Howcan we adapt a retrieval-based LM for a task? Whenshould we use a retrieval-based LM? 针对How,目前主要的求解范式可以被分为:Fine-tuning,Reinforcement learning,Prompting;并且这三者可同时出现并利用,具体形式如下所示: How can we adapt a retrieval-based LM for a task? 虽然Fine-tuning与Reinfor...
本文主要是对 ACL 2023 Tutorial: Retrieval-based Language Models and Applications部分的Section 3: Retrieval-based LMs: Architecture进行梳理总结Roadmap检索式LM的分类nearest-neighbor LMretrieve and rea…
Iterative retrieval in RAG models is a process where doc-uments are repeatedly collected based on the initial query and the text generated thus far, providing a more compre-hensive knowledge base for LLMs [Borgeaud et al., 2022, Arora et al., 2023]. This approach has been shown to en-...
This paper proposes a Long-term knowledge-based Multimedia retrieval System (LMS) based on Latent Semantic Indexing (LSI) and human interaction (RF). Experiments show the effectiveness of the proposed system.doi:10.1504/IJASS.2007.019304Xin Chen...
YuLan-IR: Information Retrieval Boosted LMs. Contribute to RUC-GSAI/YuLan-IR development by creating an account on GitHub.
RECOMP: Improving Retrieval-Augmented LMs with Compression and Selective Augmentation Fangyuan Xu, Weijia Shi, Eunsol Choi 2023 KILT: a Benchmark for Knowledge Intensive Language Tasks F. Petroni, Aleksandra Piktus, Angela Fan, Patrick Lewis, Majid Yazdani, Ni...
Dense Text Retrieval based on Pretrained Language Models: A Survey Wayne Xin Zhao, Jing Liu, Ruiyang Ren, Ji-Rong Wen TOIS – Dec 2023 [paper] Retrieval-Augmented Generation for Large Language Models: A Survey Yunfan Gao, Yun Xiong, Xinyu Gao, Kangxiang Jia, Jinliu Pan, Yuxi Bi, Yi Dai...
Language Models (LMs), in their most basic form, perform just like any other machine learning model - they produce interpolations and extrapolations based ... Y Ding,J Nie,D Wu,... - Southeastcon 被引量: 0发表: 0年 Why do Nearest Neighbor Language Models Work? However recently, retriev...
基于contrastive learning的思想,模型选择双塔双塔BERT,使用in-batch training的方式进行训练,获取数据集合对应的embedding,然后使用FAISS建立索引。损失函数如下: L(qi,pi+,pi,1−,...,pi,n−)=−logesim(qi,pi+)esim(qi,pi+)+∑j=1nesim(qi,pi,j−) 样本选择 这里的数据是Question-Answer数据,正样...
How to adapt a retrieval-based LM for a task Fine-tuning Reinforcement learning Prompting When to use a retrieval-based LM 长尾:针对长尾效果欠佳(long tail) Large Language Models Struggle to Learn Long-Tail Knowledge When Not to Trust Language Models: Investigating Effectiveness of Parametric and ...