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cs.CL2025
Improving Context Fidelity via Native Retrieval-Augmented Reasoning
Suyuchen Wang, Jinlin Wang, Xinyu Wang +6
Large language models (LLMs) often struggle with context fidelity, producing inconsistent answers when responding to questions based on provided information. Existing approaches ei…
cs.CL2025
Easy Dataset: A Unified and Extensible Framework for Synthesizing LLM Fine-Tuning Data from Unstructured Documents
Ziyang Miao, Qiyu Sun, Jingyuan Wang +4
Large language models (LLMs) have shown impressive performance on general-purpose tasks, yet adapting them to specific domains remains challenging due to the scarcity of high-quali…
cs.CL2020
Meta-Learning for Natural Language Understanding under Continual Learning Framework
Jiacheng Wang, Yong Fan, Duo Jiang +1
Neural network has been recognized with its accomplishments on tackling various natural language understanding (NLU) tasks. Methods have been developed to train a robust model to h…