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Table-based Question Answering
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Answering questions based on given Tables or Datasets.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Weaver: Interweaving SQL and LLM for Table Reasoning
Synthetic Clarification and Correction Dialogues about Data-Centric Tasks -- A Teacher-Student Approach
Tabular-TX: Theme-Explanation Structure-based Table Summarization via In-Context Learning
ARTEMIS-DA: An Advanced Reasoning and Transformation Engine for Multi-Step Insight Synthesis in Data Analytics
Piece of Table: A Divide-and-Conquer Approach for Selecting Sub-Tables in Table Question Answering
SynTQA: Synergistic Table-based Question Answering via Mixture of Text-to-SQL and E2E TQA
Seek and Solve Reasoning for Table Question Answering
Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding
TableQAKit: A Comprehensive and Practical Toolkit for Table-based Question Answering
Bridging the Gap: Deciphering Tabular Data Using Large Language Model
OmniTab: Pretraining with Natural and Synthetic Data for Few-shot Table-based Question Answering
Table Retrieval May Not Necessitate Table-specific Model Design
Translating Natural Language to SQL using Pointer-Generator Networks and How Decoding Order Matters
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.