Papers with Code 아카이브

Table Retrieval

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

하위 태스크
0
평가표
1
보존된 평가 기록
5

When given a query, the goal of this task is to retrieve a relevant table from a (potentially large) collection of tables. The query could be a single sentence (such as a question), or it could also be a conversation. As for the retrieval, the tables could be in the raw form (i.e. the values of each cells), the metadata (such as the title, description), or summary statistics.

데이터셋

출처에 같은 태스크 이름으로 연결된 데이터셋입니다. 동명 태스크가 포함될 수 있으므로, 비교할 때는 평가 결과의 조건도 확인하세요.

CompMix-IR

CompMix-IR Dataset Overview: Characteristics: CompMix-IR is a heterogeneous knowledge retrieval benchmark dataset, featuring four knowledge types (text, knowledge graphs, tables, and infoboxes), 9,400+ QA pairs, and a corpus of 10 million entries. It supports two retrieval scenarios: retrieving across all knowledge types or retrieving specific types based on user instructions. Motivation: It addresses the limitations of existing benchmarks by providing a more comprehensive and realistic dataset that reflects real-world retrieval needs with diverse knowledge sources and user intents. Potential Use Cases: Ideal for developing and evaluating heterogeneous IR models, instruction-aware retrieval systems, and open-domain QA systems. It can also be used for benchmarking, cross-domain IR research, and enhancing the adaptability and robustness of retrieval models.

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.