Explainable Multimodal Agents With Symbolic Representations & Can AI Be Less Biased?

More than 170 audiences visited the online lecture of our Junior Member Ruotong Liao, PhD student in the group of our PI Volker Tresp, on Monday, 17. March 2025, as an invited speaker at the United Nations "AI for Good".

With her talk "Perceive, Remember, and Predict: Explainable Multimodal Agents with Symbolic Representations," Ruotong Liao took part in the online event "Explainable Multimodal Agents with Symbolic Representations & Can AI be less biased?"

At the event, which was hosted by the leading platform for artificial intelligence for sustainable development, Ruotong Liao explained her research results, focussed on how the integration of temporal reasoning and symbolic knowledge about evolving events enables LLMs to make structured, interpretable, and context-sensitive predictions. Ruotong Liao presented work aimed at developing explainable multimodal agents capable of perceiving, storing, predicting, and justifying their conclusions over time.

See the whole presentation in the stream.