LLM Survey 2024
Learning From Correctness Without Prompting Makes LLM Efficient Reasoner
Summary pending...
High Quality
Summary pending...
Exhasutive Review on [Search Workflows](https://github.com/xinzhel/LLM-Search)
Summary pending...
LLM-based Rewriting of Inappropriate Argumentation using Reinforcement Learning from Machine Feedback
Summary pending...
MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedback
Summary pending...
Augmented Language Models: a Survey
Summary pending...
The Rise and Potential of Large Language Model Based Agents: A Survey
Summary pending...
A Survey on the Memory Mechanism of Large Language Model based Agents
Summary pending...
LLM Reasoners: New Evaluation, Library, and Analysis of Step-by-Step Reasoning with Large Language Models
Summary pending...
Understanding the planning of LLM agents: A survey
This survey paper explores the planning mechanisms employed by large language model (LLM) agents, highlighting their capabilities and limitations. Understanding these planning strategies is crucial for improving LLM performance in complex tasks and applications.
GEAR: Augmenting Language Models with Generalizable and Efficient Tool Resolution
Summary pending...
ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs
Summary pending...
Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models
Summary pending...
Making Large Language Models into World Models with Precondition and Effect Knowledge
Summary pending...
A Survey on Large Language Model based Autonomous Agents
This paper surveys the development and application of large language model-based autonomous agents, highlighting their capabilities and challenges. It is important as it provides a comprehensive overview of how these agents are transforming various fields and identifies future research directions.
ISR-LLM: Iterative Self-Refined Large Language Model for Long-Horizon Sequential Task Planning
Summary pending...
TPTU-v2: Boosting Task Planning and Tool Usage of Large Language Model-based Agents in Real-world Systems
Summary pending...
Learning From Mistakes Makes LLM Better Reasoner
Summary pending...
A Review of Prominent Paradigms for LLM-Based Agents: Tool Use (Including RAG), Planning, and Feedback Learning
Summary pending...
A Review of Prominent Paradigms for LLM-Based Agents: Tool Use (Including RAG), Planning, and Feedback Learning
This paper explores how to improve the coherence of understanding across different repositories. It highlights the importance of consistent data interpretation for better information retrieval and knowledge management.
When is Tree Search Useful for {LLM} Planning? It Depends on the Discriminator
Summary pending...
Alphazero-like Tree-Search can guide large language model decoding and training
Summary pending...
Language Agent Tree Search Unifies Reasoning, Acting, and Planning in Language Models
Summary pending...
Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generation
Summary pending...
Tree-of-Traversals: A Zero-Shot Reasoning Algorithm for Augmenting Black-box Language Models with Knowledge Graphs
Summary pending...
CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing
Summary pending...
SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning
Summary pending...
ToolChain: Efficient Action Space Navigation in Large Language Models with A\* Search
Summary pending...
LLM-A\*: Large Language Model Enhanced Incremental Heuristic Search on Path Planning
This paper presents LLM-A*, an approach that integrates large language models into incremental heuristic search for path planning. It aims to enhance the efficiency and effectiveness of finding optimal paths in complex environments, which is crucial for applications in robotics and AI navigation.
HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face
This paper introduces HuggingGPT, a framework that integrates ChatGPT with various models from Hugging Face to tackle a range of AI tasks. It highlights the potential of combining different AI models to enhance task performance and flexibility.
On the Planning Abilities of Large Language Models -- A Critical Investigation
Summary pending...
LLM-MCTS:Large Language Models as Commonsense Knowledge for Large-Scale Task Planning
Summary pending...
Prompt-Based Monte-Carlo Tree Search for Goal-oriented Dialogue Policy Planning
Summary pending...
Monte Carlo Thought Search: Large Language Model Querying for Complex Scientific Reasoning in Catalyst Design
Summary pending...
ChatCoT: Tool-Augmented Chain-of-Thought Reasoning on Chat-based Large Language Models
The paper introduces ChatCoT, a method that enhances chat-based large language models by integrating tool-augmented reasoning through chain-of-thought techniques. This approach improves the models' ability to perform complex tasks by leveraging external tools for better decision-making and problem-solving.
HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face
Summary pending...
Least-to-Most Prompting Enables Complex Reasoning in Large Language Models
Summary pending...
MultiTool-CoT: GPT-3 Can Use Multiple External Tools with Chain of Thought Prompting
Summary pending...
ToolkenGPT: Augmenting Frozen Language Models with Massive Tools via Tool Embeddings
This paper introduces ToolkenGPT, a method that enhances frozen language models by integrating them with a variety of external tools through the use of tool embeddings. This advancement allows for improved task performance by leveraging specialized functionalities of these tools, making language models more versatile.
On the Planning Abilities of Large Language Models - A Critical Investigation
Summary pending...
PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Change
Summary pending...
Tree of Thoughts: Deliberate Problem Solving with Large Language Models
Summary pending...
Planning with Large Language Models for Code Generation
Summary pending...
Plan, Verify and Switch: Integrated Reasoning with Diverse X-of-Thoughts
Summary pending...
ByteSized32: A Corpus and Challenge Task for Generating Task-Specific World Models Expressed as Text Games
Summary pending...
Leveraging Pre-trained Large Language Models to Construct and Utilize World Models for Model-based Task Planning
Summary pending...
Leveraging Pre-trained Large Language Models to Construct and Utilize World Models for Model-based Task Planning
Summary pending...
Large Language Models Still Can't Plan (A Benchmark for LLMs on Planning and Reasoning about Change)
Summary pending...