Papers with quantitative methods

2 papers
FinLLM-B: When Large Language Models Meet Financial Breakout Trading (2025.naacl-industry)

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Challenge: Existing methods for financial breakout detection are subpar, despite large data and knowledge required.
Approach: They propose a financial breakout dataset and introduce FinLLM-B, a large language model for financial breakout detection.
Outcome: The proposed model outperforms GPT-3.5 in the field of financial breakout detection.
Queens are Powerful too: Mitigating Gender Bias in Dialogue Generation (2020.emnlp-main)

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Challenge: Social biases present in data are often directly reflected in the predictions of models trained on that data.
Approach: They analyze gender bias in dialogue data and propose techniques to mitigate it . they use counterfactual data augmentation, targeted data collection, and bias controlled training .
Outcome: The proposed techniques mitigate gender bias by balancing genderedness of generated dialogue utterances.

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