Papers by Bardia Mohammadi

2 papers
Ask in Any Modality: A Comprehensive Survey on Multimodal Retrieval-Augmented Generation (2025.findings-acl)

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Challenge: Large Language Models (LLMs) suffer from hallucinations and outdated knowledge due to their reliance on static training data.
Approach: They review training strategies, robustness enhancements, loss functions, and agent-based approaches and outline open challenges and future directions to guide research in this evolving field.
Outcome: The proposed model improves accuracy and accuracy while integrating external dynamic information for improved factual grounding.
Cache Saver: A Modular Framework for Efficient, Affordable, and Reproducible LLM Inference (2025.findings-emnlp)

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Challenge: Inference is the major cost throughout the lifecycle of a large language model (LLM).
Approach: They propose a plug-and-play, asynchronous framework that facilitates high-level inference optimizations.
Outcome: The proposed framework reduces cost and CO2 by 35% across methods, tasks, and LLMs.

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