Papers with limited learning

2 papers
From Implicit Exploration to Structured Reasoning: Guideline and Refinement for LLMs (2025.findings-emnlp)

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Challenge: Existing models rely on implicit exploration, which leads to unstable reasoning paths and lack of error correction.
Approach: They propose a framework that shifts from implicit exploration to structured reasoning through guideline and refinement.
Outcome: The proposed model outperforms strong baselines on the Big-Bench Hard benchmark.
CEPT: A Contrast-Enhanced Prompt-Tuning Framework for Emotion Recognition in Conversation (2024.lrec-main)

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Challenge: Emotion recognition in conversation research suffers from data imbalance and the presence of similar linguistic expressions for different emotions.
Approach: They propose a Contrast-Enhanced Prompt-Tuning framework that transforms an ERC task into a Masked Language Modeling task and generates the emotion for each utterance in the conversation.
Outcome: The proposed framework outperforms the state-of-the-art methods on all three benchmark datasets and excels in recognizing minority emotions.

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