raymin0223/mixture_of_recursions

• highreadme#1

  Reposition README opening to clarify it's a research paper's official implementation

  Why:

  CURRENT

  # Mixture-of-Recursions: Learning Dynamic Recursive Depths for Adaptive Token-Level Computation (NeurIPS 2025)

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  # Mixture-of-Recursions: Learning Dynamic Recursive Depths for Adaptive Token-Level Computation (NeurIPS 2025)
  
  This repository contains the official implementation of the NeurIPS 2025 paper "Mixture-of-Recursions: Learning Dynamic Recursive Depths for Adaptive Token-Level Computation."

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• mediumtopics#2

  Add topics to specify it's a research paper's official implementation

  Why:

  CURRENT

  adaptive-computation, early-exiting, kv-cache, llm, recursive-transformers, router

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  adaptive-computation, early-exiting, kv-cache, llm, recursive-transformers, router, neurips-2025, paper-implementation, research-code

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• lowreadme#3

  Add a "Quick Start" or "Usage" section to the README

  Why:

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  ## 🚀 Quick Start
  
  To get started with Mixture-of-Recursions, follow these steps:
  
  1. **Installation:**
     ```bash
     git clone https://github.com/raymin0223/mixture_of_recursions.git
     cd mixture_of_recursions
     pip install -r requirements.txt
     ```
  
  2. **Running Experiments:**
     [Provide a simple command to run a demo or reproduce a key result, e.g., python train.py --model mor --dataset wikitext]

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Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

• CATEGORY QUERY

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  AI recommended 17 alternatives but never named raymin0223/mixture_of_recursions. This is the gap to close.

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• CATEGORY QUERY

  Seeking techniques to implement adaptive token-level computation for LLMs to save resources.

  you: not recommended
  AI recommended (in order):

  1. Hugging Face Transformers
  2. DeepSpeed
  3. ONNX Runtime
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  AI recommended 8 alternatives but never named raymin0223/mixture_of_recursions. This is the gap to close.

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• Metadata completeness

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• README presence

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• Compared to common alternatives in this category, what is the core differentiator of raymin0223/mixture_of_recursions?

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  ✓AI named raymin0223/mixture_of_recursions explicitly

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• If a team adopts raymin0223/mixture_of_recursions in production, what risks or prerequisites should they evaluate first?

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  ✓AI named raymin0223/mixture_of_recursions explicitly

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• In one sentence, what problem does the repo raymin0223/mixture_of_recursions solve, and who is the primary audience?

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  ✓AI named raymin0223/mixture_of_recursions explicitly

  AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?