Search Results for author:
Found 6 papers, 3 papers with code
AdaMoLE: Fine-Tuning Large Language Models with Adaptive Mixture of Low-Rank Adaptation Experts
We introduce AdaMoLE, a novel method for fine-tuning large language models (LLMs) through an Adaptive Mixture of Low-Rank Adaptation (LoRA) Experts.
Application of Neural Ordinary Differential Equations for Tokamak Plasma Dynamics Analysis
In the quest for controlled thermonuclear fusion, tokamaks present complex challenges in understanding burning plasma dynamics.
SecQA: A Concise Question-Answering Dataset for Evaluating Large Language Models in Computer Security
In this paper, we introduce SecQA, a novel dataset tailored for evaluating the performance of Large Language Models (LLMs) in the domain of computer security.
Anomaly Detection of Command Shell Sessions based on DistilBERT: Unsupervised and Supervised Approaches
This work highlights the potential of leveraging recent advances in transformers to address important computer security challenges.
Deep Reinforcement Learning based Group Recommender System
The DRGR model is applied on the MovieLens-Rand dataset with two baselines.
Yelp Review Rating Prediction: Machine Learning and Deep Learning Models
We predict restaurant ratings from Yelp reviews based on Yelp Open Dataset.
