基于整体句子语义的无监督词汇替换候选排序研究被撤稿

This paper has been withdrawn by Zhongyang Hu

No PDF available, click to view other formats

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 semantic differences before and after substitution. However, effectively modeling the bidirectional influence of candidate substitution on both the target word and its context remains challenging. Existing methods often focus solely on semantic changes at the target position or rely on parameter tuning over multiple evaluation metrics, making it difficult to accurately characterize semantic variation. To address this, we investigate two approaches: one based on attention weights and another leveraging the more interpretable integrated gradients method, both designed to measure the influence of context tokens on the target token and to rank candidates by incorporating semantic similarity between the original and substituted sentences. Experiments on the LS07 and SWORDS datasets demonstrate that both approaches improve ranking performance.

Comments:	A paper I recently submitted has been accepted; it shares the same title but the content is slightly different.
Subjects:	Computation and Language (cs.CL); Artificial Intelligence (cs.AI)
Cite as:	arXiv:2509.11513 [cs.CL]
	(or arXiv:2509.11513v2 [cs.CL] for this version)
	https://doi.org/10.48550/arXiv.2509.11513 arXiv-issued DOI via DataCite

Submission history

From: Zhongyang Hu [view email]
[v1] Mon, 15 Sep 2025 01:57:09 UTC (18 KB)
[v2] Wed, 11 Nov 2026 13:19:28 UTC (1 KB) (withdrawn)