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Why It Matters
Mathematical problem solving often requires deterministic computational steps that agents delegate to tools and implicitly trust.
Provenance
Discovered via ArXiv and published by ArXiv.
Key Claims
Original description
Mathematical problem solving often requires deterministic computational steps that agents delegate to tools and implicitly trust. Yet tools can fail silently, returning plausible but incorrect results. How well can agents detect and correct corrupted tool call outputs? We study this through a controlled corruption framework where a hidden interceptor replaces tool call results with plausible incorrect information on targeted problems. We evaluate agents across 31 problems under four verification designs including no verification (baseline), mandatory same-context reflection, optional fresh-con...
Discovered via ArXiv
Research papers and preprints from arXiv.
Publisher: arxiv.org
ID: http://arxiv.org/abs/2610.08097v1 · Indexed about 2 hours ago