Search: “research”

LxMLS 2026 is a 6-day in-person event scheduled for July 20-25 at Instituto Superior Técnico that covers machine learning topics from theory to practice for solving natural language processing problem

A developer created a visualization tool that displays GPT-2's internal concept activations in real-time during text generation, representing the model's 'thinking' process as a 3D graph that updates

A study examining 71 AI scenarios found that AI experts (N=119) and the public (N=1100) hold differing views on AI risks, benefits, and value, with experts discounting risk influences more heavily tha

The NeurIPS Creative AI track became part of the main conference proceedings for 2025, with papers presented as posters during the conference , marking a change from 2024 when the track was not part o

This r/MachineLearning discussion thread explores the standards and expectations reviewers and program committees use when evaluating ML papers for acceptance at top venues such as NeurIPS, ICML, and

This r/MachineLearning discussion thread focuses on the post-discussion reviewer scores for ICML 2026's dedicated Position Paper Track, where authors and community members share and compare their revi

This Reddit post on r/MachineLearning presents a community-contributed dictionary of contemporary Large Language Model (LLM) terminology, covering terms related to training, fine-tuning, inference, al

This r/MachineLearning discussion thread addresses the common and frustrating experience of receiving highly polarizing reviewer scores for ICML paper submissions — for example, one reviewer rating a

This r/MachineLearning post presents educational PyTorch implementations of FlashAttention versions 1 through 4, designed to highlight the key algorithmic differences across each iteration rather than

A bug was identified in NVIDIA's cuBLAS library where `cublasSgemmStridedBatched` dispatches the same suboptimal `cutlass_80_simt_sgemm_128x32_8x5` kernel for every batched FP32 workload from 256×...

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*AI Systems Performance Engineering* by Chris Fregly is a ~1,000-page book (published December 2025) covering GPU/CUDA kernel tuning, PyTorch optimization, distributed training, and high-throughput...

A r/MachineLearning discussion explores the challenge of finding S3-compatible object storage that can both saturate H100 GPU bandwidth and avoid AWS's egress fees during high-throughput AI trainin...

The ICML 2026 'final justification' is a **new requirement this year** where reviewers must submit a written explanation of their final recommendation after reading author rebuttals. New for ICML ...

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Applying PCA as a rotation step before naively truncating embeddings from non-Matryoshka models like BGE-M3 can recover much of the retrieval quality that is otherwise lost when simply chopping dim...

**Paramax** (also referred to as 'Parax' in the Reddit post title) is a small Python library by Daniel Ward that provides parameterizations and parameter constraints for JAX PyTrees, designed to wo...

At ICML 2026, reviewers are officially required to acknowledge authors' rebuttals — starting March 31, if authors have posted a response to an official review, the reviewer is required to acknowle...

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A beginner-friendly tutorial demonstrating how to build a ~3.2M parameter LLM from scratch using Mary Shelley's *Frankenstein* as the sole training corpus, designed to run on Kaggle's free GPU in u...

https://preview.redd.it/t7wxguxqvzth1.png?width=1314&format=png&auto=webp&s=0ba382fb88894c6e687d5bb9a4b14a85334eae67 Guess we have a dataset for sycophancy and AI content detection submitted by /u/Str

Dataset: https://huggingface.co/datasets/datasocial/tiktok-5.6B-videos If you want to explore the data without downloading billions of rows, you can query my ClickHouse database directly. It includes:

In this project, I distilled the Stockfish value function into a ResNet/ViT model using 1 billion positions from the Gigafish dataset. The 3.9 billion position dataset is available on huggingface: htt

Hey all, I don't know if you guys are experiencing the same thing, but there is this behaviour that i have been noticing on the latest models on openAI (since sol 5.6) and Anthropic since Fable 5.1 an

Something keeps happening in frontier AI, and the explanation we are given is always one size larger than the event. An OpenAI research model, running in a supposedly offline training environment, hit

Help: Project l'm building a shelf audit tool. A photo goes through YOLO, which crops each product, and then I embed the crop and search a small gallery of reference photos to get the SKU. New product

I set out to test portable Engrams and accidentally ended up testing compiled external memory instead. Am I onto something useful or reinventing a known idea? I've been building a small open research

I’m a computer engineering graduate and come from a traditional embedded systems background, with knowledge of microcontrollers, computer architecture and operating systems. Is knowledge of C and C++

we're a small lab (switzerland + south africa) and just open-sourced our first model: a 27b fine-tune of qwen3.8-27b specialized for creative writing and short-form personal text (stories, dialogue, r

I have this idea I'd like feedback on. most camera footage for training, is sunny daytime, because that's what cameras record most of the time. The edge cases models actually struggles with, like nigh

Hi everyone, The NeurIPS results aren’t out yet, but I’m expecting my paper to be rejected, so I’m considering submitting it to a journal instead. My scores were 2/3/3 (3/4/4). I feel like I would pro

GoBench evaluates LLMs on 9x9 Go games against a ladder of KataGo opponents, from random to superhuman. It measures general reasoning ability, strongly correlates with ARC-AGI 2 (r=0.83 correlation),

Two months ago I announced I had found a new dynamic quant method called Voodoo Quant which was SOTA for the most aggressive quant levels on some smaller Qwen3.5 GGUF models. I kept the methodology pr

Suppose I create two machine learning models suppose tree and neural network for a task let's suppose regression problem, now suppose I am sending both of this paper to two different journals, now the

I have created a VAE model using PyTorch on White Wine dataset. Basically, the main goal is to discover a brand-new white wine recipe. It puts all the wines into a latent space, finds the best part wh

I’ve been researching which models to sub to and I’m currently not subbed to anything. I’ve definitely searched here and other places for opinions but a lot of what I was reading wasn’t current or 6mo

DISCLAIMER I ramble a lot and am not good at focusing on documentation and or coherent thoughts. TLDR I did things I made a thing and it works for me. I will try to answer any questions. A few people

TimesFM-3 is the third generation of Google Research's zero-shot forecasting model, and the main change from 2.5 is that it handles multivariate inputs natively instead of being limited to a single se

I'm one of the co-authors of this paper. It's a seminal work in exploring the properties of 3D generated by LLMs via spatial programming. I've set up visual demonstrations of such 3D objects at: https

I recently implemented a minimal, educational version of SynthID-Text-style watermarking for language models. I saw anthropic post about how they'll start adding watermarks to their model responses an

Hello gang, I made an implementation of DSpark PC Tree (Parent conditioned drafting tree). This is an implementation of this research paper: https://arxiv.org/abs/2608.02123 Unaffiliated, just found i

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