9 papers · 1 filter
On the Diverse Dynamical Behaviors Arising in Deep Linear Transformers
Sixu Li, Thomas Jacob Maranzatto, Jan Peszek +5
We study the inference-time behavior of deep linear encoder-only transformers through the lens of interacting particle systems. In this perspective, tokens are modeled as particles…
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…
Multi-Modal Semantic Communication
Matin Mortaheb, Erciyes Karakaya, Sennur Ulukus
Semantic communication aims to transmit information most relevant to a task rather than raw data, offering significant gains in communication efficiency for applications such as te…
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…