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ML research mapped: 10 years of papers organized by topic

Latentic Labs has created a research map that organizes 10 years of machine learning papers from major conferences like ICML and NeurIPS into approximately 1,260 topics. The platform extracts benchmark records and ablation studies from tens of thousands of papers, linking each reported number back to its source. While not a definitive leaderboard due to potential comparability issues and ongoing updates, the tool aims to provide a starting point for understanding research trends, including the evolution of best reported numbers and common baselines within specific topics. AI

IMPACT Provides researchers with a structured overview of ML research trends and benchmark progress.

RANK_REASON The cluster describes a new tool that organizes and analyzes academic research papers, which falls under the research category. [lever_c_demoted from research: ic=1 ai=1.0]

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AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

ML research mapped: 10 years of papers organized by topic

How we ranked this

Signal score
4 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
The cluster describes a new tool that organizes and analyzes academic research papers, which falls under the research category. [lever_c_demoted from research: ic=1 ai=1.0]
Source corroboration
Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
paper, other
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
Breaking (< 6h)
Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

Full methodology in our editorial standards.

COVERAGE [1]

  1. r/MachineLearning TIER_1 English(EN) · /u/latenticlabs ·

    We turned 10 years of ML papers into one page per topic: benchmark records, what got tried, what reviewers expect [P]

    <!-- SC_OFF --><div class="md"><p>We've been working on this for a while and shipped it today.</p> <p>We took every accepted paper from ICML, NeurIPS, ICLR, CVPR and AAAI since 2016 (about 109k), grouped them into ~1,260 topics, and pulled the results tables and ablations out of …