这篇文章提出的时候已经到了2021年的11月,杨植麟团队提出了一种新的预训练范式,Task-driven Language Modeling (TLM),根据下游需要完成的任务来有针对性的进行上游预训练数据的筛选。这种针对性的预训练可以大幅度加速下游的微调时间,从而取得更好的效果。 TLM的流程 这篇文章我问了很多人的观点,国内外的研究者的观...
训练任务:检索和生成联合训练(unsupervised data) Prefix language modeling LM:一个由N个单词组成的块,并将这个块分成两个长度相等的子序列N/2。然后,输入第一个子序列,生成第二个子序列 检索:第一个子序列用作查询,第二个子序列对应于输出检索 Masked language modeling LM:15%的长度为3的token mask掉预测 检...
SUFFIX RETRIEVAL-AUGMENTED LANGUAGE MODELINGZecheng Wang and Yik-Cheung TamNYU ShanghaiDepartment of Computer Science567 West Yangsi Road, Pudong New District, Shanghai 200126, ChinaABSTRACTCausal language modeling (LM) uses word history to predict thenext word. BERT, on the other hand, makes use...
Supportiveness-based Knowledge Rewriting for Retrieval-augmented Language Modeling Zile Qiao, Wei Ye, Yong Jiang, Tong Mo, Pengjun Xie, Weiping Li, Fei Huang, Shikun Zhang 2024 Self-Knowledge Guided Retrieval Augmentation for Large Language Models ...
using masked language modeling as the learning signal and backpropagating through a retrieval step that considers millions of documents. We demonstrate the effectiveness of Retrieval-Augmented Language Model pre-training (REALM) by fine-tuning on the challenging task of Open-domain Question Answering (...
Signalfrom the language modeling objective backpropagates all the waythrough the retriever, which must consider millions of documentsin Z—a signif i cant computational challenge that we address.correctly predict the missing word in the following sen-tence: “ The is the currency of the UnitedKing...
It uses a pre-trained T5 to initialize the encoder-decoder language model and a pre-trained Contriever for the dense retriever, improv-ing its efficiency for complex language modeling tasks. Atlas[Izacard等人,2022]还在预训练和微调阶段将检索机制纳入T5架构[rafael等人,2020]。它使用预训练的T5来初始...
We introduce REPLUG, a retrieval-augmented language modeling framework that treats the language model (LM) as a black box and augments it with a tuneable retrieval model. Unlike prior retrieval-augmented LMs that train language models with special cross attention mechanisms to encode the retrieved ...
Retrieval-Augmented Multimodal Language Modeling 来自 Semantic Scholar 喜欢 0 阅读量: 68 作者: Michihiro Yasunaga,Armen Aghajanyan,Weijia Shi,Rich James,J. Leskovec,Percy Liang,M. Lewis,Luke Zettlemoyer,Wen-tau Yih 展开 摘要: Recent multimodal models such as DALL-E and CM3 have achieved ...
a method designed to enhance the capabilities of long-context language modeling by utilizing an external retriever for historical information retrieval. MemLong combines a non-differentiable ``ret-mem'' module with a partially trainable decoder-only language model and introduces a fine-grained, controll...