View PDF ↗
PDF Viewer
Open Full PDF

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 (15)

[1]
Variance-Based Pruning for Accelerating and Compressing Trained Networks
2025Uranik Berisha, Jens Mehnert et al.
[2]
Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations
2023Atticus Geiger, Zhengxuan Wu et al.
[3]
Causal Abstraction: A Theoretical Foundation for Mechanistic Interpretability
2023Atticus Geiger, D. Ibeling et al.
[4]
Causal Abstraction with Soft Interventions
2022Riccardo Massidda, Atticus Geiger et al.
[5]
Inducing Causal Structure for Interpretable Neural Networks
2021Atticus Geiger, Zhengxuan Wu et al.
[6]
Causal Abstractions of Neural Networks
2021Atticus Geiger, Hanson Lu et al.
[7]
Neuron Merging: Compensating for Pruned Neurons
2020Woojeong Kim, Suhyun Kim et al.
[8]
Zoom In: An Introduction to Circuits
2020Christopher Olah, Nick Cammarata et al.
[9]
Approximate Causal Abstractions
2019Sander Beckers, F. Eberhardt et al.
[10]
Causality
2019Giri Narasimhan
[11]
Abstracting Causal Models
2018Sander Beckers, Joseph Y. Halpern
[12]
Causal Consistency of Structural Equation Models
2017Paul K. Rubenstein, S. Weichwald et al.
[13]
Gradient-based learning applied to document recognition
1998Yann LeCun, L. Bottou et al.
[14]
Second Order Derivatives for Network Pruning: Optimal Brain Surgeon
1992B. Hassibi, D. Stork
[15]
Optimal Brain Damage
1989Yann LeCun, J. Denker et al.

Founder's Pitch

"A novel method to discover causal abstractions in neural networks using mechanism sparsification."

Causal InferenceScore: 2View PDF ↗

Commercial Viability Breakdown

0-10 scale

High Potential

0/4 signals

0

Quick Build

1/4 signals

2.5

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: 2/27/2026

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.