Reimagining Retrieval Augmented Language Models for Answering Queries

2023-06-01 · Wang-Chiew Tan, Yuliang Li, Pedro Rodriguez, Richard James, Xi Victoria Lin, Alon Halevy, Scott Yih

We present a reality check on large language models and inspect the promise of retrieval augmented language models in comparison. Such language models are semi-parametric, where models integrate model parameters and knowledge from external data sources to make their predictions, as opposed to the parametric nature of vanilla large language models. We give initial experimental findings that semi-parametric architectures can be enhanced with views, a query analyzer/planner, and provenance to make a significantly more powerful system for question answering in terms of accuracy and efficiency, and potentially for other NLP tasks

📄 PDF Abstract BibTeX arXiv:2306.01061

Code (0)

등록된 구현이 없습니다.

Tasks

Question Answering Retrieval

HANRAG: Heuristic Accurate Noise-resistant Retrieval-Augmented Generation for Multi-hop Question Answering

2025-09-08 · Duolin Sun, Dan Yang, Yue Shen, Yihan Jiao 외 arxiv

The Retrieval-Augmented Generation (RAG) approach enhances question-answering systems and dialogue generation tasks by integrating information retrieval (IR) technologies with large language models (LLMs). This strategy,…

Multi-hop Question Answering Information Retrieval Dialogue Generation

EfficientRAG: Efficient Retriever for Multi-Hop Question Answering

2024-08-08 · Ziyuan Zhuang, Zhiyang Zhang, Sitao Cheng, Fangkai Yang 외

Retrieval-augmented generation (RAG) methods encounter difficulties when addressing complex questions like multi-hop queries. While iterative retrieval methods improve performance by gathering additional information, cur…

Multi-hop Question Answering Question Answering RAG Retrieval+1

Towards Retrieval Augmented Generation over Large Video Libraries

2024-06-21 · Yannis Tevissen, Khalil Guetari, Frédéric Petitpont

Video content creators need efficient tools to repurpose content, a task that often requires complex manual or automated searches. Crafting a new video from large video libraries remains a challenge. In this paper we int…

Answer Generation Question Answering RAG Retrieval+1

Telco-oRAG: Optimizing Retrieval-augmented Generation for Telecom Queries via Hybrid Retrieval and Neural Routing

2025-05-17 · Andrei-Laurentiu Bornea, Fadhel Ayed, Antonio De Domenico, Nicola Piovesan 외

Artificial intelligence will be one of the key pillars of the next generation of mobile networks (6G), as it is expected to provide novel added-value services and improve network performance. In this context, large langu…

RAG Retrieval Retrieval-augmented Generation

Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question Complexity

2024-03-21 · Soyeong Jeong, Jinheon Baek, Sukmin Cho, Sung Ju Hwang 외

Retrieval-Augmented Large Language Models (LLMs), which incorporate the non-parametric knowledge from external knowledge bases into LLMs, have emerged as a promising approach to enhancing response accuracy in several tas…

Question Answering RAG Retrieval