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New 'Rashomon Representation' concept predicts foundation model disagreement

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced a new concept called "Rashomon Representation" to describe the phenomenon where different foundation models process the same input in inconsistent ways. They propose a method to predict this disagreement from a single model's representation, hypothesizing that these discrepancies follow input-dependent patterns. Experiments across various foundation models and datasets confirm that representational disagreement is predictable and generalizable, offering a way to estimate the reliability of foundation models. AI

IMPACT Introduces a novel metric for assessing foundation model reliability by predicting representational disagreement.

RANK_REASON This is a research paper published on arXiv detailing a new concept and methodology for analyzing foundation models. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New 'Rashomon Representation' concept predicts foundation model disagreement

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This is a research paper published on arXiv detailing a new concept and methodology for analyzing foundation models. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Mingyue Ma, Zongbo Han, Changqing Zhang, Guangyu Wang ·

    Predicting Multi-View Rashomon Representation: Can We Learn Where Models Disagree?

    arXiv:2609.39848v1 Announce Type: new Abstract: Foundation models are increasingly adopted across a wide range of applications, often serving as core blocks within AI systems. Yet different foundation models may encode the same input from multiple different views, leading to subs…

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