7 citations · 10 across the 4 of their papers we have counts for
4 papers
Calibrating Large Language Models Using Their Generations Only
Dennis Ulmer, Martin Gubri, Hwaran Lee +2
As large language models (LLMs) are increasingly deployed in user-facing applications, building trust and maintaining safety by accurately quantifying a model's confidence in its p…
Non-Exchangeable Conformal Language Generation with Nearest Neighbors
Dennis Ulmer, Chrysoula Zerva, André F. T. Martins
Quantifying uncertainty in automatically generated text is important for letting humans check potential hallucinations and making systems more reliable. Conformal prediction is an…
Bootstrapping LLM-based Task-Oriented Dialogue Agents via Self-Talk
Dennis Ulmer, Elman Mansimov, Kaixiang Lin +3
Large language models (LLMs) are powerful dialogue agents, but specializing them towards fulfilling a specific function can be challenging. Instructing tuning, i.e. tuning models o…
Uncertainty in Natural Language Generation: From Theory to Applications
Joris Baan, Nico Daheim, Evgenia Ilia +7
Recent advances of powerful Language Models have allowed Natural Language Generation (NLG) to emerge as an important technology that can not only perform traditional tasks like sum…