Large Language Model based Multi-Agents: A Survey of Progress and Challenges
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Updated
Apr 24, 2024
Large Language Model based Multi-Agents: A Survey of Progress and Challenges
Awesome LLM Self-Consistency: a curated list of Self-consistency in Large Language Models
The data and implementation for the experiments in the paper "Flows: Building Blocks of Reasoning and Collaborating AI".
LLMs represent numbers on a helix and manipulate that helix to do addition.
A framework for evaluating the effectiveness of chain-of-thought reasoning in language models.
Awesome Mixture of Experts (MoE): A Curated List of Mixture of Experts (MoE) and Mixture of Multimodal Experts (MoME)
Análise do Impacto da Padronização de Markdown na Carga Cognitiva e Desempenho de Tarefas
Análise Causal Heterogênea para Subgrupos de Intervenção em Ansiedade
Análise Robusta de Intervenções para Ansiedade com Técnicas de Tratamento de Dados Ausentes
Pipeline Unificado para Tomada de Decisão Financeira com Agentes Multimodais e Descentralizados
Framework de Mixture of Experts para Explicabilidade de Estados de Ansiedade
Análise Avançada de Intervenção para Ansiedade com SHAP
Análise de Intervenção de Ansiedade com Descoberta Causal
Análise Avançada de Dados com Causalidade e Aprendizado por Reforço
Repo for exploring the (in)effectiveness of chain of thought in planning
Awesome-LLM-Planning
Latent-Explorer is the Python implementation of the framework proposed in the paper "Unveiling LLMs: The Evolution of Latent Representations in a Dynamic Knowledge Graph".
Self-Improving LLMs Through Iterative Refinement
Compare the intelligence of different AIs using randomly generated tasks.
Análise Causal de Intervenções de Ansiedade com Algoritmos de Descoberta Causal
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