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Transduction is All You Need for Structured Data Workflows

2025-08-21 · Alfio Gliozzo, Naweed Khan, Christodoulos Constantinides, Nandana Mihindukulasooriya, Nahuel Defosse, Gaetano Rossiello, Junkyu Lee arxiv

This paper introduces Agentics, a functional agentic AI framework for building LLM-based structured data workflow pipelines. Designed for both research and practical applications, Agentics offers a new data-centric paradigm in which agents are embedded within data types, enabling logical transduction between structured states. This design shifts the focus toward principled data modeling, providing a declarative language where data types are directly exposed to large language models and the data values are composed through transductions between input and output types. We present a range of structured data workflow tasks and empirical evidence demonstrating the effectiveness of this approach, including data wrangling, text-to-SQL semantic parsing, and domain-specific multiple-choice question answering, and data-driven scientific discovery tasks.

📄 PDF Abstract BibTeX arXiv:2508.15610

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Tasks

Question Answering Semantic Parsing

Agentics 2.0: Logical Transduction Algebra for Agentic Data Workflows

2026-03-04 · Alfio Massimiliano Gliozzo, Junkyu Lee, Nahuel Defosse arxiv

Agentic AI is rapidly transitioning from research prototypes to enterprise deployments, where requirements extend to meet the software quality attributes of reliability, scalability, and observability beyond plausible te…

Semantic Parsing Text Generation

Deep Tree Transductions - A Short Survey

2019-02-05 · Davide Bacciu, Antonio Bruno

The paper surveys recent extensions of the Long-Short Term Memory networks to handle tree structures from the perspective of learning non-trivial forms of isomorph structured transductions. It provides a discussion of mo…

Survey

Do we need bigram alignment models? On the effect of alignment quality on transduction accuracy in G2P

2015-09-01 · EMNLP 2015 9 · Steffen Eger

Lemmatization Transliteration

Distribution Matching for Transduction

2009-12-01 · NeurIPS 2009 12 · Novi Quadrianto, James Petterson, Alex J. Smola

Many transductive inference algorithms assume that distributions over training and test estimates should be related, e.g. by providing a large margin of separation on both sets. We use this idea to design a transduction …

General Classification regression

Hand-Transformer: Non-Autoregressive Structured Modeling for 3D Hand Pose Estimation

2020-08-01 · ECCV 2020 8 · Lin Huang, Jianchao Tan, Ji Liu, Junsong Yuan

3D hand pose estimation is still far from a well-solved problem mainly due to the highly nonlinear dynamics of hand pose and the difficulties of modeling its inherent structural dependencies. To address this issue, we co…

3D Hand Pose Estimation Decoder Hand Pose Estimation Pose Estimation