Ross ROSS = Recommend OSS · open-source software intelligence for agents

RedditSota/state-of-the-art-result-for-machine-learning-problems resource

This repository provides state of the art (SoTA) results for all machine learning problems. We do our best to keep this repository up to date. If you do find a problem's SoTA result is out of date or missing, please raise this as an issue or submit Google form (with this information: research paper name, dataset, metric, source code and year). We will fix it immediately. observed · 2026-08-28

github.com/RedditSota/state-of-the-art-result-for-machine-learning-problems · Apache-2.0 (permissive) observed · 2026-08-28

Health v2 · maintenance only

32/100

  • Activity 0
  • Release rhythm 35
  • Longevity 100

Flags: no_releases

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 3220
  • days_rel: n/a
  • days_push: 2626
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

8892 stars · 1293 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A curated repository tracking state-of-the-art (SoTA) results across machine learning problems, organized by learning paradigm (supervised, semi-supervised, unsupervised, transfer, reinforcement learning). Each entry lists research papers, datasets, metrics, source code links, and years.

Use cases

  • find the state-of-the-art result for a machine learning benchmark
  • look up best performing models on datasets like ImageNet or WikiText
  • find research papers that achieved SoTA on a task
  • check which model holds the record for language modeling perplexity
  • discover source code implementations of top-performing ML papers
  • compare benchmark metrics across computer vision and NLP tasks

When to choose

  • you need a quick reference for current SoTA results across many ML tasks
  • you want paper, dataset, metric, and code links in one place
  • you are surveying progress in NLP, computer vision, speech, or reinforcement learning

When to avoid

  • you need guaranteed up-to-date leaderboards (last update was February 2019)
  • you need a runnable tool or library rather than a reference list
  • you need exhaustive coverage of niche subfields or recent benchmarks

Facets

learning-resource · maturity maintenance

machine-learning nlp computer-vision speech-recognition reinforcement-learning machine-learning deep-learning computer-vision artificial-intelligence awesome-lists cross-platform state-of-the-art benchmark-results research-papers leaderboard curated-list natural-language-processing

1 source

Member repositories

For agents

markdown · JSON · MCP: product_card(name="RedditSota/state-of-the-art-result-for-machine-learning-problems")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem