5 papers
Encoded but Not Routed: Explaining the Table-Chart Gap in Scientific Claim Verification
Sunisth Kumar, Xanh Ho, Tim Schopf +3
Multimodal LLMs are increasingly used to assist scientific peer review, where a core requirement is verifying whether claims in a paper are supported by its evidence. Prior work ha…
Attribution, Citation, and Quotation: A Survey of Evidence-based Text Generation with Large Language Models
Tobias Schreieder, Tim Schopf, Michael Färber
The increasing adoption of large language models (LLMs) has raised serious concerns about their reliability and trustworthiness. As a result, a growing body of research focuses on…
Is this Idea Novel? An Automated Benchmark for Judgment of Research Ideas
Tim Schopf, Michael Färber
Judging the novelty of research ideas is crucial for advancing science, enabling the identification of unexplored directions, and ensuring contributions meaningfully extend existin…
DocIE@XLLM25: In-Context Learning for Information Extraction using Fully Synthetic Demonstrations
Nicholas PopoviÄ, Ashish Kangen, Tim Schopf +1
Large, high-quality annotated corpora remain scarce in document-level entity and relation extraction in zero-shot or few-shot settings. In this paper, we present a fully automatic,…
Efficient Few-shot Learning for Multi-label Classification of Scientific Documents with Many Classes
Tim Schopf, Alexander Blatzheim, Nektarios Machner +1
Scientific document classification is a critical task and often involves many classes. However, collecting human-labeled data for many classes is expensive and usually leads to lab…