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)
Causal Inference Analysis for Decreasing Cognitive Load and Enhancing Task Performance via Standardized Markdown Language Routines with Multiple Generative Models
Mixture of Experts Framework for Enhanced Explainability of Anxiety States Pre- and Post-Intervention Across Experimental Groups
Comparative Causal Network Analysis of Alpha Waves and HRV (Normalized) Using Knowledge Retrieval for Emotion Recognition Systems
Interaction Pipelines with Multiple LLMs for Thought Hypergraph Distillation to Enhance Error Detection with Pre- and Post-Task Anxiety Analysis
Unified Pipeline with Crossmodal Data and Decentralized Agents for Causal Analysis of Financial Decision-Making Dynamics
Zero-Knowledge Proofs Integrated with Crossmodal and Foundational Models for Causal Analysis of Crypto Market Performance
Fuzzy Logic Distillation for Structuring Thought Hypergraphs to Enhance Citation Analysis and Relevance Assessment of Academic Articles
Thought Hypergraphs for Enhanced Detection and Explainability of Errors Across Experimental Groups
Self-Improving LLMs Through Iterative Refinement
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".
Repo for exploring the (in)effectiveness of chain of thought in planning
Compare the intelligence of different AIs using randomly generated tasks.
Awesome-LLM-Planning
Willamette is an Ollama-Powered Model Runner
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