Vector Ridge Lab

A living map of what we've reproduced from the state of the art.

Every node is a paper we read, scored and turned into a working proof of concept — usually within a day of publication. Spin the world, pick a region, open a demo.

53proofs of concept
6regions
latest:
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Your integration plan

Turn the map into a plan

The map above matches by keywords. Here an AI reviews your description against every proof of concept, explains how each technique applies to your case, and gives you one prompt for your coding agent with your context and the references already in it.

Your project

Example: we are a logistics company with 13 trucks. Drivers deviate from routes and we pay extra tolls. We have GPS data in Postgres and a small Python team.

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The search is free, up to 6 requests a day. We ask who you are so we can follow up if a technique fits; we don't share your data or send newsletters.

By searching you agree that Vector Ridge Labs may contact you about this project.

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See how the Lab works

Agents read the research and build the demos. Two independent gates decide what ships. Watch a paper become a live demo, step by step.

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  • POC-053 · 26 Oct 20268/10
    MemoryTax

    MemoryTax: when is an agent memory layer worth paying for? (Shanghai Jiao Tong)

  • POC-052 · 19 Oct 20268/10
    Next-Concept Modeling

    Next-Concept Modeling (NCM): Stanford's Coarse-to-Fine Hierarchical Text Generation

  • POC-051 · 16 Oct 20268/10
    Muse Spark Open

    Muse Spark Open: Meta Drops 816B MoE Model — 42B Active Params, 1M Context, Runs Locally on Two Mac Studios

  • POC-050 · 15 Oct 20269/10
    Fork-and-Flush Agents

    Fork-and-Flush: Simple Trick Boosts Research Agents 66% by Escaping Idea Ruts

  • POC-049 · 12 Oct 20269/10
    KV Cache Multi-Model Agents

    KV cache techniques for faster, cheaper multi-model AI agents

  • POC-048 · 8 Oct 20269/10
    EmbeddingGemma 2

    Unsloth releases quantized EmbeddingGemma 2 with multimodal support for text, audio, and video

  • POC-047 · 5 Oct 20269/10
    Darwin Gödel Machine

    How AI Agents Are Learning to Rewrite Their Own Stack

  • POC-046 · 2 Oct 20268/10
    CLM

    New method lets LLMs manage their own context, beating human-designed strategies by 47.6%

  • POC-045 · 1 Oct 20269/10
    PageIndex

    Tree search framework hits 98.7% on documents where vector search fails

  • POC-044 · 30 Sept 20269/10
    ScientistTwo

    Google's autonomous research agent outperforms human papers on 86 tasks by 25%

  • POC-043 · 29 Sept 20268/10
    Claude Science

    Claude breaks physics world record by solving nine-loop particle calculation unsupervised

  • POC-042 · 28 Sept 20269/10
    System One

    System One Models: Jev / Laya / CLM-8B — Fast Typed AI Decisions for Production Stacks

  • POC-041 · 26 Sept 20268/10
    MAttr

    New attribution method tops interpretability benchmark by 2.9x, pinpoints Llama refusals to 1% of weights

  • POC-040 · 24 Sept 20269/10
    Claude 950 Agents

    950 Claude Agents Ran Overnight and Rewrote Biology's Rulebook

  • POC-039 · 22 Sept 20269/10
    Talking Agents

    Talking AI agents beat solo agents 4-to-1 on hard reasoning tasks

  • POC-038 · 18 Sept 20268/10
    Jev Memory Compaction

    TypesafeAI's Jev speeds up memory compaction by scoring and dropping irrelevant tool calls

  • POC-037 · 17 Sept 20268/10
    Dream-RSI

    Google DeepMind's self-improving agent cuts AI search costs by up to 162x

  • POC-036 · 16 Sept 20268/10
    Denoising Looped Models

    New denoising trick trains looped models to hit 58.8% on ARC-AGI-1

  • POC-035 · 14 Sept 20269/10
    DeepSeek V4.1-Flash

    DeepSeek V4.1-Flash Architecture Deep-Dive: CED + CSA2 + Bounded Replay + Hierarchical Indexer

  • POC-034 · 10 Sept 20268/10
    TOC-Guided Retrieval

    New retrieval model uses table of contents to hit 82.6% recall with near-zero hallucination

  • POC-033 · 9 Sept 20269/10
    Meta AIRA3

    Meta's autonomous research system places top 10 among 4,000 Kaggle teams

  • POC-032 · 8 Sept 20268/10
    DeepMind Swarm

    Google DeepMind's 100-agent swarm spontaneously split into cheaters and whistleblowers

  • POC-031 · 7 Sept 20268/10
    Shopify Flywheel

    Shopify's self-improving AI pipeline: 0.8B model beats GPT-5.6, $27M→$1M cost

  • POC-030 · 6 Sept 20268/10
    Symbolic Structure in LLM Vectors

    8-year study finds LLMs secretly build symbolic structure inside their vectors

  • POC-029 · 5 Sept 20268/10
    Uncertainty Calibration

    Google's new training trick makes LLMs know what they don't know

  • POC-028 · 4 Sept 20269/10
    Agent Wiki

    Google's framework lets small AI agents outperform models 3x their size using a persistent knowledge wiki

  • POC-027 · 3 Sept 20269/10
    Skill Team

    Anthropic hackathon winner open-sources a 68-agent, 286-skill engineering team built on Claude

  • POC-026 · 31 Aug 20268/10
    Agent Escape

    Agents Can Escape: Trail of Bits VM escape + OpenAI-HuggingFace breach analysis

  • POC-025 · 26 Aug 20268/10
    Prime Intellect Harness

    Prime Intellect open-source agent harness boosts ARC-AGI-3 from 30% to 95.5%

  • POC-024 · 25 Aug 20268/10
    Prune+Spill

    Pi's coding agent cuts context costs 88% by spilling tool output to disk

  • POC-023 · 24 Aug 20268/10
    Agent Skills

    AI agent skills: Why they succeed — and what causes them to crash

  • POC-022 · 22 Aug 20268/10
    Matryoshka LM

    Matryoshka Language Model — 36% Compute Savings

  • POC-021 · 21 Aug 20268/10
    LLMs vs Embeddings

    LLMs beat embedding models but cost up to 1,431x more, study finds

  • POC-020 · 19 Aug 20268/10
    Self-Verify

    Stanford's Self-Verification Trick: DeepSeek 11x Cheaper on Coding Benchmarks

  • POC-019 · 18 Aug 20268/10
    Mind Virus Propagation

    AI 'Mind Viruses': Adversarial Prompt Propagation in Multi-Agent Networks

  • POC-018 · 17 Aug 20269/10
    Agent Security

    The 3-layer security stack for AI agents (NemoClaw + NanoClaw + CrabTrap)

  • POC-017 · 22 Jul 20268/10
    PromptShield

    PromptShield: Protecting User Privacy in AI Chatbots

  • POC-016 · 12 Jul 20268/10
    HuntGPT

    HuntGPT: Integrating Machine Learning-Based Anomaly Detection and Explainable AI with Large Language Models

  • POC-015 · 11 Jul 20268/10
    ElementBERT

    Semantic Embeddings of Chemical Elements for Enhanced Materials Inference and Discovery

  • POC-014 · 8 Jul 20269/10
    Self-Harness

    Self-Harness & HarnessX: Why self-improving harnesses are the next frontier for AI developers

  • POC-013 · 4 Jul 20268/10
    KG-RAG

    DeepSeek-Lattice-KG: A Compact Language Model With Knowledge Graph Augmentation for Lattice Structure Design

  • POC-012 · 25 Jun 20269/10
    GrepSeek DCI

    GrepSeek: Direct Corpus Interaction — Hybrid Search for AI Agents

  • POC-011 · 24 May 20268/10
    Extreme Event AI

    Extreme Event AI: Reliability Calibration for RAG on Edge-Case Queries

  • POC-010 · 23 May 20268/10
    Label Scarcity

    Label Scarcity: Semi-Supervised Pseudo-Labeling for RAG

  • POC-009 · 22 May 20268/10
    TopoMAS

    TopoMAS: LLM-Driven Topological Materials Multi-Agent System

  • POC-008 · 21 May 20268/10
    Opinion Maximization

    Opinion Maximization Based on Fairness in Social Networks

  • POC-007 · 20 May 20268/10
    Bi-Stage RAG

    Bi-Stage Adaptive RAG

  • POC-006 · 19 May 20268/10
    OLR-WAA

    OLR-WAA: Adaptive & Drift-Resilient Online Regression

  • POC-005 · 18 May 20268/10
    Attribution Crisis

    Attribution Crisis: LLM Search Attribution Scorer

  • POC-004 · 17 May 20268/10
    Synergistic Engine

    Synergistic Engine: CEP + Declarative Rules for RAG

  • POC-001 · 16 May 202610/10
    Hybrid Search

    Query-Adaptive Hybrid Search

  • POC-002 · 16 May 20269/10
    CAD Score

    CAD Score: Context-Aware Semantic Diversity

  • POC-003 · 16 May 20269/10
    DSSW

    Dynamic Sub-Sequence Warping (DSSW)