← Search

Bardia Mohammadi

2 accepted papers

2025

Ask in Any Modality: A Comprehensive Survey on Multimodal Retrieval-Augmented Generation

ACL 2025finding

Large Language Models (LLMs) suffer from hallucinations and outdated knowledge due to their reliance on static training data. Retrieval-Augmented Generation (RAG) mitigates these issues by integrating external dynamic information for improved factual grounding. With advances in multimodal learning,…

2025

Cache Saver: A Modular Framework for Efficient, Affordable, and Reproducible LLM Inference

EMNLP 2025

Inference constitutes the majority of costs throughout the lifecycle of a large language model (LLM). While numerous LLM inference engines focusing primarily on low-level optimizations have been developed, there is a scarcity of non-intrusive client-side frameworks that perform high-level optimizati