AB
AB
AiBoss

All Categories

project

InftyThink - An infinite-depth reasoning paradigm jointly launched by Zhejiang University and Peking University

InftyThink is an innovative paradigm for large-scale model inference, overcoming the limitations of traditional models in long-duration inference tasks. It breaks down complex inference processes into multiple short segments through segmented iteration, generating an intermediate summary after each segment...

What is InftyThink?

InftyThink is an innovative large-scale model reasoning paradigm that breaks through the limitations of traditional models in long reasoning tasks. By using a segmented iterative approach, it breaks down complex reasoning processes into multiple short segments, generating intermediate summaries after each segment, thus achieving block-based thinking. This "zigzag" memory pattern—periodically discarding old details and retaining new summaries—effectively reduces computational complexity, enabling the model to handle theoretically infinitely long reasoning chains.

InftyThink's technical principles

  • Iterative Reasoning and Periodic SummaryInftyThink breaks down the traditional single, continuous reasoning process into multiple short reasoning segments, generating a concise summary after each segment as contextual input for the next stage of reasoning. This simulates the human cognitive process of gradual inductive summarization, enabling the model to perform infinitely deep reasoning while maintaining contextual coherence, thus overcoming the limitations of traditional long reasoning in terms of context length and computational complexity.
  • Fixed computational overhead and context windowInftyThink implements a "zigzag" memory usage pattern, clearing the context of the previous round after each short inference round and retaining only the summary, significantly reducing the computational complexity during inference. Compared to traditional inference paradigms, InftyThink achieves a better balance between inference depth and computational efficiency.
  • Decoupled from the original architecture and highly compatible with training paradigmsInftyThink does not rely on adjustments to the model structure; instead, it achieves its paradigm by reconstructing training data into a multi-round inference format. It can seamlessly integrate with existing pre-trained models, fine-tuning, and reinforcement learning processes, demonstrating strong engineering feasibility.
  • Develop data reconstruction technologyInftyThink has developed a method to convert existing long text inference datasets into an iterative format. For example, the OpenR1-Math dataset is converted into 333,000 training instances, facilitating model training under this paradigm.

InftyThink's core advantages

  • Breaking the context window limitationThrough iterative reasoning and intermediate summarization, InftyThink can handle theoretically infinitely long inference chains, breaking through the limitations of traditional large model context windows.
  • Reduce computing costsCompared to traditional long inference methods, InftyThink reduces the direct processing of long sequences during inference, significantly lowering computational costs.
  • Improve reasoning performanceIn some complex reasoning tasks, InftyThink can better handle long sequence information, improving the accuracy of reasoning and the throughput of generation.

InftyThink's project address

Application scenarios of InftyThink

  • Solving mathematical problemsInftyThink can handle complex mathematical problems by gradually solving long-chain mathematical problems through segmented iterative reasoning and intermediate summarization.
  • Logical reasoningIn tasks requiring long-sequence logical reasoning, InftyThink can effectively improve the accuracy and efficiency of reasoning.
  • Code generationIn code generation tasks, InftyThink can generate complex code logic step by step, maintaining code coherence and correctness.
  • Intelligent tutoringIn the intelligent tutoring system, InftyThink can provide detailed answers and explanations step by step based on students' questions, helping students better understand and master knowledge points.
  • Drug developmentIn the drug development process, InftyThink can be used to predict the 3D structure and binding affinity of drug targets, thus accelerating the development process.
Back