cover Dataset & Benchmark Results for Developing Division: Dhaka, BD
Ovi Paul, Abu Bakar Siddik Nayem, Anis Sarker +3
Land Use Land Cover (LULC) analysis on satellite images using deep learning-based methods is significantly helpful in understanding the geography, socio-economic conditions, povert…