4 papers
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…
VOTE: Vision-Language-Action Optimization with Trajectory Ensemble Voting
Juyi Lin, Amir Taherin, Arash Akbari +11
Recent large-scale Vision Language Action (VLA) models have shown superior performance in robotic manipulation tasks guided by natural language. However, current VLA models suffer…
Cross-Platform Scaling of Vision-Language-Action Models from Edge to Cloud GPUs
Amir Taherin, Juyi Lin, Arash Akbari +5
Vision-Language-Action (VLA) models have emerged as powerful generalist policies for robotic control, yet their performance scaling across model architectures and hardware platform…
RAGs to Riches: RAG-like Few-shot Learning for Large Language Model Role-playing
Timothy Rupprecht, Enfu Nan, Arash Akbari +8
Role-playing Large language models (LLMs) are increasingly deployed in high-stakes domains such as healthcare, education, and governance, where failures can directly impact user tr…