PERFECT: Prompt-free and Efficient Few-shot Learning with Language Models

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Existing vehicle trajectory prediction models struggle with generalizability, prediction uncertainties, and handling complex interactions. It is often due to limitations like complex architectures customized for a specific dataset and inefficient multimoda ...

While large language models (LLMs) are increasingly playing a pivotal role in education by providing instantaneous, adaptive responses, their potential to promote critical thinking remains understudied. In this paper, we fill such a gap and present an inno ...

Decision-making permeates every aspect of human and societal development, from individuals' daily choices to the complex decisions made by communities and institutions. Central to effective decision-making is the discipline of optimization, which seeks th ...

Instruction-tuning is a widely adopted finetuning method that enables large language models (LLMs) to generate output that more closely resembles human responses. However, no studies have shown that instruction-tuning actually teaches LLMs to process langu ...

Agent-based simulations have been widely applied in many disciplines, by scientists and engineers alike. Scientists use agent-based simulations to tackle global problems, including alleviating poverty, reducing violence, and predicting the impact of pandem ...

Current machine learning models for vision are often highly specialized and limited to a single modality and task. In contrast, recent large language models exhibit a wide range of capabilities, hinting at a possibility for similarly versatile models in co ...

The high computational costs of deep convolutional neural networks hinder their deployment in real-world applications, including pulmonary nodule detection from CT scans where large 3D image sizes amplify the issue. This paper presents a novel 3D method to ...

Machine learning and data processing algorithms have been thriving in finding ways of processing and classifying information by exploiting the hidden trends of large datasets. Although these emerging computational methods have become successful in today's ...

Non-linear partial differential Kolmogorov equations are successfully used to describe a wide range of time dependent phenomena, in natural sciences, engineering or even finance. For example, in physical systems, the Allen-Cahn equation describes pattern f ...

Dynamical Systems (DS) are fundamental to the modeling and understanding time evolving phenomena, and have application in physics, biology and control. As determining an analytical description of the dynamics is often difficult, data-driven approaches are ...

Neural networks are ubiquitous in applied machine learning for education. Their pervasive success in predictive performance comes alongside a severe weakness, the lack of explainability of their decisions, especially relevant in human-centric fields. We im ...

Succinct non-interactive arguments of knowledge (SNARKs) are cryptographic proofs with strong efficiency properties. Applications of SNARKs often involve proving computations that include the SNARK verifier, a technique called recursive composition. Unfort ...

Avian flapping strategies have the potential to revolutionize future drones as they may considerably improve agility, increase slow speed flight capability, and extend the aerodynamic performance. The study of live birds is time-consuming, laborious, and, ...

Magnetic manipulation is a method used for biomedical applications to remotely control micro-robots in a contactless manner. The electromagnet manipulator should control a magnetic field with 3 degrees of freedom inside a region of interest. In various cas ...

Poor decisions and selfish behaviors give rise to seemingly intractable global problems, such as the lack of transparency in democratic processes, the spread of conspiracy theories, and the rise in greenhouse gas emissions. However, people are more predict ...

Respiration is an essential and primary mechanism for speech production. We first inhale and then produce speech while exhaling. When we run out of breath, we stop speaking and inhale. Though this process is involuntary, speech production involves a system ...

In many real world medical image classification settings we do not have access to samples of all possible disease classes, while a robust system is expected to give high performance in recognizing novel test data. We propose a generalized zero shot learnin ...

Data integration has been studied extensively for decades and approached from different angles. However, this domain still remains largely rule-driven and lacks universal automation. Recent developments in machine learning and in particular deep learning h ...

PERFECT: Prompt-free and Efficient Few-shot Learning with Language Models

Chattez avec Graph Search

Towards Generalizable Trajectory Prediction using Dual-Level Representation Learning and Adaptive Prompting

Enhancing Critical Thinking in Education by Means of a Socratic Chatbot

Reliable data-driven decision-making through optimal transport

Instruction-tuned LLMs with World Knowledge are More Aligned to the Human Brain

Generalizing Bulk-Synchronous Parallel Processing for Data Science: From Data to Threads and Agent-Based Simulations

18 GHz Ultraviolet Astrocomb via Chip-Integrated Harmonic Generation

Efficient Lung Nodule Detection via 3D Deep Learning with Shifted Convolutions

2D Nanosystems: Applications of 2D Semiconductors for In-Memory Computing

Solving Non-linear Kolmogorov Equations in Large Dimensions by Using Deep Learning: A Numerical Comparison of Discretization Schemes

Linearization and Identification of Multiple-Attractor Dynamical Systems through Laplacian Eigenmaps

Evaluating the Explainers: Black-Box Explainable Machine Learning for Student Success Prediction in MOOCs

On Succinct Non-interactive Arguments in Relativized Worlds

Robotic Avian Wing Explains Aerodynamic Advantages of Wing Folding and Stroke Tilting in Flapping Flight

Topology Optimization of an Electromagnet Manipulator for 3D Uniform Magnetic Field

Reusability report: Predicting spatiotemporal nonlinear dynamics in multimode fibre optics with a recurrent neural network

Discrete-Choice Mining of Social Processes

Deep learning architectures for estimating breathing signal and respiratory parameters from speech recordings

Medical Image Classification Using Generalized Zero Shot Learning

Business Entity Matching with Siamese Graph Convolutional Networks