TEX: Test-Time Scaling Testing Agents via Execution-based Cross-Validation
We present TEX, a collaborative test-time scaling framework based on execution-driven cross-validation.
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Key points
- Test-case generation is critical but remains challenging for language models.
- Existing test-time scaling methods either isolate candidates or aggregate traces, which do not scale to long-horizon tasks.
- TEX parallelizes agents to generate tests and patches, cross-executing each test against every patch to form a $K \times K$ feedback matrix.
- Our results highlight execution-grounded feedback as an effective scaling mechanism for long-horizon agentic tasks.
Sources (1)
- [1]TEX: Test-Time Scaling Testing Agents via Execution-based Cross-ValidationarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 19, 09:06 PM
We present TEX, a collaborative test-time scaling framework based on execution-driven cross-validation.
Test-case generation is critical but remains challenging for language models.
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