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cs.CL2026
QChunker: Learning Question-Aware Text Chunking for Domain RAG via Multi-Agent Debate
Jihao Zhao, Daixuan Li, Pengfei Li +3
The effectiveness upper bound of retrieval-augmented generation (RAG) is fundamentally constrained by the semantic integrity and information granularity of text chunks in its knowl…
cs.CL2020★ 22 cited
CPM: A Large-scale Generative Chinese Pre-trained Language Model
Zhengyan Zhang, Xu Han, Hao Zhou +22
Pre-trained Language Models (PLMs) have proven to be beneficial for various downstream NLP tasks. Recently, GPT-3, with 175 billion parameters and 570GB training data, drew a lot o…