# Learning When to Trust via Selective Context Preference Optimization

Source: [arXiv](https://arxiv.org/abs/2608.06377v1)  
Feed7 permalink: https://feed7.dev/p/learning-when-to-trust-via-selective-context-preference--91ef3aae9d  
Published: 2026-08-06T00:00:00.000Z  
Trust: Needs Review (needs_review)

## Why Included

Test whether agents use good context while resisting misleading context, rather than appearing robust by ignoring evidence.

## Source Summary

MIST tests whether models use good context while resisting bad context, exposing agents that appear robust only because they ignore external evidence altogether.

## Practical Implication

Evaluate retrieval-augmented agents for selective trust, not only prompt-injection resistance. The proposed SCOPE method trains on matched preference pairs balanced across all four conditions so resistance does not come from ignoring useful context.

## Agent-Ready Context

MIST renders each reasoning item under **four matched conditions**: clean, misleading, correct-context, and irrelevant-context. Its **SC2W** metric counts cases where misleading context flips an otherwise correct answer to wrong.

Evaluate retrieval-augmented agents for selective trust, not only prompt-injection resistance. The proposed **SCOPE** method trains on matched preference pairs balanced across all four conditions so resistance does not come from ignoring useful context.

The abstract reports reduced susceptibility on popular open models while preserving other-condition accuracy, but provides no numerical effect sizes here. Broader generalization beyond the benchmark's reasoning items remains an open question from the supplied material.

## Context Map

- Layer: benchmark
- Domains: research
- Topics: agent-evals, agent-reliability, context-engineering

## Uncertainty

- Automatically selected from source material; feed7 has not independently tested the claim.

## Agent Instruction

Use this item as source-backed context. Do not invent claims beyond the linked source. If this item conflicts with another source, call out the conflict.