Articles for category: AI Research

March 4, 2025

ikayaniaamirshahzad@gmail.com

Optimizing LLM Test-Time Compute Involves Solving a Meta-RL Problem – Machine Learning Blog | ML@CMU

Figure 1: Training models to optimize test-time compute and learn “how to discover” correct responses, as opposed to the traditional learning paradigm of learning “what answer” to output. The major strategy to improve large language models (LLMs) thus far has been to use more and more high-quality data for supervised fine-tuning (SFT) or reinforcement learning (RL). Unfortunately, it seems this form of scaling will soon hit a wall, with the scaling laws for pre-training plateauing, and with reports that high-quality text data for training maybe exhausted by 2028, particularly for more difficult tasks, like solving reasoning problems which seems to

March 4, 2025

ikayaniaamirshahzad@gmail.com

Reddit – Dive into anything

We value your privacy Reddit and its partners use cookies and similar technologies to provide you with a better experience. By accepting all cookies, you agree to our use of cookies to deliver and maintain our services and site, improve the quality of Reddit, personalize Reddit content and advertising, and measure the effectiveness of advertising. By rejecting non-essential cookies, Reddit may still use certain cookies to ensure the proper functionality of our platform. For more information, please see our Cookie Notice and our Privacy Policy. Source link

March 4, 2025

ikayaniaamirshahzad@gmail.com

Reddit – Dive into anything

We value your privacy Reddit and its partners use cookies and similar technologies to provide you with a better experience. By accepting all cookies, you agree to our use of cookies to deliver and maintain our services and site, improve the quality of Reddit, personalize Reddit content and advertising, and measure the effectiveness of advertising. By rejecting non-essential cookies, Reddit may still use certain cookies to ensure the proper functionality of our platform. For more information, please see our Cookie Notice and our Privacy Policy. Source link

March 4, 2025

ikayaniaamirshahzad@gmail.com

Reddit – Dive into anything

We value your privacy Reddit and its partners use cookies and similar technologies to provide you with a better experience. By accepting all cookies, you agree to our use of cookies to deliver and maintain our services and site, improve the quality of Reddit, personalize Reddit content and advertising, and measure the effectiveness of advertising. By rejecting non-essential cookies, Reddit may still use certain cookies to ensure the proper functionality of our platform. For more information, please see our Cookie Notice and our Privacy Policy. Source link

March 4, 2025

ikayaniaamirshahzad@gmail.com

Reddit – Dive into anything

We value your privacy Reddit and its partners use cookies and similar technologies to provide you with a better experience. By accepting all cookies, you agree to our use of cookies to deliver and maintain our services and site, improve the quality of Reddit, personalize Reddit content and advertising, and measure the effectiveness of advertising. By rejecting non-essential cookies, Reddit may still use certain cookies to ensure the proper functionality of our platform. For more information, please see our Cookie Notice and our Privacy Policy. Source link

March 4, 2025

ikayaniaamirshahzad@gmail.com

Reddit – Dive into anything

We value your privacy Reddit and its partners use cookies and similar technologies to provide you with a better experience. By accepting all cookies, you agree to our use of cookies to deliver and maintain our services and site, improve the quality of Reddit, personalize Reddit content and advertising, and measure the effectiveness of advertising. By rejecting non-essential cookies, Reddit may still use certain cookies to ensure the proper functionality of our platform. For more information, please see our Cookie Notice and our Privacy Policy. Source link

March 4, 2025

ikayaniaamirshahzad@gmail.com

[D] LF Data annotators for machine learning

Hey everyone! I’m working on a computer vision project that’s giving me a bit of a headache. I’m building a custom object detection model for a pretty niche use case: identifying and classifying industrial machine parts (screws, bolts, and custom components) in low-light factory environments. It’s not something I can just pull off the shelf from a public dataset, and automated labeling tools are struggling because the parts are often overlapping, partially obscured, or look super similar to each other. After wrestling with this for a while, I’ve come to the conclusion that I need to go the manual labeling

March 4, 2025

ikayaniaamirshahzad@gmail.com

Probabilistic time series forecasting with compositional bayesian neural networks

AutoBNN is based on a line of research that over the past decade has yielded improved predictive accuracy by modeling time series using GPs with learned kernel structures. The kernel function of a GP encodes assumptions about the function being modeled, such as the presence of trends, periodicity or noise. With learned GP kernels, the kernel function is defined compositionally: it is either a base kernel (such as Linear, Quadratic, Periodic, Matérn or ExponentiatedQuadratic) or a composite that combines two or more kernel functions using operators such as Addition, Multiplication, or ChangePoint. This compositional kernel structure serves two related purposes.

March 4, 2025

ikayaniaamirshahzad@gmail.com

Exploring the structural changes driving protein function with BioEmu-1

From forming muscle fibers to protecting us from disease, proteins play an essential role in almost all biological processes in humans and other life forms alike. There has been extraordinary progress in recent years toward better understanding protein structures using deep learning, enabling the accurate prediction of protein structures from their amino acid sequences. However, predicting a single protein structure from its amino acid sequence is like looking at a single frame of a movie—it offers only a snapshot of a highly flexible molecule. Biomolecular Emulator-1 (BioEmu-1) is a deep-learning model that provides scientists with a glimpse into the rich world of

March 4, 2025

ikayaniaamirshahzad@gmail.com

A Gentle Introduction to Graph Neural Networks

This article is one of two Distill publications about graph neural networks. Take a look at Understanding Convolutions on Graphs to understand how convolutions over images generalize naturally to convolutions over graphs. Graphs are all around us; real world objects are often defined in terms of their connections to other things. A set of objects, and the connections between them, are naturally expressed as a graph. Researchers have developed neural networks that operate on graph data (called graph neural networks, or GNNs) for over a decade. Recent developments have increased their capabilities and expressive power. We are starting to see