1 citations · 2 across the 9 of their papers we have counts for
9 papers
Is It Novel and Why? Fine-Grained Patent Novelty Prediction Based on Passage Retrieval
Valentin Knappich, Anna Hätty, Simon Razniewski +1
Novelty assessment is a critical yet complex task in the examination process for patent acceptance, requiring examiners to determine whether an invention is disclosed in a prior ar…
A Solver-in-the-Loop Framework for Improving LLMs on Answer Set Programming for Logic Puzzle Solving
Timo Pierre Schrader, Lukas Lange, Tobias Kaminski +2
The rise of large language models (LLMs) has sparked interest in coding assistants. While general-purpose programming languages are well supported, generating code for domain-speci…
PEDANTIC: A Dataset for the Automatic Examination of Definiteness in Patent Claims
Valentin Knappich, Annemarie Friedrich, Anna Hätty +1
Patent claims define the scope of protection for an invention. If there are ambiguities in a claim, it is rejected by the patent office. In the US, this is referred to as indefinit…
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…
AnnoCTR: A Dataset for Detecting and Linking Entities, Tactics, and Techniques in Cyber Threat Reports
Lukas Lange, Marc Müller, Ghazaleh Haratinezhad Torbati +4
Monitoring the threat landscape to be aware of actual or potential attacks is of utmost importance to cybersecurity professionals. Information about cyber threats is typically dist…