Papers with Code 아카이브

Conversational Search

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

하위 태스크
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평가표
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보존된 평가 기록
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데이터셋

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

BeNYfits

Click to add a brief description of the dataset (Markdown and LaTeX enabled). Provide: * a high-level explanation of the dataset characteristics * explain motivations and summary of its content * potential use cases of the dataset An agent benchmark for adaptive decision-making in dialog measuring agent accuracy and dialog turn efficiency in helping users determine eligibility for public, real-world opportunities. This dataset containss the following: * Natural language descriptions of 82 NYC public benefits programs (e.g., tax credits, childcare, subsidized AC) Two simulated user datasets containing all features relevant to that household's eligibility: * Representative: 25 households with features drawn from real NYC demographic data * Diverse: 56 households which, collectively, satisfy nearly every possible acceptance/rejection criteria in all 82 public benefits opportunities

ICConv

The dataset contains 105,811 information-seeking conversations converted from MS MARCO. This dataset is constructed to relieve the data scarcity problem of conversational search to an extent. Considering the multi-intent problem and contextual information, this large-scale intent-oriented and context-aware dataset is automatically constructed based on the web search session data in MS MARCO. This dataset can be used to train and evaluate conversational search systems.

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