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Found 10 papers, 5 papers with code
Can ChatGPT Read Who You Are?
We compare the personality trait estimations made by ChatGPT against those by human raters and report ChatGPT's competitive performance in inferring personality traits from text.
A Security Risk Taxonomy for Large Language Models
As large language models (LLMs) permeate more and more applications, an assessment of their associated security risks becomes increasingly necessary.
Beyond the Safeguards: Exploring the Security Risks of ChatGPT
The increasing popularity of large language models (LLMs) such as ChatGPT has led to growing concerns about their safety, security risks, and ethical implications.
Toward Physically Plausible Data-Driven Models: A Novel Neural Network Approach to Symbolic Regression
Symbolic regression is a method that can automatically generate such models from data.
SymFormer: End-to-end symbolic regression using transformer-based architecture
The task of finding formulas from a set of observed inputs and outputs is called symbolic regression.
ViewFormer: NeRF-free Neural Rendering from Few Images Using Transformers
We propose a 2D-only method that maps multiple context views and a query pose to a new image in a single pass of a neural network.
Visual Navigation in Real-World Indoor Environments Using End-to-End Deep Reinforcement Learning
This precludes the use of the learned policy on a real robot.
Vision-based Navigation Using Deep Reinforcement Learning
However, the application of deep RL to visual navigation with realistic environments is a challenging task.
Constructing Parsimonious Analytic Models for Dynamic Systems via Symbolic Regression
We demonstrate on a real pendulum system that the analytic model found enables a RL controller to successfully perform the swing-up task, based on a model constructed from only 100 data samples.
Symbolic Regression Methods for Reinforcement Learning
Reinforcement learning algorithms can solve dynamic decision-making and optimal control problems.
