mlsanityData to 7 Oct 2026

Reducing Reasoning Costs: The Path of Optimization for Chain of Thought via Sparse Attention Mechanism

arXiv 2411.09111 ↗First posted 14 Nov 2024cs.LGcited by 4

On the map: LLM reasoning → Prompting and chain-of-thought reasoning

Abstract (arXiv)

In order to address the chain of thought in the large language model inference cost surge, this research proposes to use a sparse attention mechanism that only focuses on a few relevant tokens. The researcher constructed a new attention mechanism and used GiantRabbit trained with custom GPTs as an experimental tool. The experiment tested and compared the reasoning time, correctness score and chain of thought length of this model and o1 Preview in solving the linear algebra test questions of MIT OpenCourseWare. The results show that GiantRabbit's reasoning time and chain of thought length are significantly lower than o1 Preview. It verifies the feasibility of sparse attention mechanism for optimizing chain of thought reasoning. Detailed architectural details and experimental process have been uploaded to Github, the link is:https://github.com/brucewang123456789/GeniusTrail.git.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Placed in Prompting and chain-of-thought reasoning, one of 17 directions in LLM reasoning. Builds on 19 of its 28 references that are in the map. First posted on arXiv 14 Nov 2024.

Builds on

19 of 28 references.

Closest ancestors · 3

Same direction, newest first

  1. 2024Chain of Thought Empowers Transformers to Solve Inherently Serial Problems20 Feb
  2. 2024The Impact of Reasoning Step Length on Large Language Models10 Jan
  3. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Models28 Jan

Other references · 16

  1. 2017Attention Is All You Needcited by 59,932
  2. 2020Reformer: The Efficient Transformercited by 1,658
  3. 2023SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shotcited by 1,090
  4. 2022Decomposed Prompting: A Modular Approach for Solving Complex Taskscited by 554
  5. 2022Transformer Feed-Forward Layers Build Predictions by Promoting Concepts in the Vocabulary Spacecited by 522
  6. 2021Nystr"omformer: A Nystr"om-Based Algorithm for Approximating Self-Attentioncited by 468
  7. 2016From Softmax to Sparsemax: A Sparse Model of Attention and Multi-Label Classificationcited by 337
  8. 2023Compositional Chain-of-Thought Prompting for Large Multimodal Modelscited by 160
  9. 2024Evaluation of OpenAI o1: Opportunities and Challenges of AGIcited by 127
  10. 2023A Survey of Graph Meets Large Language Model: Progress and Future Directionscited by 84
  11. 2024GPT-4 Jailbreaks Itself with Near-Perfect Success Using Self-Explanationcited by 24
  12. 2022Transkimmer: Transformer Learns to Layer-wise Skimcited by 21
4 more
  1. 2022LSG Attention: Extrapolation of pretrained Transformers to long sequencescited by 16
  2. 2022A microstructure estimation Transformer inspired by sparse representation for diffusion MRIcited by 14
  3. 2021Predicting Attention Sparsity in Transformerscited by 13
  4. 2024Focus on the Core: Efficient Attention via Pruned Token Compression for Document Classificationcited by 7

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 1; 2026: 1.

4 papers.

  1. 2025TwT: Thinking without Tokens by Habitual Reasoning Distillation with Multi-Teachers' Guidancecited by 11
  2. 2024Mitigating Sycophancy in Decoder-Only Transformer Architectures: Synthetic Data Interventioncited by 5
  3. 2026FROST: Filtering Reasoning Outliers with Attention for Efficient Reasoningcited by 5
  4. 2024"Moralized" Multi-Step Jailbreak Prompts: Black-Box Testing of Guardrails in Large Language Models for Verbal Attackscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026An Asymptotic Theory of Chain-of-Thought in In-Context Learning
  2. 2024From Sparse Dependence to Sparse Attention: Unveiling How Chain-of-Thought Enhances Transformer Sample Efficiency
  3. 2026Neural Chain-of-Thought Search: Searching the Optimal Reasoning Path to Enhance Large Language Models
  4. 2025How does Chain of Thought Think? Mechanistic Interpretability of Chain-of-Thought Reasoning with Sparse Autoencoding
  5. 2024Training Nonlinear Transformers for Chain-of-Thought Inference: A Theoretical Generalization Analysis
  6. 2025Efficient Reasoning for LLMs through Speculative Chain-of-Thought
  7. 2025Focused Chain-of-Thought: Efficient LLM Reasoning via Structured Input Information
  8. 2024Chain of Preference Optimization: Improving Chain-of-Thought Reasoning in LLMs