SPARTA
Scalable and Principled Benchmark of Tree-Structured Multi-hop QA over Text and Tables
SPARTA introduces a revolutionary approach to creating benchmarks for multi-hop question answering that spans both structured tables and unstructured text. This work addresses the critical need for standardized evaluation in multi-modal QA systems.
Innovation
SPARTA presents a fully automated SQL-centric pipeline that constructs tree-structured multi-hop QA benchmarks by unifying structured and unstructured evidence from tables and text into a single relational representation.
Key Features
Automated Pipeline
- SQL-Centric Design: Leverages SQL’s expressive power for complex query construction
- Tree-Structured Reasoning: Models multi-hop reasoning as traversable tree structures
- Cross-Modal Integration: Seamlessly combines tabular and textual evidence
Scalability
- Fully Automated: Reduces human annotation requirements
- Principled Construction: Ensures consistent quality across generated benchmarks
- Extensible Framework: Adaptable to various domains and data types
Technical Approach
The system transforms the challenge of multi-modal QA into a unified relational framework where:
- Tables provide structured factual information
- Text offers contextual and descriptive details
- SQL Queries define the reasoning paths required to answer questions
Impact on Research
SPARTA addresses several critical challenges in the field:
- Benchmark Standardization: Provides consistent evaluation metrics
- Multi-Modal Integration: Advances techniques for combining different data modalities
- Reasoning Complexity: Enables evaluation of sophisticated multi-hop reasoning capabilities
Applications
The framework enables researchers to:
- Evaluate multi-modal QA systems consistently
- Generate large-scale benchmarks efficiently
- Study complex reasoning patterns across modalities
- Advance the field of structured and unstructured data integration
Status
Currently under review, representing cutting-edge research in automated benchmark generation for multi-modal question answering systems.
