Search: “r-machinelearning”

Hey everyone! I wanted to share something I’ve been working on. I was inspired by projects from DeepMind and OpenAI, but noticed that most games are prohibitively difficult to integrate with an agent

The preprint can be accessed via the following link: https://arxiv.org/abs/2608.12408 (q-bio.NC / cs.LG). And for the code: https://github.com/nilsleut/evaluation-resolution-rsa The following assertio

A premise: I hope this question is 'worth' of this subreddit, I did a decent amount of research before posting, I thought it was potentially interesting enough for it, but possibly not basic enough fo

I have a big database of local court decisions with a legal sentence which is like a paragraph summary of the doc. I've been tinkering with FTing for many days now, all results inconclusive never beat

Links: Preprint: https://doi.org/10.5281/zenodo.22028087 Entropic Scree Function v1.0.0 / GitHub: https://github.com/tjleestjohn/Entropic-Scree TL;DR: Standard PCA fundamentally fractures non-linear d

Worked some time ago on one of the ad teams at Yahoo, and this grew out of a question I kept returning to while there are there 'simple' models that are both simple, scalable, interpretable, and contr

I’ve been looking at a fairly basic question in weight-space learning that I don’t think gets separated cleanly enough: Why does reading semantics directly from neural network weights work pretty well

I trained three LLMs from scratch in raw PyTorch then post-trained each one with SFT and then GRPO. Same process every time: same synthetic arithmetic curriculum, same reward function, same hyperparam

Original Article - https://x.com/p_nawrot/status/2089315591010079034 I've spent the last few years working on efficient attention and KV Cache Compression. I've read many papers, dug deep into referen

There’s a hands-on workshop on August 29 that builds and benchmarks this properly, end to end, using entirely open models, no API calls involved. Led by Ben Auffarth, AI Consultant and Founder of Chel

Been working on this for the last few months. I've been working on PyTorch for the past few years and I always felt, many a times my work went into dump, because of some mistakes I made in the code. t

Hey everyone, I'm trying to get a better sense of where classic ML fits in the current landscape, dominated by LLMs and deep learning. Are supervised and unsupervised learning still considered importa

I may have stumbled onto something interesting while trying to figure out a recurring artifact in ChatGPT image generation and editing (maybe applicable to other models as well?). It started with a ve

I’m working on performance regression detection using machine learning/anomaly detection. My setup is basically: Healthy runs are used to learn normal behaviour Regression runs are used to see whether

I've been building an open-source tool for diagnosing world models, the kind that predict future frames from a starting context and a sequence of actions. It compares a rollout against ground truth an

Back after ~6 months — rebuilding my spiking language model around CPU-first inference Hey everyone. It’s been around six months since I last posted anything about this project here. Some of you might

Link: https://arxiv.org/pdf/2604.27883 Hi, Most of use are familiar with the headache of training a neural network using gradient descent where the training error may go to zero but the test error may

I am working on an AI for a small single-player merge puzzle and would appreciate pointers to related algorithms, papers, or existing implementations. It resembles 2048 in its action -> afterstate ->

Hello all, I am wondering if a transition from a Ph.D. in electrical engineering (Quantum optics/photonics) to a job in ML is a reasonable aspiration. Personally, I have extensive software development

Hey everyone - we've been building something particularly relevant to ML at large - The Agentic World Cup - a platform where Agents compete in sports. As you know, today's Agents can code, do math, an

Today the most important factor in AI is cost. My idea is to split ML models inference (closed ones, proprietary) across server and edge computing on clients, and I would like to hear what do you thin

Obviously nobody needs a transformer that's good at multiplication. I wanted to know whether a stock transformer could do exact arithmetic if I chose its weights directly. I implemented the grade-scho

I am trying to learn concepts like On Policy Distillation (OPD), On Policy Self Distillation (OPSD) and how do they compare to RL algorithms like GRPO. There are a lot of papers on this, but because o

It's an encoder-only transformer that consumes past(blood glucose + carbs + insulin) and future(carbs + insulin) and predicts future blood glucose for the next 2 hours. Announced meals and boluses/bas

Kimi K3 by Moonshot reached the frontier as an open-weight model. Artificial Analysis ranks it fourth of 580 models, behind only Claude Opus 5, Fable 5, and GPT-5.6 Sol. Moonshot released more than th

Hey everyone, I recently open-sourced a new Python package called ganfs (Generative Adversarial Network Feature Selection), and I wanted to share it with the community. The Problem: Selecting the best

I've always found it a little strange that AI is everywhere, but the codecs we use in practice are the traditional hand-engineered systems like h.264, h.265, av1. Alexnet started the wave of neural ne

We developed a leaderboard ranking frontier model security. There's no shortage of model capability rankings, but we didn't find anything comparable for model security. Yet security is becoming increa

While building this workflow a thing that surprised me was that, initially I thought the pipeline was complete: From Goal to → Decompose → Research → Specification → Implementation It successfully bro

I work on PostSlate, a video editing tool, and this comes out of our own work. We run ML models on-device, face detection and embedding among other things, which means we can't assume anything about t

ML research is progressing at breakneck speed where frontier labs in both academia and industry have access to considerably large computes (GPUs). Where do small labs or independent researchers go in

My data set is a list of images, each equipped with a a couple sentences of text. A user would search primarily with text only. My default approach is using BM25, but how would I facilitate searching

Hello guys. I found some problems in current frontier models. And want to share. # math_code_hallucination > Record of a failure caused by combining mathematics and code in a single prompt. --- ## Cas

I'm really confused about what the point of the prompt injection was (speaking as an author). Is it just a study? I would really prefer that they took action against the AI-generated reviews. Obviousl

One of the papers I reviewed has what seems to be entirely LLM-generated rebuttals, and the original paper is also clearly LLM-generated, with Claude-speak everywhere. While the authors acknowledge LL

TL;DR: Most RL post-training algorithms optimize the current batch and move on. But after an update, did the new policy actually become better? We introduce Policy Improvement Reinforcement Learning (

Largest empirical study of AI penetration in academic publishing ever conducted—51%-by-2025 is the most authoritative quantitative marker yet of how thoroughly LLMs have reshaped scientific writing, a

Hi everyone! 👋 I built and trained the complete Transformer architecture from scratch using pure PyTorch (`torch.nn` primitives) based on the original 'Attention Is All You Need' paper. I trained the

This was my Bachelor's Final Project: implementing YOLO26n inference completely from scratch using ARM64 Assembly Language and C, without relying on existing inference frameworks. The goal was to unde

I'm a software engineer who mainly builds softwaes/applications, and I'm starting to work on machine learning projects. Since ML workloads often require GPUs, I know services like Google Colab and Kag

NOTE -> I expect answer from people who actually have experience and strong understanding of these. please give something beneficial. I'm building a SaaS platform in Sri Lanka that handles documents a

I have been running some experiments with smaller open-weight LLMs on multiple-choice questions of Swedish medical licensing exams. On a dataset called MedQA-SWE, GPT-4 scored 84% accuracy in 2024 and

Hey everyone, I have been looking into how people source compute for their Inference workloads (and in general). I wanted to understand some specific pain points here. If you've used online services l

There are a few reasons why problems from International Mathematical Olympiad function as a good benchmark for LLMs: - The problems are new, not included in the training data of any model - Hard math

I've been chasing the question of what algorithms a transformer can actually express -- separate from what it can learn. So I built a compiler: define a computation graph in ordinary Python, and it pr

Built an open-source AI coding agent that was 7%–75% cheaper than a cold 'claude -p' run on 6/6 well-localized tasks across repositories up to ~82k LOC. The biggest difference: Cold agent: 6.83, 207 t