Monday, March 4th 2024, Faculty of Mathematics and Computer Science of the University of Bucharest will host the conference titled “Factuality Challenges in the Era of Large Language Models”, organized as part of the Solomon Marcus research seminaries and the Natural Language Processing at the UB Faculty of Mathematics and Computer Science.
The event will take place at the Țițeica Amphitheatre at the Faculty headquarters (14 Academiei Str, Bucharest), between 5 PM – 7 PM, and the main speakers at the conference will be Aigerim Alibek and professor and international Natural Language Processing expert Preslav Nakov, Director of the Natural Language Processing Department at the Mohamed bin Zayed University of Artificial Intelligence in Abu Dhabi, United Arab Emirates (MBZUAI).
The conference will discuss the risks, the challenges, and the opportunities that Large Language Models (LLMs) bring regarding factuality. Speakers will then delve into recent work on using LLMs to assist fact-checking (e.g., claim normalization, stance detection, question-guided fact-checking, program-guided reasoning, and synthetic data generation for fake news and propaganda identification), on checking and correcting the output of LLMs, on detecting machine-generated text (blackbox and whitebox), and on fighting the ongoing misinformation pollution with LLMs. Finally, they will discuss work on safeguarding LLMs, and the safety mechanisms incorporated in Jais-chat, the world’s best open Arabic-centric foundation and instruction-tuned LLM.
More information on the conference „Factuality Challenges in the Era of Large Language Models” are available here.
The specialists of the Human Language Technologies Research Center within the Faculty of Mathematics and Computer Science of the University of Bucharest investigate a large array of sub-fields such as natural language processing, AI, similarity of natural languages, relation between languages starting from the origin of words, robotic equipment for the analysis of human behavior, detecting aggressive language online, fighting discrimination, managing emotions, such as mechanisms which explain positive of negative effects of communication or the degree of evolution of depression as a result of the specialized analysis of social media posts.