Projects

The advancement of NLP technologies focused on knowledge and people offers a unique opportunity to strengthen the business and societal structures by fostering trustworthy digital ecosystems. The results of this project have the potential to positively impact society by providing tools and resources that ensure the quality, integrity, and transparency of language models and digital content, enhancing the ability to access and generate trustworthy information. By addressing challenges such as disinformation, hate speech, and abusive behavior, while fostering the dissemination of valuable and reliable content, this project establishes an innovative framework to integrate quality metrics, FAIR principles, and privacy and security strategies into the development of NLP technologies, laying the groundwork for a responsible and beneficial digital transformation for society and market.

HIVEMIND transforms software engineering with a human-centric, AI-driven approach. By integrating an adaptive multi-agent framework, we enable seamless collaboration between developers and specialised LLM agents, streamlining software specification, code development, and maintenance. Validated across key industrial and societal sectors, HIVEMIND enhances efficiency, security, and adaptability, setting a new standard for responsible software development.

ML3T-SCI is framed as a holistic program for training experts in Large Language Models and Language Technologies, offering two specializations: one oriented towards scientific research and the other focused on corporate innovation.

While it is widely accepted that Deep Learning (DL) techniques are superior to rule-based and knowledge-based ones, this 4-year project will seek to establish formally through proper evaluations spanning different datasets whether DL always performs better and if not, in what circumstances. In addition, the project will seek to find answers as to how to boost the performance of the successful DL-based applications even further. The study will examine different NLP tasks/applications and to the best of our knowledge will be the first study to establish the extent to which DL guarantees improvement over rule-based methods and whether combining DL methods with various techniques, models and resources, would offer further improvements. Given the emergence and pervasive employment of Large Language Models, the project will experiment with Large Language Models as additional methodology and will compare them with Deep Learning and rule-based methods. This GenT 4-year project funded by the Valencian...

INTEGER – Intelligent Text Generation [RTI2018-094649-B-I00] The Integer project proposes that it is possible to consider the communicative objective as one more input in the automatic text generation process, without prefixing it in the system design, giving rise to more flexible solutions. Furthermore, through the use of recent learning techniques, the versatility of the system can be extended by integrating heterogeneous information sources (text, image, sound, etc.).  INTEGER – Intelligent Text Generation [RTI2018-094649-B-I00] is a project funded by the State Program for Research, Development and Innovation Oriented to the Challenges of Society, within the framework of the State Plan for Scientific and Technical Research and Innovation 2017-2020. https://integer.gplsi.es/

Artificial Intelligence (AI) is an essential enabling technology whose potential should be developed to serve human progress, while at the same time avoiding and combating the potential risks associated with its malicious use. AI has raised new challenges concerning human-machine interaction and communication. Humans communicate and understand reality through natural language and as huge amounts of digital data are expressed in natural language, this has triggered the development of Human Language Technologies (HLT) and Natural Language Processing (NLP) methods (1), such as searchers, chatbots, translators or conversational agents, among others. These technologies have become essential everyday tools for a growing number of people around the globe.

Natural language is the main means of interaction in human societies. When these societies move to the digital world, the interaction between elements generates digital content, also mostly made up of natural language. Digital media and social networks have enhanced this interaction, creating an ecosystem of spaces where content is created and consumed in increasing quantity and speed. However, this ubiquitous environment of interaction has two opposing perspectives.