2 citations · 3 across the 9 of their papers we have counts for
10 papers
GRASP: Generating, Revising, and Assessing for Strategic Planning with Agentic AI
Arunabh Srivastava, Mohammad A., Khojastepour +2
Large Language Models (LLMs) typically exhibit a performance profile where reliability degrades as task complexity increases. We address the challenge of generating high-quality na…
RunAgent: Interpreting Natural-Language Plans with Constraint-Guided Execution
Arunabh Srivastava, Mohammad A., Khojastepour +2
Humans solve problems by executing targeted plans, yet large language models (LLMs) remain unreliable for structured workflow execution. We propose RunAgent, a multi-agent plan exe…
Re-ranking the Context for Multimodal Retrieval Augmented Generation
Matin Mortaheb, Mohammad A. Amir Khojastepour, Srimat T. Chakradhar +1
Retrieval-augmented generation (RAG) enhances large language models (LLMs) by incorporating external knowledge to generate a response within a context with improved accuracy and re…
RAG-Check: Evaluating Multimodal Retrieval Augmented Generation Performance
Matin Mortaheb, Mohammad A. Amir Khojastepour, Srimat T. Chakradhar +1
Retrieval-augmented generation (RAG) improves large language models (LLMs) by using external knowledge to guide response generation, reducing hallucinations. However, RAG, particul…
Efficient Semantic Communication Through Transformer-Aided Compression
Matin Mortaheb, Mohammad A. Amir Khojastepour, Sennur Ulukus
Transformers, known for their attention mechanisms, have proven highly effective in focusing on critical elements within complex data. This feature can effectively be used to addre…
Transformer-Aided Semantic Communications
Matin Mortaheb, Erciyes Karakaya, Mohammad A. Amir Khojastepour +1
The transformer structure employed in large language models (LLMs), as a specialized category of deep neural networks (DNNs) featuring attention mechanisms, stands out for their ab…
Deep Learning-Based Real-Time Quality Control of Standard Video Compression for Live Streaming
Matin Mortaheb, Mohammad A. Amir Khojastepour, Srimat T. Chakradhar +1
Ensuring high-quality video content for wireless users has become increasingly vital. Nevertheless, maintaining a consistent level of video quality faces challenges due to the fluc…
Deep Learning-Based Real-Time Rate Control for Live Streaming on Wireless Networks
Matin Mortaheb, Mohammad A. Amir Khojastepour, Srimat T. Chakradhar +1
Providing wireless users with high-quality video content has become increasingly important. However, ensuring consistent video quality poses challenges due to variable encoded bitr…
Semantic Multi-Resolution Communications
Matin Mortaheb, Mohammad A. Amir Khojastepour, Srimat T. Chakradhar +1
Deep learning based joint source-channel coding (JSCC) has demonstrated significant advancements in data reconstruction compared to separate source-channel coding (SSCC). This supe…
Codebook Design for Composite Beamforming in Next-generation mmWave Systems
Nariman Torkzaban, Mohamamd A., Khojastepour +1
In pursuance of the unused spectrum in higher frequencies, millimeter wave (mmWave) bands have a pivotal role. However, the high path-loss and poor scattering associated with mmWav…