185 citations · 483 across the 49 of their papers we have counts for
65 papers · 1 filter
Do LLMs Make More Mistakes If They Do Not Believe the Input Data?
Peter Kochelka, Aleš Manuel Papáček, Vojtěch Dvořák +1
Large language models (LLMs) are prone to hallucinating or misinterpreting facts, which impairs their usability in retrieval-augmented generation or data-to-text systems. We analys…
VetScore: Risk-Weighted Fact Verification for Veterinary Long-Form QA with Citations
Ivan Kartáč, Jan Tovarys, Mateusz Lango +1
Citation excerpts can be used to increase the reliability of generated outputs and their faithfulness to cited sources, which is especially important in high-stakes domains such as…
Can LLM Coding Agents Reason About Time Series?
Filip Rechtorík, Ondřej Dušek, Zdeněk Kasner
Large language models (LLMs) are increasingly being used for automated decision-making systems in finance, healthcare, or environmental monitoring. Time series data are ubiquitous…
Modular Monolingual Adaptation using Pretrained Language Models
Nalin Kumar, Ondřej Dušek
Building monolingual language models (LMs) for low-resource languages typically relies on adapting pretrained language models (PLMs) by finetuning the whole model on the target lan…
AnimatedLLM: Explaining LLMs with Interactive Visualizations
Zdeněk Kasner, Ondřej Dušek
Large language models (LLMs) are becoming central to natural language processing education, yet materials showing their mechanics are sparse. We present AnimatedLLM, an interactive…
Strategies for Span Labeling with Large Language Models
Danil Semin, Ondřej Dušek, Zdeněk Kasner
Large language models (LLMs) are increasingly used for text analysis tasks, such as named entity recognition or error detection. Unlike encoder-based models, however, generative ar…