title: EquivPruner: Boosting Efficiency and Quality in LLM-Based Search via
    Action Pruning
summary: Large Language Models (LLMs) excel at complex reasoning through search
  algorithms, yet current strategies often suffer from massive token consumption
  due to redundant exploration of semantically equivalent steps. Existing
  semantic similarity methods struggle to accurately identify such equivalence in
  domain-specific contexts like mathematical reasoning. To address this, we
  propose EquivPruner, a simple yet effective approach that identifies and prunes
  semantically equivalent actions during LLM reasoning search. We also introduce
  MathEquiv, the first dataset we created for mathematical statement equivalence,
  which enables the training of a lightweight equivalence detector. Extensive
  experiments across various models and tasks demonstrate that EquivPruner
  significantly reduces token consumption, improving searching efficiency and
  often bolstering reasoning accuracy. For instance, when applied to
  Qwen2.5-Math-7B-Instruct on GSM8K, EquivPruner reduced token consumption by
  48.1\% while also improving accuracy. Our code is available at
  https://github.com/Lolo1222/EquivPruner.
paper_authors._id: 6830109ea20ebb4738e76931
paper_authors.name: Jiawei Liu
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2025-05-26T08:15:09.111Z
paper_authors._id: 6747d38098fe79433a8c4580
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/no-auth/BrcsTfusqfu9p9uv1NeX6.png
paper_authors.fullname: Jiawei Liu
paper_authors.type: user
paper_authors.user: Jiawei1222
paper_authors._id: 6830109ea20ebb4738e76932
paper_authors.name: Qisi Chen
paper_authors._id: 6830109ea20ebb4738e76933
paper_authors.name: Jianshu Zhang
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-05-27T12:42:26.545Z
paper_authors._id: 65d8b0f0661492b25c6623de
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/65d8b0f0661492b25c6623de/c6LPDse8NIV_3BHIu8dYe.png
paper_authors.fullname: Jianshu Zhang
paper_authors.type: user
paper_authors.user: Sterzhang
paper_authors._id: 6830109ea20ebb4738e76934
paper_authors.name: Quan Liu
paper_authors._id: 6830109ea20ebb4738e76935
paper_authors.name: Defu Lian
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-05-27T12:42:48.468Z
paper_authors._id: 66ed026076a8038cb4ae6053
paper_authors.avatarUrl: /avatars/99b6527da6b66c6b5df3fc8261587322.svg
paper_authors.fullname: Defu Lian
paper_authors.type: user
paper_authors.user: dove-ustc
paper_title: EquivPruner: Boosting Efficiency and Quality in LLM-Based Search via
    Action Pruning
paper_summary: Large Language Models (LLMs) excel at complex reasoning through search
  algorithms, yet current strategies often suffer from massive token consumption
  due to redundant exploration of semantically equivalent steps. Existing
  semantic similarity methods struggle to accurately identify such equivalence in
  domain-specific contexts like mathematical reasoning. To address this, we
  propose EquivPruner, a simple yet effective approach that identifies and prunes
  semantically equivalent actions during LLM reasoning search. We also introduce
  MathEquiv, the first dataset we created for mathematical statement equivalence,
  which enables the training of a lightweight equivalence detector. Extensive
  experiments across various models and tasks demonstrate that EquivPruner
  significantly reduces token consumption, improving searching efficiency and
  often bolstering reasoning accuracy. For instance, when applied to
  Qwen2.5-Math-7B-Instruct on GSM8K, EquivPruner reduced token consumption by
  48.1\% while also improving accuracy. Our code is available at
  https://github.com/Lolo1222/EquivPruner.
paper_ai_summary: EquivPruner reduces token consumption and improves reasoning accuracy by pruning semantically equivalent actions in LLM searches, leveraging a new dataset for mathematical equivalence.
paper_ai_keywords: Large Language Models (LLMs) semantic similarity semantically equivalent actions EquivPruner MathEquiv equivalence detector GSM8K