2 citations · 2 across the 5 of their papers we have counts for
5 papers
RAGMark: A Comprehensive Framework for Benchmarking Retrieval-Augmented Generation Systems
Zlatan Feric, Amir Taherin, Bin Ren +3
We present RAGMark, a modular benchmarking framework for advanced Retrieval-Augmented Generation (RAG) systems targeting small-scale multi-GPU environments. RAGMark evaluates diver…
Hydra: Phase-Aware Workload Characterization of LLM Inference across Edge SoC Generations, Backends, and Quantization Levels
Amir Taherin, Sana Taghipour Anvari, Charles Amante +9
Edge LLM deployment is shaped by more than model size and precision: inference backend, hardware platform, memory traffic, and power management all affect latency and efficiency. W…
From Retrieved Context to Runtime Control: Adaptive Compression for Edge-based RAG
Zlatan Feric, Amir Taherin, Yanzhi Wang +1
Retrieval-augmented generation (RAG) improves language-model responses by grounding generation in external passages, which comes with overhead: retrieved context lengthens the prom…
Using Undersampling with Ensemble Learning to Identify Factors Contributing to Preterm Birth
Shi Dong, Zlatan Feric, Guangyu Li +10
In this paper, we propose Ensemble Learning models to identify factors contributing to preterm birth. Our work leverages a rich dataset collected by a NIEHS P42 Center that is tryi…
Learning Disentangled Representations of Video with Missing Data
Armand Comas-Massagué, Chi Zhang, Zlatan Feric +2
Missing data poses significant challenges while learning representations of video sequences. We present Disentangled Imputed Video autoEncoder (DIVE), a deep generative model that…