Papers with grouping methods
Group, Extract and Aggregate: Summarizing a Large Amount of Finance News for Forex Movement Prediction (D19-51)
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| Challenge: | Existing studies on forex prediction ignore related text completely and focus on forex trade data only, which loses important semantic information. |
| Approach: | They propose a BERT-based Hierarchical Aggregation Model to summarize forex news . they group news from different aspects and extract the most crucial news in each group . |
| Outcome: | The proposed model outperforms baseline methods and grouping methods and summarizes the influence patterns for forex trading. |
Analyzing and Evaluating Correlation Measures in NLG Meta-Evaluation (2025.naacl-long)
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| Challenge: | Existing studies have not investigated the differences between different correlation measures in meta-evaluation. |
| Approach: | They analyze 12 common correlation measures using real-world data from six widely-used NLG evaluation datasets and 32 evaluation metrics. |
| Outcome: | The proposed measures exhibit the best performance in discriminative power and ranking consistency . the measures using system-level grouping or Kendall correlation are the least sensitive to score granularity . |
CORG: Generating Answers from Complex, Interrelated Contexts (2025.naacl-long)
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| Challenge: | Existing approaches to analyzing knowledge in a corpus often focus on single factors in isolation. |
| Approach: | They propose a framework that organizes multiple contexts into independently processed groups . they classify these relationships into distracting, ambiguous, counterfactual, and duplicated . |
| Outcome: | The proposed framework outperforms existing grouping methods and single-context approaches. |