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References (12)

[1]
Reasoning or Overthinking: Evaluating Large Language Models on Financial Sentiment Analysis
2025Dimitris Vamvourellis, Dhagash Mehta
[2]
Targeted Distillation for Sentiment Analysis
2025Yice Zhang, Guangyu Xie et al.
[3]
Explainable Sentiment Analysis With DeepSeek-R1: Performance, Efficiency, and Few-Shot Learning
2025Donghao Huang, Zhaoxia Wang
[4]
A review of Chinese sentiment analysis: subjects, methods, and trends
2025Zhaoxia Wang, Donghao Huang et al.
[5]
DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
2025Adam Suma, Samuel Dauncey
[6]
Deciphering the Factors Influencing the Efficacy of Chain-of-Thought: Probability, Memorization, and Noisy Reasoning
2024Akshara Prabhakar, Thomas L. Griffiths et al.
[7]
A Survey on Knowledge Distillation of Large Language Models
2024Xiaohan Xu, Ming Li et al.
[8]
Sentiment Analysis in the Era of Large Language Models: A Reality Check
2023Wenxuan Zhang, Yue Deng et al.
[9]
Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes
2023Cheng-Yu Hsieh, Chun-Liang Li et al.
[10]
Chain of Thought Prompting Elicits Reasoning in Large Language Models
2022Jason Wei, Xuezhi Wang et al.
[11]
Sentiment Analysis of Online Movie Reviews using Machine Learning
2022Isaiah Steinke, Justin Wier et al.
[12]
Utilization of Oversampling for multiclass sentiment analysis on Amazon Review Dataset
2019Anirban Mukherjee, S. Mukhopadhyay et al.

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