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New methods tackle order-dependency in System One AI models

By PulseAugur Editorial · [4 sources] ·

Researchers have developed new methods to address the order-dependency issue in System One models, which are designed to make decisions in a single forward pass. Two papers, Prism-1 and Runoff, propose distinct approaches to ensure that the order of options or the addition of new options does not unfairly influence the model's output. Prism-1 achieves this by processing each option independently, while Runoff uses a two-pass system that first scores options individually and then compares them. A third paper explores calibration and risk-budgeted decisions within System One models, focusing on controlling errors in uncertain cases. AI

IMPACT These methods could lead to more reliable and predictable AI decision-making in applications where option order or set manipulation is a concern.

RANK_REASON Multiple research papers proposing novel methods for improving AI model decision-making processes.

Read on Hugging Face Daily Papers →

AI-generated summary · Google Gemini · from 4 sources. How we write summaries →

New methods tackle order-dependency in System One AI models

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COVERAGE [4]

  1. arXiv cs.AI TIER_1 English(EN) · Yao Long Teng, Jianguo Huang, Yanchen Deng, Jiayi Cai, Bo An ·

    Prism-1: Position- and Rival-Independent Scoring for System One Models

    arXiv:2610.22066v1 Announce Type: new Abstract: Given a state and a set of options, such as intents, tools or interface elements, System One decision models return a distribution over the options in one forward pass, without generated reasoning. Web systems increasingly build the…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    Prism-1: Position- and Rival-Independent Scoring for System One Models

    Given a state and a set of options, such as intents, tools or interface elements, System One decision models return a distribution over the options in one forward pass, without generated reasoning. Web systems increasingly build them by reading decisions from language models. Two…

  3. arXiv cs.AI TIER_1 English(EN) · Jianguo Huang, Yao Long Teng, Yanchen Deng, Bo An ·

    Consider, Then Choose: Order-Invariant Decisions in System One Models

    arXiv:2610.18233v1 Announce Type: new Abstract: System One models answer typed questions in a single forward pass and promise the same answer for the same input. For choice questions, this promise fails: the answer depends on the order of the options, increasingly so as they grow…

  4. arXiv cs.LG TIER_1 English(EN) · Soundouss Messoudi, Youness Mansar ·

    Calibration and Risk-Budgeted Decisions with System One Models

    arXiv:2610.19811v1 Announce Type: cross Abstract: LLM workflows and agents rely on a set of binary decisions like allow/block an input, or discard/retain a retrieved document. When human deferral is unavailable, uncertain cases must still receive an action. We study System One de…

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