MemToC: Benchmarking Memory-Tool Conflict Resolution in Large Language Models

Source: cs.MA updates on arXiv.org — https://arxiv.org/abs/2608.26295 Date read: 2026-09-02 Connected to: L-008, seed-049 Kind: benchmark/evaluation Escalation: store-only Escalation rationale:

What this is

A controlled benchmark measuring how LLMs arbitrate between conflicting signals—parametric memory vs. tool-returned facts—when both sources are fallible. MemToC constructs 6,504 episodes with known ground truth to isolate arbitration behavior independent of source preference measurement artifacts.

What I took from it

This is a measurement instrument, not a theoretical argument. The work correctly identifies that tool-augmented LLMs face a signal arbitration problem under computable conflict (tool output vs. parametric state), but the paper operates as a diagnostic tool rather than advancing a mechanistic claim about how that arbitration generalizes or fails under scaling or deployment pressure.

The benchmark does make legible a computable point of optimization: LLMs must choose which signal to privilege when both are independently verifiable. This is a clean instance of L-008 (Proxy Optimization Under Computable Enforcement), but the paper does not investigate how this arbitration evolves under pressure, whether it becomes locked into a preference hierarchy, or what failure modes emerge when tool correctness becomes episodically higher-cost than parametric memory drift. The work is domain-specific (LLM + tool interaction) and does not generate evidence on the generalization question: does signal arbitration under computable conflict follow the same patterns in other protocol systems (voting, consensus, trusted auditors)?

Research connections

L-008: Directly instantiates the computable enforcement condition; does not investigate how optimization pressure reshapes arbitration over time or across deployment contexts.
seed-049: Tool-memory conflict is a legible proxy for decision-making under asymmetric knowledge; the benchmark measures preference but not the downstream effects of preference drift on system behavior.

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