# structured generation

Published articles for structured generation.

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## Synthetic Data Generation for Financial AI Research with NVIDIA NeMo

DevFeed: [Synthetic Data Generation for Financial AI Research with NVIDIA NeMo](<https://devfeed.tech/articles/synthetic-data-generation-for-financial-ai-research-with-nvidia-nemo-6943.md>)

Original publisher: [Read original article](<https://developer.nvidia.com/blog/synthetic-data-generation-for-financial-ai-research-with-nvidia-nemo/>)

Author: Elizabeth Goodman

Published: 2026-07-09T19:40:37Z

Content type: article

Language: en

Sources: [NVIDIA Developer](<https://devfeed.tech/sources/nvidia-developer.md>), [NVIDIA Technical Blog](<https://devfeed.tech/sources/nvidia-technical-blog.md>)

Topics: [Synthetic Data Generation](<https://devfeed.tech/topics/synthetic-data-generation.md>), [synthetic-data](<https://devfeed.tech/topics/synthetic-data.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>), [Fine-tuning](<https://devfeed.tech/topics/fine-tuning.md>), [Natural language processing](<https://devfeed.tech/topics/nlp.md>), [Nemotron](<https://devfeed.tech/topics/nemotron.md>), [vllm](<https://devfeed.tech/topics/vllm.md>), [datasets](<https://devfeed.tech/topics/datasets.md>)

Tags: [agentic-ai-generative-ai](<https://devfeed.tech/tags/agentic-ai-generative-ai.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-agent](<https://devfeed.tech/tags/ai-agent.md>), [ai-ready-data](<https://devfeed.tech/tags/ai-ready-data.md>), [cloud-services](<https://devfeed.tech/tags/cloud-services.md>), [compute](<https://devfeed.tech/tags/compute.md>), [data](<https://devfeed.tech/tags/data.md>), [data-science](<https://devfeed.tech/tags/data-science.md>), [featured](<https://devfeed.tech/tags/featured.md>), [financial-services](<https://devfeed.tech/tags/financial-services.md>), [fine-tuning](<https://devfeed.tech/tags/fine-tuning.md>), [generation](<https://devfeed.tech/tags/generation.md>), [hardware](<https://devfeed.tech/tags/hardware.md>), [inference](<https://devfeed.tech/tags/inference.md>), [llms](<https://devfeed.tech/tags/llms.md>), [models](<https://devfeed.tech/tags/models.md>), [natural-language-processing](<https://devfeed.tech/tags/natural-language-processing.md>), [nemo](<https://devfeed.tech/tags/nemo.md>), [nemotron](<https://devfeed.tech/tags/nemotron.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [research](<https://devfeed.tech/tags/research.md>), [structured-generation](<https://devfeed.tech/tags/structured-generation.md>), [synthetic](<https://devfeed.tech/tags/synthetic.md>), [synthetic-data](<https://devfeed.tech/tags/synthetic-data.md>), [synthetic-data-generation](<https://devfeed.tech/tags/synthetic-data-generation.md>), [vllm](<https://devfeed.tech/tags/vllm.md>), [workflow](<https://devfeed.tech/tags/workflow.md>)

### AI overview

This developer article presents an iterative pipeline for generating a diverse synthetic dataset of more than 500,000 financial news headlines. It combines NeMo Data Designer for structured generation, NeMo Curator for semantic deduplication, Nemotron models for synthesis, and a farthest-from-centroid few-shot strategy to reduce repetition and correct category imbalance.

### Source excerpt

Fine-tuning LLMs for financial natural language processing (NLP) is constrained by limited, imbalanced data. Real-world financial news overrepresents earnings...

## CodeAgents + Structure: A Better Way to Execute Actions

DevFeed: [CodeAgents + Structure: A Better Way to Execute Actions](<https://devfeed.tech/articles/codeagents-structure-a-better-way-to-execute-actions-7494.md>)

Original publisher: [Read original article](<https://huggingface.co/blog/structured-codeagent>)

Author: Aksel Joonas Reedi; Aymeric Roucher

Published: 2025-05-28T00:00:00Z

Content type: article

Language: en

Sources: [Hugging Face - Blog](<https://devfeed.tech/sources/hugging-face-blog.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [AI Development](<https://devfeed.tech/topics/ai-development.md>), [Code](<https://devfeed.tech/topics/code.md>), [Python](<https://devfeed.tech/topics/python.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>), [gaia](<https://devfeed.tech/topics/gaia.md>), [JSON](<https://devfeed.tech/topics/json.md>), [Parsing](<https://devfeed.tech/topics/parsing.md>)

Tags: [agents](<https://devfeed.tech/tags/agents.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-agents](<https://devfeed.tech/tags/ai-agents.md>), [artificial-intelligence](<https://devfeed.tech/tags/artificial-intelligence.md>), [code](<https://devfeed.tech/tags/code.md>), [coding](<https://devfeed.tech/tags/coding.md>), [community](<https://devfeed.tech/tags/community.md>), [gaia](<https://devfeed.tech/tags/gaia.md>), [llm](<https://devfeed.tech/tags/llm.md>), [nlp](<https://devfeed.tech/tags/nlp.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [python](<https://devfeed.tech/tags/python.md>), [smolagents](<https://devfeed.tech/tags/smolagents.md>), [structured-generation](<https://devfeed.tech/tags/structured-generation.md>), [tools](<https://devfeed.tech/tags/tools.md>)

### AI overview

The article compares traditional JSON-based tool-calling agents with CodeAgents that generate executable Python. It explains that code-based actions provide more flexible tool composition, state management, loops, functions, conditionals, and hypothesis testing, while motivating structured generation to avoid errors when parsing code from Markdown.

### Source excerpt

We're on a journey to advance and democratize artificial intelligence through open source and open science.

## Releasing Outlines-core 0.1.0: structured generation in Rust and Python

DevFeed: [Releasing Outlines-core 0.1.0: structured generation in Rust and Python](<https://devfeed.tech/articles/releasing-outlines-core-0-1-0-structured-generation-in-rust-and-python-7432.md>)

Original publisher: [Read original article](<https://huggingface.co/blog/outlines-core>)

Author: bwillard; David Holtz; Erik Kaunismäki; Kaustubh Chaudhari; Remi Louf; Umut Şahin; Will Kurt

Published: 2024-10-22T00:00:00Z

Content type: release

Language: en

Sources: [Hugging Face - Blog](<https://devfeed.tech/sources/hugging-face-blog.md>)

Topics: [Rust](<https://devfeed.tech/topics/rust.md>), [Python](<https://devfeed.tech/topics/python.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Open Source](<https://devfeed.tech/topics/open-source.md>)

Tags: [chain-of-thought](<https://devfeed.tech/tags/chain-of-thought.md>), [format](<https://devfeed.tech/tags/format.md>), [function-calling](<https://devfeed.tech/tags/function-calling.md>), [generation](<https://devfeed.tech/tags/generation.md>), [llm](<https://devfeed.tech/tags/llm.md>), [llms](<https://devfeed.tech/tags/llms.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [python](<https://devfeed.tech/tags/python.md>), [rust](<https://devfeed.tech/tags/rust.md>), [structured-generation](<https://devfeed.tech/tags/structured-generation.md>), [synthetic-data](<https://devfeed.tech/tags/synthetic-data.md>)

### AI overview

The article announces Outlines-core 0.1.0, a lightweight Rust core with Python bindings for structured generation. It describes performance, portability, and integration improvements, and explains how constrained generation makes LLM outputs conform to formats such as JSON, Pydantic models, regular expressions, and context-free grammars.

### Source excerpt

We're on a journey to advance and democratize artificial intelligence through open source and open science.