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Found 4 papers, 3 papers with code
Reasoning in Conversation: Solving Subjective Tasks through Dialogue Simulation for Large Language Models
Based on the characteristics of the tasks and the strong dialogue-generation capabilities of LLMs, we propose RiC (Reasoning in Conversation), a method that focuses on solving subjective tasks through dialogue simulation.
Enhancing Multilingual Capabilities of Large Language Models through Self-Distillation from Resource-Rich Languages
While large language models (LLMs) have been pre-trained on multilingual corpora, their performance still lags behind in most languages compared to a few resource-rich languages.
Continual Knowledge Distillation for Neural Machine Translation
While many parallel corpora are not publicly accessible for data copyright, data privacy and competitive differentiation reasons, trained translation models are increasingly available on open platforms.
DirectQuote: A Dataset for Direct Quotation Extraction and Attribution in News Articles
Applying this task to news data is highly related to fact-checking, media monitoring and news tracking.
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