A Deep Generative Model for Synthesizing Labeled Wireless Signals
A Deep Generative Model for Synthesizing Labeled Wireless Signals Wireless sensing technologies—such as those used for indoor localization, the Internet of T...
A Deep Generative Model for Synthesizing Labeled Wireless Signals Wireless sensing technologies—such as those used for indoor localization, the Internet of T...
Don't Drop Dropout: Optimizing Layer Sparsity for Efficient LLM Training and Inference This research investigates the role of "layer dropout"—a technique tha...
Commonsense Reasoning in Computer Vision: Foundations, Recent Advancements, and Future Directions This paper provides a comprehensive survey of how researche...
AI is fundamentally changing how researchers conduct design science, yet there has been a lack of clear guidance on how to integrate AI into the research pro...
Does Your Agent's Memory Survive a Model Upgrade? A Controlled Study of Memory Portability investigates the hidden risks of upgrading the AI models that powe...
Necessary or Sufficient? Evaluating LLM Explanations With Behavioural Evidence This research investigates whether the explanations provided by Large Language...
Large Language Models for HVAC Operations in Building Energy Systems: A Critical Review of Methods, Applications, and Deployment Readiness This paper provide...
Beyond Aggregate Scores: Behavioral Correctness Assumptions for Assessing Reference-Based Automatic Evaluation Methods This paper introduces a new diagnostic...
RISE: Recursive Improvement via Self-Extrapolating Policy Distillation RISE is a new training method designed to help language models improve themselves recu...
Quantum circuits are essential for running quantum algorithms, but they require Boolean functions to be implemented in a reversible way.