Showing results for Pseudo Intelligence: A Unifying Lens on Language Model Evaluation.
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We propose pseudointelligence, which captures the maxim that “(perceived) intelligence lies in the eye of the beholder.”
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Figure 1: Evaluation of a pseudointelligent model. For each capability µ, (1) iid samples are drawn and (2) fed to the learners, who (3) output a model and ...
Oct 18, 2023 · We propose a complexity-theoretic framework of model evaluation cast as a dynamic interaction between a model and a learned evaluator.
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In this paper, a new word-based language model evaluation measure is proposed to account for the effect of word segmentation and the goal of predicting CER.
Inspired by pseudorandomness, we propose pseudointelligence, which captures the maxim that “(perceived) intelligence lies in the eye of the beholder.” That is, ...
Oct 18, 2023 · With large language models surpassing human performance on an increasing number of benchmarks, we must take a principled approach for ...
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Recent advances in Large language models (LLMs) have demonstrated remarkable potential in text evaluation but their effectiveness in assessing FC in ...
Aug 4, 2024 · This article aims to explore the dual challenge of assessing the effects of Large Language Models and associated semantic technologies on text dissemination ...
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EmoBench: Evaluating the Emotional Intelligence of Large Language Models ... Revealing the Parametric Knowledge of Language Models: A Unified Framework for ...
Jun 28, 2024 · This paper endeavors to evaluate the competency of popular LVLMs in specialized and general tasks, respectively, aiming to offer a comprehensive understanding ...