10 citations · 26 across the 17 of their papers we have counts for
18 papers
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…
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…
FreshTab: Sourcing Fresh Data for Table-to-Text Generation Evaluation
Kristýna Onderková, Ondřej Plátek, Zdeněk Kasner +1
Table-to-text generation (insight generation from tables) is a challenging task that requires precision in analyzing the data. In addition, the evaluation of existing benchmarks is…
LLMs as Span Annotators: A Comparative Study of LLMs and Humans
Zdeněk Kasner, Vilém Zouhar, Patrícia Schmidtová +7
Span annotation - annotating specific text features at the span level - can be used to evaluate texts where single-score metrics fail to provide actionable feedback. Until recently…
Teaching LLMs at Charles University: Assignments and Activities
Jindřich Helcl, Zdeněk Kasner, Ondřej Dušek +4
This paper presents teaching materials, particularly assignments and ideas for classroom activities, from a new course on large language models (LLMs) taught at Charles University.…
factgenie: A Framework for Span-based Evaluation of Generated Texts
Zdeněk Kasner, Ondřej Plátek, Patrícia Schmidtová +2
We present factgenie: a framework for annotating and visualizing word spans in textual model outputs. Annotations can capture various span-based phenomena such as semantic inaccura…
A Survey of Text Style Transfer: Applications and Ethical Implications
Sourabrata Mukherjee, Mateusz Lango, Zdenek Kasner +1
Text style transfer (TST) is an important task in controllable text generation, which aims to control selected attributes of language use, such as politeness, formality, or sentime…
WebLINX: Real-World Website Navigation with Multi-Turn Dialogue
Xing Han Lù, Zdeněk Kasner, Siva Reddy
We propose the problem of conversational web navigation, where a digital agent controls a web browser and follows user instructions to solve real-world tasks in a multi-turn dialog…
Beyond Traditional Benchmarks: Analyzing Behaviors of Open LLMs on Data-to-Text Generation
Zdeněk Kasner, Ondřej Dušek
We analyze the behaviors of open large language models (LLMs) on the task of data-to-text (D2T) generation, i.e., generating coherent and relevant text from structured data. To avo…
Balancing the Style-Content Trade-Off in Sentiment Transfer Using Polarity-Aware Denoising
Sourabrata Mukherjee, Zdeněk Kasner, Ondřej Dušek
Text sentiment transfer aims to flip the sentiment polarity of a sentence (positive to negative or vice versa) while preserving its sentiment-independent content. Although current…
TabGenie: A Toolkit for Table-to-Text Generation
Zdeněk Kasner, Ekaterina Garanina, Ondřej Plátek +1
Heterogenity of data-to-text generation datasets limits the research on data-to-text generation systems. We present TabGenie - a toolkit which enables researchers to explore, prepr…
BLOOM: A 176B-Parameter Open-Access Multilingual Language Model
BigScience Workshop, :, Teven Le Scao +391
Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to wi…
Mind the Labels: Describing Relations in Knowledge Graphs With Pretrained Models
Zdeněk Kasner, Ioannis Konstas, Ondřej Dušek
Pretrained language models (PLMs) for data-to-text (D2T) generation can use human-readable data labels such as column headings, keys, or relation names to generalize to out-of-doma…
Neural Pipeline for Zero-Shot Data-to-Text Generation
Zdeněk Kasner, Ondřej Dušek
In data-to-text (D2T) generation, training on in-domain data leads to overfitting to the data representation and repeating training data noise. We examine how to avoid finetuning p…
Evaluating Semantic Accuracy of Data-to-Text Generation with Natural Language Inference
Ondřej Dušek, Zdeněk Kasner
A major challenge in evaluating data-to-text (D2T) generation is measuring the semantic accuracy of the generated text, i.e. checking if the output text contains all and only facts…
Data-to-Text Generation with Iterative Text Editing
Zdeněk Kasner, Ondřej Dušek
We present a novel approach to data-to-text generation based on iterative text editing. Our approach maximizes the completeness and semantic accuracy of the output text while lever…
Improving Fluency of Non-Autoregressive Machine Translation
Zdeněk Kasner, Jindřich Libovický, Jindřich Helcl
Non-autoregressive (nAR) models for machine translation (MT) manifest superior decoding speed when compared to autoregressive (AR) models, at the expense of impaired fluency of the…