tree-of-thought-llm

[NeurIPS 2023] Tree of Thoughts: Deliberate Problem Solving with Large Language Models (by princeton-nlp)
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tree-of-thought-llm reviews and mentions

Posts with mentions or reviews of tree-of-thought-llm. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-03-22.
  • AI Chat Applications with the Metacognition Approach: Tree of Thoughts (ToT)
    2 projects | dev.to | 22 Mar 2024
    [2305.10601] Tree of Thoughts: Deliberate Problem Solving with Large Language Models (arxiv.org)
  • Last night /u/ alesneolith posted a very serious writeup claiming to have worked in one of the projects. The writeup is more elaborate than expected and got surprisingly little attention. His account has been since deleted.
    2 projects | /r/UFOs | 7 Dec 2023
    Language models are increasingly being deployed for general problem solving across a wide range of tasks, but are still confined to token-level, left-to-right decision-making processes during inference. This means they can fall short in tasks that require exploration, strategic lookahead, or where initial decisions play a pivotal role. To surmount these challenges, we introduce a new framework for language model inference, “Tree of Thoughts” (ToT), which generalizes over the popular “Chain of Thought” approach to prompting language models, and enables exploration over coherent units of text (“thoughts”) that serve as intermediate steps toward problem solving. ToT allows LMs to perform deliberate decision making by considering multiple different reasoning paths and self-evaluating choices to decide the next course of action, as well as looking ahead or backtracking when necessary to make global choices. Our experiments show that ToT significantly enhances language models’ problem-solving abilities on three novel tasks requiring non-trivial planning or search: Game of 24, Creative Writing, and Mini Crosswords. For instance, in Game of 24, while GPT-4 with chain-of-thought prompting only solved 4% of tasks, our method achieved a success rate of 74%. Code repo with all prompts: https://github.com/princeton-nlp/tree-of-thought-llm.
  • Ultra Fast Bert
    1 project | news.ycombinator.com | 22 Nov 2023
    GPU utilization should be down when using this technique. I’m hoping this could allow for more efficient batch inference on GPUs. If you can predict 10 tokens for the price of 1 it should allow you to do tree of thought much more efficiently.

    https://github.com/princeton-nlp/tree-of-thought-llm

  • Is it best to not pay attention to AI news and/or find ways to delude ourselves into believing better outcomes?
    1 project | /r/samharris | 10 Jul 2023
    For those familiar with Daniel Kahneman's Thinking Fast and Slow, the current LLMs (such as GPT-4 via ChatGPT) seem to resemble System 1 thinking (near-instantaneous, automatic, intuitive processes like next-word prediction). However, they lack System 2 thinking (slow, effortful, logical, planning, reasoning). What I learned today is that Google's Gemini (an LLM in training now) not only has more modalities (I think all Youtube Video and audio??), more compute, and almost twice the training data, but they're building in AlphaGo-type learning, which resembles tree of thoughts and looks a LOT like the missing puzzle piece of System 2 thinking. Will it be AGI? Maybe, and it's coming this winter.
  • Langchain Is Pointless
    16 projects | news.ycombinator.com | 8 Jul 2023
    Tree of thoughts: https://arxiv.org/abs/2305.10601

    Good video on "Tree of thoughts" which also reviews / puts it in the context of other methods: https://www.youtube.com/watch?v=ut5kp56wW_4

    Completion vs conversational interface is something you can read about in the OpenAI API documentation.

    For the remaining things I don't have single specific pointer at hand.

  • To all skeptics with a background in AI/CS : what is your realistic timeline for AGI/ASI ?
    1 project | /r/singularity | 6 Jul 2023
    What do you think about the combination of Tree of Thoughts: Deliberate Problem Solving with Large Language Models LongNet: Scaling Transformers to 1,000,000,000 Tokens Textbooks Are All You Need Attention Is All You Need Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation
  • Why do language models appear to work left-to-right?
    1 project | /r/MLQuestions | 1 Jul 2023
    You are right. Tree of Thoughts: Deliberate Problem Solving with Large Language Models proposes to solve this via MCTS-style generation (similar to how AlphaGo worked, and a lot of planning & control problems are executed).
  • Munk Debate on Artificial Intelligence
    1 project | /r/samharris | 30 Jun 2023
    The transformer was developed in 2017 and it powers all modern LLMs. If you're familiar with Daniel Kahneman's work from Thinking Fast and Slow, you could easily summarize LLMs as excellent System 1 thinking: our fast, automatic, unconscious responses (e.g. autocomplete). I'd argue that we're one development (similar to the transformer) away from creating System 2 thinking: deliberate and strategic thinking. In fact, with merely GPT-4 and some clever architectures, researchers have developed chain-of-thought prompting and, more recently, tree-of-thoughts reasoning. While external to the LLM architecture, embedding these concepts into a LLM could very likely solve the creation of System 2 thinking and produce the first real AGI. Adding more modalities (e.g. audio, images, video, topography, etc.) will simply add more nuance in the weights and biases of a complete system.
  • Question regarding model compatibility for Alpaca Turbo
    8 projects | /r/LocalLLaMA | 30 Jun 2023
    There are a bunch of other methods to improve quality and performance like tree-of-thought-llm, connecting a LLM to a database or have it review its own output.
  • Tree of thoughts build in open-source model
    2 projects | /r/LocalLLaMA | 28 Jun 2023
  • A note from our sponsor - InfluxDB
    www.influxdata.com | 30 Apr 2024
    Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality. Learn more →

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princeton-nlp/tree-of-thought-llm is an open source project licensed under MIT License which is an OSI approved license.

The primary programming language of tree-of-thought-llm is Python.

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