Hallucinations in LLMs Using Semantic Entropy | Jannik Kossen, University of Oxford | BLISS e.V.

We are excited to feature Jannik Kossen, Research Scientist at Meta AI and PhD Student at University of Oxford, who will discuss "Detecting Hallucinations in Large Language Models Using Semantic Entropy", lasting approximately 45 minutes.

🎥 Watch to Discover:
Large language models can 'hallucinate' factually incorrect outputs, presenting significant risks for their adoption to high-stakes applications. Jannik will present joint work recently published in Nature (https://www.nature.com/articles/s4158...) on detecting hallucinations in large language models using semantic entropy, which mitigates hallucinations by quantifying the model's own uncertainty over the meaning of generations. He will also discuss a recent pre-print (https://arxiv.org/abs/2406.15927) that proposes a method to drastically reduce the cost of uncertainty quantification in LLMs by predicting semantic entropy from latent space, and he may ramble about uncertainties in LLMs more generally.

Jannik is an AI research scientist at Meta FAIR, building LLMs for code generation. At some point, the University of Oxford, where he worked on uncertainty and data-efficiency in vision and language models, will probably grant him a PhD. He previously studied Physics in Bremen and Heidelberg, has interned at Google and DeepMind, but now lives in Berlin.

Recorded on July. 15, 2025 at TU Berlin, Berlin.

About BLISS e.V.:
We are BLISS e.V., the AI organization in Berlin that connects like-minded individuals who share great interest and passion for the field of machine learning. This summer 2025, we will host an exciting speaker series on site in Berlin, featuring excellent researchers from Merantix Momentum, Meta AI, Inria, Microsoft AI4Science, Google DeepMind, and University of Oxford.

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