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Research paper on lexical substitution withdrawn from arXiv

By PulseAugur Editorial · [1 sources] ·

A research paper titled "Unsupervised Candidate Ranking for Lexical Substitution via Holistic Sentence Semantics" was submitted to arXiv, proposing new methods for ranking candidate words in lexical substitution tasks. The paper, authored by Zhongyang Hu, investigates approaches using attention weights and integrated gradients to measure contextual influence and sentence similarity. Experiments on the LS07 and SWORDS datasets showed improved ranking performance, though the paper has since been withdrawn. AI

IMPACT This research on lexical substitution, while withdrawn, explored novel methods for improving semantic understanding in language models.

RANK_REASON The cluster describes a withdrawn academic paper on a specific NLP task. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Research paper on lexical substitution withdrawn from arXiv

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The cluster describes a withdrawn academic paper on a specific NLP task. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Zhongyang Hu, Naijie Gu, Xiangzhi Tao, Tianhui Gu, Yibing Zhou ·

    Unsupervised Candidate Ranking for Lexical Substitution via Holistic Sentence Semantics

    arXiv:2509.11513v2 Announce Type: replace-cross Abstract: A key subtask in lexical substitution is ranking the given candidate words. A common approach is to replace the target word with a candidate in the original sentence and feed the modified sentence into a model to capture s…

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