PDF Viewer

BUILDER'S SANDBOX

Build This Paper

Use an AI coding agent to implement this research.

OpenAI Codex
OpenAI CodexAI Agent

Lightweight coding agent in your terminal.

Claude Code
Claude CodeAI Agent

Agentic coding tool for terminal workflows.

AntiGravity IDE
AntiGravity IDEScaffolding

AI agent mindset installer and workflow scaffolder.

Cursor
CursorIDE

AI-first code editor built on VS Code.

VS Code
VS CodeIDE

Free, open-source editor by Microsoft.

Estimated $9K - $13K over 6-10 weeks.

See exactly what it costs to build this -- with 3 comparable funded startups.

7-day free trial. Cancel anytime.

Discover the researchers behind this paper and find similar experts.

7-day free trial. Cancel anytime.

References (45)

[1]
Systematicity between Forms and Meanings across Languages Supports Efficient Communication
2026Doreen Osmelak, Yang Xu et al.
[2]
Recursive numeral systems are highly regular and easy to process
2025Ponrawee Prasertsom, Andrea Silvi et al.
[3]
Learning a Novel Number System: The Role of Compositional Rules and Counting Procedures
2025Sebastian Holt, David Barner
[4]
The learning bias for cross-category harmony is sensitive to semantic similarity: Evidence from artificial language learning experiments
2025Fang Wang, Simon Kirby et al.
[5]
Re-examining the tradeoff between lexicon size and average morphosyntactic complexity in recursive numeral systems
2025David Yang, Terry Regier
[6]
Learning Efficient Recursive Numeral Systems via Reinforcement Learning
2024Jonathan D. Thomas, Andrea Silvi et al.
[7]
Predictability and Variation in Language Are Differentially Affected by Learning and Production
2024Aislinn Keogh, Simon Kirby et al.
[8]
Recursive Numeral Systems Optimize the Trade-off Between Lexicon Size and Average Morphosyntactic Complexity
2024M. Denic, J. Szymanik
[9]
Cultural evolution via iterated learning and communication explains efficient color naming systems
2023Emil Carlsson, Devdatt P. Dubhashi et al.
[10]
Deep neural networks and humans both benefit from compositional language structure
2023Lukas Galke Poech, Yoav Ram et al.
[11]
Exact Number Concepts Are Limited to the Verbal Count Range
2022Benjamin Pitt, E. Gibson et al.
[12]
Deep Reinforcement Learning at the Edge of the Statistical Precipice
2021Rishabh Agarwal, Max Schwarzer et al.
[13]
Learning Approximate and Exact Numeral Systems via Reinforcement Learning
2021Emil Carlsson, Devdatt P. Dubhashi et al.
[14]
What makes a language easy to learn? A preregistered study on how systematic structure and community size affect language learnability.
2021Limor Raviv, Marianne de Heer Kloots et al.
[15]
Numeral Systems Across Languages Support Efficient Communication: From Approximate Numerosity to Recursion
2020Yang Xu, Emmy Liu et al.
[16]
A reinforcement-learning approach to efficient communication
2020Mikael Kågebäck, Emil Carlsson et al.
[17]
Bandit Algorithms
2020Tor Lattimore, Csaba Szepesvari
[18]
Ease of learning explains semantic universals.
2019Shane Steinert-Threlkeld, Jakub Szymanik
[19]
Learnability and semantic universals
2019Shane Steinert-Threlkeld, Jakub Szymanik
[20]
The Emergence of Compositional Languages for Numeric Concepts Through Iterated Learning in Neural Agents
2019Shangmin Guo, Yi Ren et al.

Showing 20 of 45 references

Founder's Pitch

"Study explores the learnability of regular numeral systems using reinforcement learning, focusing on linguistic applications."

NLPScore: 2View PDF ↗

Commercial Viability Breakdown

0-10 scale

High Potential

0/4 signals

0

Quick Build

0/4 signals

0

Series A Potential

0/4 signals

0

Sources used for this analysis

arXiv Paper

Full-text PDF analysis of the research paper

GitHub Repository

Code availability, stars, and contributor activity

Citation Network

Semantic Scholar citations and co-citation patterns

Community Predictions

Crowd-sourced unicorn probability assessments

Analysis model: GPT-4o · Last scored: 2/25/2026

Explore the full citation network and related research.

7-day free trial. Cancel anytime.

Understand the commercial significance and market impact.

7-day free trial. Cancel anytime.

Get detailed profiles of the research team.

7-day free trial. Cancel anytime.