[NeurIPS 2024 Spotlight] Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models
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Updated
Oct 28, 2024 - Python
[NeurIPS 2024 Spotlight] Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models
[ACL 2024] A Survey of Chain of Thought Reasoning: Advances, Frontiers and Future
[NeurIPS 2024] Code for the paper "Diffusion of Thoughts: Chain-of-Thought Reasoning in Diffusion Language Models"
In Building Systems With The ChatGPT API, you will learn how to automate complex workflows using chain calls to a large language model.
Codes for ICML 2024 paper: "Video-of-Thought: Step-by-Step Video Reasoning from Perception to Cognition"
Research papers about Chain of Thought (CoT)
Official implementation of LoT paper: "Enhancing Zero-Shot Chain-of-Thought Reasoning in Large Language Models through Logic"
Monte Carlo Tree Search Self-Refine (MCTSr)
About The corresponding code from our paper " Making Reasoning Matter: Measuring and Improving Faithfulness of Chain-of-Thought Reasoning" . Do not hesitate to open an issue if you run into any trouble!
A no-string framework for reasoning over your tabular data rows with any provided LLM
LLM's can't reason.
Enhancing LLMs with LoRA
Making CoT great again, but for everyone this time!
This repository contains results from my MSc. thesis on "Test Case Generation from User Stories using Generative AI Techniques with LLM Models." Each folder includes generated test cases in PDF, detailed metrics scores of data in Excel sheets, and visual graphs, offering a comprehensive view of the experiments in images folder and their outcomes.
This Credit Risk Assessment agent leverages advanced machine learning techniques, including Chain of Thought (CoT) reasoning and Reinforcement Learning (RL), to evaluate credit risk. The project aims to provide more transparent, effective, and explainable solutions to the complex task of assessing creditworthiness.
KNET is an educational Retrieval-Augmented Generation (RAG) system built from scratch, designed to empower STEM learners by combining transformers and intelligent retrieval to simulate human reasoning and deliver precise, context-aware answers to foster curiosity and understanding!
Exploring Chain-of-Thought reasoning in deep learning models. Implement and evaluate with synthetic data, showcasing model training and performance analysis.
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