5 citations · 5 across the 9 of their papers we have counts for
10 papers
Receiver Decides Agent-to-Agent Negotiations
Fardeen Sadab, Alif Hasnain, Afsana Shehrin +2
When one language-model agent asks another for money, which of the two decides how much changes hands? We ran a round-robin tournament of 1,049 negotiations among fifteen agents. I…
Routing Is Not Enough: Diagnosing Intra-Adapter Subspace Contention in MoE+LoRA Fine-Tuning
Mehreen Hossain Chowdhury, Nowshin Mahjabin, Ahmed Shafin Ruhan +3
Multi-domain fine-tuning often combines MoE routing with LoRA, assuming that token-level routing separates domain-specific updates. We test this assumption in MoE+LoRA using Python…
UnDA: Unpaired Domain Alignment for Cross-Modal Knowledge Transfer in Medical Imaging
Rafsan Jany, Shadab Tanjeed Ahmad, Ahsan Bulbul +3
Multimodal based approaches often outperform single modality approaches in downstream tasks as the different modalities provide complementary information, yet acquiring paired clin…
SleepExplain: Explainable Non-Rapid Eye Movement and Rapid Eye Movement Sleep Stage Classification from EEG Signal
Rafsan Jany, Md. Hamjajul Ashmafee, Iqram Hussain +1
Classification of sleep stages is one of the most important diagnostic approaches for a variety of sleep-related disorders. Electroencephalography (EEG) is regarded as a powerful t…
Probabilistic Feature Imputation and Uncertainty-Aware Multimodal Federated Aggregation
Nafis Fuad Shahid, Maroof Ahmed, Md Akib Haider +3
Multimodal federated learning enables privacy-preserving collaborative model training across healthcare institutions. However, a fundamental challenge arises from modality heteroge…
Progressive Code Integration for Abstractive Bug Report Summarization
Shaira Sadia Karim, Abrar Mahmud Rahim, Lamia Alam +4
Bug reports are often unstructured and verbose, making it challenging for developers to efficiently comprehend software issues. Existing summarization approaches typically rely on…
Personalized Federated Segmentation with Shared Feature Aggregation and Boundary-Focused Calibration
Ishmam Tashdeed, Md. Atiqur Rahman, Sabrina Islam +1
Personalized federated learning (PFL) possesses the unique capability of preserving data confidentiality among clients while tackling the data heterogeneity problem of non-independ…
AntiFLipper: A Secure and Efficient Defense Against Label-Flipping Attacks in Federated Learning
Aashnan Rahman, Abid Hasan, Sherajul Arifin +5
Federated learning (FL) enables privacy-preserving model training by keeping data decentralized. However, it remains vulnerable to label-flipping attacks, where malicious clients m…
FedStrategist: A Meta-Learning Framework for Adaptive and Robust Aggregation in Federated Learning
Md Rafid Haque, Abu Raihan Mostofa Kamal, Md. Azam Hossain
Federated Learning (FL) offers a paradigm for privacy-preserving collaborative AI, but its decentralized nature creates significant vulnerabilities to model poisoning attacks. Whil…
BnSentMix: A Diverse Bengali-English Code-Mixed Dataset for Sentiment Analysis
Sadia Alam, Md Farhan Ishmam, Navid Hasin Alvee +3
The widespread availability of code-mixed data can provide valuable insights into low-resource languages like Bengali, which have limited datasets. Sentiment analysis has been a fu…