Enhanced Learning Strategies for General Purpose AI: Advancing GenAI4EU (RIA) (AI/Data/Robotics Partnership)
HORIZON Research and Innovation Actions
Basic Information
- Identifier
- HORIZON-CL4-2025-04-DIGITAL-EMERGING-07
- Programme
- DIGITAL - HADEA
- Programme Period
- 2021 - 2027
- Status
- Closed (31094503)
- Opening Date
- June 10, 2025
- Deadline
- October 2, 2025
- Deadline Model
- single-stage
- Budget
- €30,000,000
- Min Grant Amount
- €6,000,000
- Max Grant Amount
- €8,000,000
- Expected Number of Grants
- 4
- Keywords
- HORIZON-CL4-2025-04-DIGITAL-EMERGING-07HORIZON-CL4-2025-04Artificial intelligence, intelligent systems, multi agent systems
Description
Project results are expected to contribute to some of the following expected outcomes:
- Development of General Purpose AI (GPAI) models and architectures demonstrating enhanced capabilities, such as formal reasoning, mathematical problem-solving, confidence level estimation, long-term planning, and seamless adaptation to dynamic and non-stationary environments.
- Innovative learning approaches combining self-supervised learning with hybrid learning, active learning, reinforcement learning, transfer learning, relational learning or continual learning and evolutionary learning.
- Theoretical insights to advance the understanding of synergies between self-supervised and complementary learning paradigms in GPAI model development.
Current large-scale AI models have demonstrated remarkable capabilities that have transformed numerous fields. They excel at tasks like natural language processing, image generation, and playing complex games. However, despite these successes, current models often struggle in several key areas. They lack the adaptability to seamlessly adjust to changing conditions in real-world environments. Additionally, their reasoning abilities remain limited, when facing complex tasks that require logical deduction, mathematical problem-solving, or multi-step planning. Moreover, current GPAI models frequently fail to recognise their own limitations, leading them to generate erroneous outputs when presented with queries outside their domains of knowledge. These limitations underscore the need for advancements in General Purpose AI (GPAI) that go beyond pattern recognition and towards robust, adaptive systems capable of a wider range of intelligent behaviours, for example, taking inspirations from biological and collective systems.
To push the boundaries of current AI technology, this topic seeks the development of groundbreaking GPAI models that combine self-supervised learning with complementary learning strategies. These strategies include hybrid learning, which integrates symbolic reasoning and knowledge representation; active learning, which allows models to actively seek information to improve their performance; reinforcement learning, which enables models to learn through interaction with their environment; relational learning, which focuses on learning from relational data structures; continual learning, which allows models to continuously adapt and acquire new knowledge without forgetting previous tasks; and evolutionary learning, which draws inspiration from biological evolution to optimize model architectures and parameters; and physics-based learning, which considers physical properties in the models’ architectures. By leveraging these complementary approaches, the aim is to create GPAI models that exhibit enhanced capabilities, overcome existing limitations, and pave the way for a new generation of intelligent systems capable of tackling complex, real-world challenges.
This topic prioritizes proposals that explore innovative approaches to developing GPAI models, focusing on at least one of the following key research areas:
- Hybrid Learning Architectures for Advanced Reasoning: Development of architectures integrating self-supervised learning with symbolic reasoning, knowledge representation, and neuro-symbolic methods to foster robust reasoning, complex planning, and problem-solving abilities within GPAI.
- Continual and Evolutionary Learning for Dynamic Environments: Research on paradigms enabling GPAI models to seamlessly adapt, learn from changing conditions, and retain knowledge essential for operation in dynamic, real-world environments.
- Reinforcement Learning Integration: Research on the fusion of self-supervised learning and reinforcement learning to overcome challenges like non-stationary data, algorithm sensitivity, and computational cost.
- Explainable AI and Trustworthy Decision-Making: Integration of robust XAI methodologies, exploring causal inference and counterfactual reasoning techniques to enhance transparency, accountability, and responsible use of GPAI models in alignment with European values and principles.
- Other Novel Paradigms: Research on the combination of self-supervised learning with other learning paradigms, such as active learning, relational learning, and embodied learning, to equip GPAI models with new advanced capabilities.
Proposed projects should aim for a balanced approach between theoretical advancements and practical applications, with a strong emphasis on the development of GPAI models that align with European values and principles, including the AI Act.
The potential impact of this research extends beyond scientific advancements, as it has the potential to transform key European industries and sectors, including advanced robotics, personalized healthcare, mobility, manufacturing, sustainable energy solutions, and the scientific sector, and to contribute to the EU climate neutrality objective through energy efficiency. Successful projects will contribute to the development of GPAI models that enhance productivity, improve decision-making, and foster innovation across a wide range of domains.
This topic strongly encourages the formation of interdisciplinary teams combining the necessary technical expertise. Such a collaborative approach will ensure that assessments accurately capture real-world capabilities and risks, and that the developed tools are responsive to the concerns of all relevant stakeholders.
Proposals must adhere to Horizon Europe's requirements regarding Open Science. Open access to research outputs should be provided unless there is a legitimate reason or constraint.
All proposals are expected to incorporate mechanisms for assessing and demonstrating progress, including qualitative and quantitative KPIs, benchmarking, and progress monitoring. This should include participation in international evaluation contests and the presentation of illustrative application use-cases that demonstrate concrete potential added value. Communicable results should be shared with the European R&D community through the AI-on-demand platform, and if necessary, other relevant digital resource platforms to bolster the European AI, Data, and Robotics ecosystem by disseminating results and best practices.
This topic implements the co-programmed European Partnership on AI, data and robotics (ADRA), and all proposals are expected to allocate tasks for cohesion activities with ADRA and the CSA HORIZON-CL4-2025-03-HUMAN-18: GenAI4EU central Hub.
Proposals should also build on or seek collaboration with existing projects and develop synergies with other relevant European, national or regional initiatives, funding programmes and platforms. Regarding European programmes, proposals are expected to develop synergies and complementarities with relevant projects funded under Horizon Europe but also under the Digital Europe Programme (DEP).
Destination & Scope
Destination 4 ensures Europe’s strategic autonomy while preserving an open economy in those technologies that will be key for a deep digital transformation of industry, public services and society, while fully playing its enabling role in the twin transition. As set out in the European Chips Act, the top-priorities are to i) strengthen processes undertaken at critical stages in the semiconductor and quantum chips value chain, including chip design and manufacturing technologies, and ii) address the use of new materials and green technologies, energy efficiency and the integration of circularity and life-cycle assessment.
Destination 4 will address high value-added hardware needs for core, cloud and edge, fast-sensing, low-latency and high-bandwidth data transmission, and help secure the supply of critical components for key markets, such as automotive, health, automation and mobility systems. For this purpose, significant human capacity will be required in chip manufacturing to ensure: (i) the strengthening of processes undertaken at critical stages in the value chain; and (ii) that workers can take up quality jobs created as part of these priorities, including through the activities undertaken by the joint undertaking initiative.
In addition, future needs in microelectronics (such as performance, size, cost, energy efficiency, environmental impact, new materials, concepts, architectures, integration) may also be addressed to make sure Europe’s microelectronics industry remains competitive. Opportunities may come from non-volatile memories, spintronics, in-memory computing, neuromorphic and other emerging technologies. Photonics research will lead to fast and versatile sensing and imaging, and energy-efficient building blocks for networks and data centres. The cluster will also push for chip-level integration of photonics and optoelectronics.
The cloud/edge/internet of things will be transformed into an agile and situation-aware infrastructure that brings data to where and when it is needed. Within these smart digital infrastructures, end-to-end artificial intelligence, from the core to the edge and across all technology layers, will be key for on-demand supply of optimal data-, communication-, and computing resource orchestration, with optimal use of energy while preserving privacy and ensuring resilience. European sovereignty in the cloud-edge server market will be strengthened through the power of open-source software, complementing the RISC-V based European Processor Initiative that aims to increase Europe’s independence in high performance computing hardware.
Cluster 4 will transform the user experience. It will push the frontiers of virtual and extended realities (VR/XR) and of open, human-centric virtual worlds for industry, entertainment and arts, public services and people alike, e.g. by leveraging social innovation. It envisages a vibrant R&I ecosystem that strategically joins-up research and development on sophisticated VR/XR optics and displays, multimodal human-computer interaction, authoring tools, real-time spatial computing, rendering, integration and application research. Improved sensing, fast processing and low-latency will be challenging for the underlying cloud/edge/Internet of things. Along similar lines, the way in which the virtual world meets the physical world will continue to evolve, thanks to all kinds of robots and other smart devices that involve self- and context awareness, spatial intelligence, exploiting the best in bias-free AI, engineering and design for game-changing physical characteristics, functional or cognitive capabilities, acute perception, autonomy and safe interaction.
Artificial intelligence underpins many of these changes and Cluster 4 will strengthen and consolidate R&I in this area. For example, today’s generative models are a preview of how virtual worlds and multimodal user-experiences could be produced on-demand. Research on core learning and analysis techniques (incremental, frugal and collaborative), as well as next generation smart robotic systems, will keep Europe at the cutting edge of AI. Artificial Intelligence is also key to keep the competitiveness and strategic autonomy of the EU scientific sector. The EU's comprehensive approach to achieving leadership in AI is reflected in its Apply AI Strategy, which aims at establishing Europe as a global leader in the development and adoption of AI. By fostering a vibrant AI ecosystem, the EU seeks to make Europe a hub for AI innovation and growth, where world-class AI models are developed and integrated into strategic sectors. This initiative is designed to drive innovation, economic growth, and competitiveness, while ensuring that the benefits of AI are shared by all. The topics related to Generative AI included in this destination will support the implementation of the GenAI4EU initiative included in the AI Innovation Package of 24 January 2024. They constitute, moreover, an integral part of the broader Apply AI strategy. By aligning these efforts with the GenAI4EU initiative and the Apply AI strategy, the EU aims to create a cohesive and coordinated approach to AI development and adoption, one that promotes European excellence and leadership in this critical field.
Europe’s long-term competitiveness in the digital area requires continuous scouting and early, low-TRL cross-disciplinary work on new and emerging technologies, dissociated from the main roadmaps. This would encourage collaboration in research and cross-fertilisation between disciplines and sectors on new approaches in: (i) microelectronics; (ii) power electronics; (iii) photonics and photon/phonon/spin/electron integration; (iv) unconventional, hybrid, neuromorphic, nature-inspired or bio-intelligent paradigms; and (v) novel systems and infrastructure architectures.
Europe’s strength in quantum technologies (including in quantum communications and optical satellite communications, etc.) is a strategic asset for its future security and independence. Cluster 4 supports early and mature quantum technologies and stimulates their industrial uptake, e.g. through experimentation and testing environments for integrating them into standard industrial design and manufacturing. Equally transformative, two-dimensional materials (2DM) could positively affect many industries, including ICT. While further exploring the vast range of 2DMs, Cluster 4 will also work towards completing a fully European supply chain and scaling up the development and piloting of 2DM technologies and devices for more industrial fields.
Eligibility & Conditions
General conditions
1. Admissibility Conditions: Proposal page limit and layout
2. Eligible Countries
are described in Annex B of the Work Programme General Annexes.
A number of non-EU/non-Associated Countries that are not automatically eligible for funding have made specific provisions for making funding available for their participants in Horizon Europe projects. See the information in the Horizon Europe Programme Guide.
3. Other Eligible Conditions
In order to achieve the expected outcomes, and safeguard the Union’s strategic assets, interests, autonomy, and security, it is important to avoid a situation of technological dependency on a non-EU source, in a global context that requires the EU to take action to build on its strengths, and to carefully assess and address any strategic weaknesses, vulnerabilities and high-risk dependencies which put at risk the attainment of its ambitions. For this reason, participation is limited to legal entities established in Member States, Iceland and Norway and the following additional associated countries: Canada, Israel, the Republic of Korea, New Zealand, Switzerland, and the United Kingdom.
For the duly justified and exceptional reasons listed in the paragraph above, in order to guarantee the protection of the strategic interests of the Union and its Member States, entities established in an eligible country listed above, but which are directly or indirectly controlled by a non-eligible country or by a non-eligible country entity, may not participate in the action unless it can be demonstrated, by means of guarantees positively assessed by their eligible country of establishment, that their participation to the action would not negatively impact the Union’s strategic assets, interests, autonomy, or security. Entities assessed as high-risk suppliers of mobile network communication equipment within the meaning of ‘restrictions for the protection of European communication networks’ (or entities fully or partially owned or controlled by a high-risk supplier) cannot submit guarantees.[[The guarantees shall in particular substantiate that, for the purpose of the action, measures are in place to ensure that: a) control over the applicant legal entity is not exercised in a manner that retrains or restricts its ability to carry out the action and to deliver results, that imposes restrictions concerning its infrastructure, facilities, assets, resources, intellectual property or know-how needed for the purpose of the action, or that undermines its capabilities and standards necessary to carry out the action; b) access by a non-eligible country or by a non-eligible country entity to sensitive information relating to the action is prevented; and the employees or other persons involved in the action have a national security clearance issued by an eligible country, where appropriate; c) ownership of the intellectual property arising from, and the results of, the action remain within the recipient during and after completion of the action, are not subject to control or restrictions by non-eligible countries or non-eligible country entity, and are not exported outside the eligible countries, nor is access to them from outside the eligible countries granted, without the approval of the eligible country in which the legal entity is established.
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Described in Annex B of the Work Programme General Annexes.
4. Financial and operational capacity and exclusion
are described in Annex C of the Work Programme General Annexes.
5a. Evaluation and award: Award criteria, scoring and thresholds
are described in Annex D of the Work Programme General Annexes.
5b. Evaluation and award: Submission and evaluation processes
are described in Annex F of the Work Programme General Annexes and the Online Manual.
5c. Evaluation and award: Indicative timeline for evaluation and grant agreement
is described in Annex F of the Work Programme General Annexes.
6. Legal and financial set-up of the grants
are described in Annex G of the Work Programme General Annexes.
are described in the specific topic of the Work Programme.
Application and evaluation forms and model grant agreement (MGA):
Application form templates — the application form specific to this call is available in the Submission System
Standard application form (HE RIA, IA)
Evaluation form templates — will be used with the necessary adaptations
Standard evaluation form (HE RIA, IA)
Guidance
Model Grant Agreements (MGA)
Additional documents:
HE Main Work Programme 2025 – 1. General Introduction
HE Main Work Programme 2025 – 7. Digital, Industry and Space
HE Main Work Programme 2025 – 14. General Annexes
HE Framework Programme 2021/695
HE Specific Programme Decision 2021/764
EU Financial Regulation 2024/2509
Decision authorising the use of lump sum contributions under the Horizon Europe Programme
Rules for Legal Entity Validation, LEAR Appointment and Financial Capacity Assessment
EU Grants AGA — Annotated Model Grant Agreement
Funding & Tenders Portal Online Manual
Support & Resources
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Latest Updates
PROPOSAL NUMBERS
Call HORIZON-CL4-2025-04 has closed on 02 October 2025
A total of 503 proposals were submitted in response to this call.
The number of proposals for each topic is shown below:
HORIZON-CL4-2025-04-DATA-02: Empowering AI/generative AI along the Cognitive Computing continuum (RIA) (AI/Data/Robotics Partnership)
74 proposals submitted (indicative topic budget 30 EUR million)
HORIZON-CL4-2025-04-DATA-03: Software Engineering for AI and generative AI (RIA) (AI/Data/Robotics Partnership)
56 proposals submitted (indicative topic budget 15 EUR million)
HORIZON-CL4-2025-04-DIGITAL-EMERGING-01: Advanced sensor technologies and multimodal sensor integration for multiple application domains (IA) (Photonics Partnership)
89 proposals submitted (indicative topic budget 25 EUR million)
HORIZON-CL4-2025-04-DIGITAL-EMERGING-04: Assessment methodologies for General Purpose AI capabilities and risks (RIA) (AI/Data/Robotics Partnership)
28 proposals submitted (indicative topic budget 7 EUR million)
HORIZON-CL4-2025-04-DIGITAL-EMERGING-05: Soft Robotics for Advanced physical capabilities (IA) (AI/Data/Robotics Partnership)
19 proposals submitted (indicative topic budget 20 EUR million)
HORIZON-CL4-2025-04-DIGITAL-EMERGING-07: Enhanced Learning Strategies for General Purpose AI: Advancing GenAI4EU (RIA) (AI/Data/Robotics Partnership)
22 proposals submitted (indicative topic budget 30 EUR million)
HORIZON-CL4-2025-04-HUMAN-08: GenAI for Africa (RIA)
215 proposals submitted (indicative topic budget 5 EUR million)
The evaluation results are expected to be communicated in January 2026.
Please note that due to a technical issue, during the first days of publication of this call, the topic page did not display the description of the corresponding destination. This problem is now solved.
In addition to the information published in the topic page, you can always find a full description of the Destination 4 ("Achieving open strategic autonomy in digital and emerging enabling technologies") that is relevant for the call in the Work Programme 2025 part for "Digital, Industry and Space". Please select from the work programme the destination relevant to your topic and take into account the description and expected impacts of that destination for the preparation of your proposal.