This solicitation closed on August 19, 2026

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DPA26BZ04-DV016ClosedSBIR

Fusion of Abstract Learning and Context-Optimized Neural-methods (FALCON)

Department of DefenseDARPA

AI Overview

FALCON seeks to combine large language models with machine learning methods to provide domain-specific analysis of structured and unstructured data at scale. The program will develop architecture, evaluation metrics, and safeguards against hallucination while demonstrating practical application across enterprise and engineering datasets.

This summary is AI-generated from the official solicitation.

Key Details

Agency
Department of Defense
Funding Amount
Release Date
July 1, 2026
Due Date
August 19, 2026 (Closed)

Official Description

By integrating the contextualization power of LLMs with the statistical power of ML, the program aims to leverage the benefits of both to provide domain-specific statistical contextualization of structured data.

This effort must:

 Survey and research the emerging ML methods suitable for large scale data containing both structured and unstructured data.  Develop an architecture to combine select ML methods with LLM models.  Determine a set of metrics that encompass accuracy, new insights, comp...

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Change History

Status ChangedAug 19, 2026 at 4:01 PM

Fusion of Abstract Learning and Context-Optimized Neural-methods (FALCON)

Status changed from Open to Closed after topic disappearance

Status ChangedJul 22, 2026 at 1:02 PM

Fusion of Abstract Learning and Context-Optimized Neural-methods (FALCON)

Status changed from Pre-Release to Open

Opportunity AddedJul 1, 2026 at 12:02 PM

Fusion of Abstract Learning and Context-Optimized Neural-methods (FALCON)

New opportunity: Fusion of Abstract Learning and Context-Optimized Neural-methods (FALCON)

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