27 citations · 81 across the 33 of their papers we have counts for
5 papers · 2 filters
Enabling LLM Knowledge Analysis via Extensive Materialization
Yujia Hu, Tuan-Phong Nguyen, Shrestha Ghosh +1
Large language models (LLMs) have majorly advanced NLP and AI, and next to their ability to perform a wide range of procedural tasks, a major success factor is their internalized f…
QUITE: Quantifying Uncertainty in Natural Language Text in Bayesian Reasoning Scenarios
Timo Pierre Schrader, Lukas Lange, Simon Razniewski +1
Reasoning is key to many decision making processes. It requires consolidating a set of rule-like premises that are often associated with degrees of uncertainty and observations to…
Pap2Pat: Benchmarking Outline-Guided Long-Text Patent Generation with Patent-Paper Pairs
Valentin Knappich, Simon Razniewski, Anna Hätty +1
Dealing with long and highly complex technical text is a challenge for Large Language Models (LLMs), which still have to unfold their potential in supporting expensive and timeinte…
Recall Them All: Retrieval-Augmented Language Models for Long Object List Extraction from Long Documents
Sneha Singhania, Simon Razniewski, Gerhard Weikum
Methods for relation extraction from text mostly focus on high precision, at the cost of limited recall. High recall is crucial, though, to populate long lists of object entities t…
Cultural Commonsense Knowledge for Intercultural Dialogues
Tuan-Phong Nguyen, Simon Razniewski, Gerhard Weikum
Despite recent progress, large language models (LLMs) still face the challenge of appropriately reacting to the intricacies of social and cultural conventions. This paper presents…