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3 days ago · Implementing Fuzzy Logic for Sentiment Analysis. Step 1: Import Necessary Libraries. We start by importing the necessary libraries for handling data, preprocessing text, performing sentiment analysis, and working with fuzzy logic. import pandas as pd. import numpy as np. import skfuzzy as fuzz.
3 days ago · Fuzzy reasoning is vital due to the frequent use of imprecise information in daily contexts. However, the ability of current large language models (LLMs) to handle such reasoning remains largely uncharted. In this paper, we introduce a new benchmark, FRoG, for fuzzy reasoning, featuring real-world mathematical word problems that incorporate generalized quantifiers. Our experimental findings reveal that fuzzy reasoning continues to pose significant challenges for LLMs. Moreover, we find that ...
3 days ago · Our experimental findings reveal that fuzzy reasoning continues to pose significant challenges for LLMs. Moreover, we find that existing methods designed to enhance reasoning do not consistently improve performance in tasks involving fuzzy logic. Additionally, our results show an inverse scaling effect in the performance of LLMs on FRoG.
4 days ago · In Artificial Intelligence (AI) field, there is a trend towards explainable AI, which is trying to clarify algorithmic decisions, intending to rebuild trust . Nonetheless, aligning these technological advances with ethical standards and fostering responsible AI require continuous cooperation among researchers, policymakers, and the public .
3 days ago · To address this challenge, a novel and general explicable forecasting framework, that combines inductive rules and fuzzy logic, is proposed in this work. Inductive rules, derived from historical weather data, provide a logical and interpretable basis for forecasting; while fuzzy logic handles the uncertainty and imprecision in the weather data.
4 days ago · A new benchmark, FRoG, is introduced for fuzzy reasoning, featuring real-world mathematical word problems that incorporate generalized quantifiers, and it is found that existing methods designed to enhance reasoning do not consistently improve performance in tasks involving fuzzy logic. Fuzzy reasoning is vital due to the frequent use of imprecise information in daily contexts. However, the ability of current large language models (LLMs) to handle such reasoning remains largely uncharted. In ...
3 days ago · In my book The AI Economy, I cite a number of incidents of fuzzy logic which human beings cope with and which, to the best of my knowledge, so far artificial intelligence can’t. I am thinking of instances where something is either logically ambiguous or logically misleading.
