#structured-data News & Analysis

6 articles tagged with #structured-data. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

6 articles

AINeutralarXiv – CS AI · 3d ago6/10

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ASTRA: Adaptive Semantic Tree Reasoning Architecture for Complex Table Question Answering

Researchers introduce ASTRA, a new architecture designed to improve how large language models process and reason about complex tables through adaptive semantic tree structures. The method combines tree-based navigation with symbolic code execution to achieve state-of-the-art performance on table question-answering benchmarks, addressing fundamental limitations in how tables are currently serialized for LLMs.

AINeutralarXiv – CS AI · Mar 96/10

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Towards Neural Graph Data Management

Researchers introduce NGDBench, a comprehensive benchmark for evaluating neural networks' ability to work with graph databases across five domains including finance and medicine. The benchmark supports full Cypher query language capabilities and reveals significant limitations in current AI models when handling structured graph data, noise, and complex analytical tasks.

AINeutralarXiv – CS AI · Mar 55/10

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Knowledge Graph and Hypergraph Transformers with Repository-Attention and Journey-Based Role Transport

Researchers present a new transformer architecture that jointly trains on natural language and structured data by maintaining separate knowledge and language representations. The model uses a key-value repository system with journey-based role transport to enable cross-attention between linguistic context and structured knowledge graphs.

AINeutralarXiv – CS AI · Mar 54/10

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Token-Oriented Object Notation vs JSON: A Benchmark of Plain and Constrained Decoding Generation

A benchmark study compares Token-Oriented Object Notation (TOON) with JSON for structured data serialization in LLMs, finding that while TOON reduces token usage, plain JSON shows better accuracy overall. The research reveals that TOON's efficiency benefits may only emerge at scale where syntax savings offset the initial prompt overhead.

AINeutralarXiv – CS AI · Mar 34/106

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LexChronos: An Agentic Framework for Structured Event Timeline Extraction in Indian Jurisprudence

Researchers developed LexChronos, an AI framework that extracts structured event timelines from Indian Supreme Court judgments using a dual-agent architecture. The system achieved 0.8751 F1 score on synthetic data and showed 75% preference over unstructured approaches in legal text summarization tasks.

AINeutralarXiv – CS AI · Mar 24/106

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Heterogeneous Multi-Agent Reinforcement Learning with Attention for Cooperative and Scalable Feature Transformation

Researchers propose a new multi-agent reinforcement learning framework that uses three cooperative agents with attention mechanisms to automate feature transformation for machine learning models. The approach addresses key limitations in existing automated feature engineering methods, including dynamic feature expansion instability and insufficient agent cooperation.