arXiv:2002.00207
Web Table Extraction, Retrieval and Augmentation: A Survey
원문 초록
Tables are a powerful and popular tool for organizing and manipulating data. A vast number of tables can be found on the Web, which represents a valuable knowledge resource. The objective of this survey is to synthesize and present two decades of research on web tables. In particular, we organize existing literature into six main categories of information access tasks: table extraction, table interpretation, table search, question answering, knowledge base augmentation, and table augmentation. For each of these tasks, we identify and describe seminal approaches, present relevant resources, and point out interdependencies among the different tasks.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
From Roots to Rewards: Dynamic Tree Reasoning with RL
Response Quality Assessment for Retrieval-Augmented Generation via Conditional Conformal Factuality
SimpleDoc: Multi-Modal Document Understanding with Dual-Cue Page Retrieval and Iterative Refinement
TableRAG: A Retrieval Augmented Generation Framework for Heterogeneous Document Reasoning
A Survey of Context Engineering for Large Language Models
RAG-R1 : Incentivize the Search and Reasoning Capabilities of LLMs through Multi-query Parallelism
토론
이 논문과 연결된 포럼 글이 아직 없습니다.