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[NeurIPS 2024 Spotlight] Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models
Reasoning in Large Language Models: Papers and Resources, including Chain-of-Thought and OpenAI o1 🍓
A simple HTN planner based around the principles of the Builder pattern.
A Hierarchical Task Network planner utilizing LLMs like OpenAI's GPT-4 to create complex plans from natural language that can be converted into an executable form.
The related works and background techniques about Openai o1
[ICCV'23] LLM-Planner: Few-Shot Grounded Planning for Embodied Agents with Large Language Models
This is a repository for paper titled, PlaSma: Making Small Language Models Better Procedural Knowledge Models for (Counterfactual) Planning
Code for MultiPLY: A Multisensory Object-Centric Embodied Large Language Model in 3D World
[ICML 2024] 3D-VLA: A 3D Vision-Language-Action Generative World Model
Integration of SIADEX with the Unified Planning Library
High-level robotic simulator based on the Godot engine.
Toolbox for automated planning and combinatorial solving.
Code for our ACL 2023 Paper "Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models".
Implementation of "Describe, Explain, Plan and Select: Interactive Planning with Large Language Models Enables Open-World Multi-Task Agents"
[ACL 2023] Reasoning with Language Model Prompting: A Survey
Must-read Papers on Large Language Model (LLM) Planning.
Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat, Coupang, Stitchfix etc. Blog: mlengineer.io.
Benchmarking large language models' complex reasoning ability with chain-of-thought prompting
A Production-ready Reinforcement Learning AI Agent Library brought by the Applied Reinforcement Learning team at Meta.
An Adaptive and Extensible Platform for Cloud and Fog Robotics Using ROS 2
Machine Learning and Computer Vision Engineer - Technical Interview Questions
Collection of Summer 2025 tech internships!
OptaPy is an AI constraint solver for Python to optimize planning and scheduling problems.