Results 91 to 100 of about 520,319 (211)
Entropy in Large Language Models
CoRRIn this study, the output of large language models (LLM) is considered an information source generating an unlimited sequence of symbols drawn from a finite alphabet. Given the probabilistic nature of modern LLMs, we assume a probabilistic model for these LLMs, following a constant random distribution and the source itself thus being stationary.
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Evaluating Foundation Models on Timbre-Related Cognitive Tasks [PDF]
Foundation models are increasingly applied to MIR tasks, yet their performance on music cognition problems remains underexplored. In this work, we investigate how state-of-the-art audio-language models and large language models (LLMs) perform on timbre ...
Saitis, C +4 more
core
Assessing the Relational Abilities of Large Language Models and Large Reasoning Models
Behavioral SciencesWe assessed the relational abilities of two state-of-the-art large language models (LLMs) and two large reasoning models (LRMs) using a new battery of several thousand syllogistic problems, similar to those used in behavior-analytic tasks for relational ...
Matthias Raemaekers +2 more
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Personalized Large Language Models
2024 IEEE International Conference on Data Mining Workshops (ICDMW)Large language models (LLMs) have significantly advanced Natural Language Processing (NLP) tasks in recent years. However, their universal nature poses limitations in scenarios requiring personalized responses, such as recommendation systems and chatbots. This paper investigates methods to personalize LLMs, comparing fine-tuning and zero-shot reasoning
Stanislaw Wozniak +4 more
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Manner implicatures in large language models
Scientific ReportsIn human speakers’ daily conversations, what we do not say matters. We not only compute the literal semantics but also go beyond and draw inferences from what we could have said but chose not to.
Yan Cong
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Prompt Optimization in Large Language Models
MathematicsPrompt optimization is a crucial task for improving the performance of large language models for downstream tasks. In this paper, a prompt is a sequence of n-grams selected from a vocabulary.
Antonio Sabbatella +4 more
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Hyperbolic Large Language Models
CoRRLarge language models (LLMs) have achieved remarkable success and demonstrated superior performance across various tasks, including natural language processing (NLP), weather forecasting, biological protein folding, text generation, and solving mathematical problems. However, many real-world data exhibit highly non-Euclidean latent hierarchical anatomy,
Sarang Patil +4 more
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Openai API, LLM (Large Language Models) [PDF]
La API de OpenAI es una interfaz de programación que proporciona acceso a modelos avanzados de inteligencia artificial (IA) desarrollados por OpenAI, específicamente Modelos de Lenguaje Grande (LLM), como GPT-3 y GPT-4.
Santa Quintero, Ricardo Andres +2 more
core
Large Language Diffusion Models
CoRRThe capabilities of large language models (LLMs) are widely regarded as relying on autoregressive models (ARMs). We challenge this notion by introducing LLaDA, a diffusion model trained from scratch under the pre-training and supervised fine-tuning (SFT) paradigm.
Shen Nie +9 more
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