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Found 8 papers, 2 papers with code
Generative LLM Powered Conversational AI Application for Personalized Risk Assessment: A Case Study in COVID-19
Large language models (LLMs) have shown remarkable capabilities in various natural language tasks and are increasingly being applied in healthcare domains.
Exploring The Neural Burden In Pruned Models: An Insight Inspired By Neuroscience
Vision Transformer and its variants have been adopted in many visual tasks due to their powerful capabilities, which also bring significant challenges in computation and storage.
Learning to Poison Large Language Models During Instruction Tuning
Our work highlights the significant security risks present during the instruction tuning of LLMs and emphasizes the necessity of safeguarding LLMs against data poisoning attacks.
Hijacking Large Language Models via Adversarial In-Context Learning
In-context learning (ICL) has emerged as a powerful paradigm leveraging LLMs for specific downstream tasks by utilizing labeled examples as demonstrations (demos) in the precondition prompts.
Efficient Bottom-Up Synthesis for Programs with Local Variables
Our algorithm can reduce the space of programs with local variables.
DGP-Net: Dense Graph Prototype Network for Few-Shot SAR Target Recognition
The inevitable feature deviation of synthetic aperture radar (SAR) image due to the special imaging principle (depression angle variation) leads to poor recognition accuracy, especially in few-shot learning (FSL).
On the restriction formula
Let $\varphi$ be a quasi-psh function on a complex manifold $X$ and let $S\subset X$ be a complex submanifold.
Complex Variables
Context-aware Attention Model for Coreference Resolution
Coreference resolution is an important task for gaining more complete understanding about texts by artificial intelligence.
