mlsanityData to 7 Oct 2026

Beyond Surface Similarity: Detecting Subtle Semantic Shifts in Financial Narratives

arXiv 2403.14341 ↗First posted 21 Mar 2024cs.CLcited by 13

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Abstract (arXiv)

In this paper, we introduce the Financial-STS task, a financial domain-specific NLP task designed to measure the nuanced semantic similarity between pairs of financial narratives. These narratives originate from the financial statements of the same company but correspond to different periods, such as year-over-year comparisons. Measuring the subtle semantic differences between these paired narratives enables market stakeholders to gauge changes over time in the company's financial and operational situations, which is critical for financial decision-making. We find that existing pretrained embedding models and LLM embeddings fall short in discerning these subtle financial narrative shifts. To address this gap, we propose an LLM-augmented pipeline specifically designed for the Financial-STS task. Evaluation on a human-annotated dataset demonstrates that our proposed method outperforms existing methods trained on classic STS tasks and generic LLM embeddings.

Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). Builds on 20 of its 49 references that are in the map. First posted on arXiv 21 Mar 2024.

Builds on

20 of 49 references.

References · 20

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8 more
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 3; 2025: 8; 2026: 2.

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  1. 2025FinMTEB: Finance Massive Text Embedding Benchmarkcited by 18
  2. 2024Do We Need Domain-Specific Embedding Models? An Empirical Investigationcited by 12
  3. 2024EconNLI: Evaluating Large Language Models on Economics Reasoningcited by 8
  4. 2025TWICE: What Advantages Can Low-Resource Domain-Specific Embedding Model Bring? -- A Case Study on Korea Financial Textscited by 3
  5. 2025Language Modeling for the Future of Finance: A Survey into Metrics, Tasks, and Data Opportunitiescited by 3
  6. 2024Same Company, Same Signal: The Role of Identity in Earnings Call Transcriptscited by 2
  7. 2025Adapting General-Purpose Embedding Models to Private Datasets Using Keyword-based Retrievalcited by 2
  8. 2025FinCap: Topic-Aligned Captions for Short-Form Financial YouTube Videoscited by 2
  9. 2025NMIXX: Domain-Adapted Neural Embeddings for Cross-Lingual eXploration of Financecited by 1
  10. 2025Revealing the Numeracy Gap: An Empirical Investigation of Text Embedding Modelscited by 1
  11. 2025Advances and Challenges in Semantic Textual Similarity: A Comprehensive Surveycited by 1
  12. 2026An Algorithmic Framework for Systematic Literature Reviews: A Case Study for Financial Narrativescited by 0
1 more
  1. 2026Grounding Large Language Models in DSGE Simulators for Policy Generation and Forecastingcited by 0