30 lines
No EOL
1.6 KiB
Markdown
30 lines
No EOL
1.6 KiB
Markdown
---
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type: entity
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entity_type: research_program
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name: SPAR Automating Circuit Interpretability with Agents
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status: active
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founded: 2025
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parent_org: SPAR (Scalable Alignment Research)
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domain: ai-alignment
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supports:
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- Circuit tracing requires hours of human effort per prompt which creates a fundamental bottleneck preventing interpretability from scaling to production safety applications
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reweave_edges:
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- Circuit tracing requires hours of human effort per prompt which creates a fundamental bottleneck preventing interpretability from scaling to production safety applications|supports|2026-04-08
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---
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# SPAR Automating Circuit Interpretability with Agents
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Research program targeting the human analysis bottleneck in mechanistic interpretability by using AI agents to automate circuit interpretation work.
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## Overview
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SPAR's project directly addresses the documented bottleneck that 'it currently takes a few hours of human effort to understand the circuits even on prompts with only tens of words.' The program attempts to use AI agents to automate the human-intensive analysis work required to interpret traced circuits, potentially enabling interpretability to scale to production safety applications.
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## Approach
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Applies the role specialization pattern from human-AI mathematical collaboration to interpretability work, where AI agents handle the exploration and analysis while humans provide strategic direction and verification.
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## Timeline
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- **2025** — Program initiated to address circuit tracing scalability bottleneck
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- **2026-01** — Identified by Mitra as the most direct attempted solution to the hours-per-prompt constraint |