Papers with semantic similarity methods

2 papers
Learning Thematic Similarity Metric from Article Sections Using Triplet Networks (P18-2)

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Challenge: In this paper, we use Wikipedia articles to learn thematic similarity metric between sentences.
Approach: They propose to leverage the partition of articles into sections to learn thematic similarity metric between sentences.
Outcome: The proposed model outperforms state-of-the-art embeddings on the task of thematic clustering of sentences.
EquivPruner: Boosting Efficiency and Quality in LLM-Based Search via Action Pruning (2026.acl-long)

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Challenge: Existing semantic similarity methods struggle to accurately identify semantically equivalent steps in domain-specific contexts like mathematical reasoning.
Approach: They propose a simple yet effective approach that identifies and prunes semantically equivalent actions during LLM reasoning search.
Outcome: The proposed approach reduces token consumption while improving reasoning efficiency and accuracy on Qwen2.5-Math-7B-Instruct on GSM8K.

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