Search Results for author:
Found 20 papers, 6 papers with code
Are We Summarizing the Right Way? A Survey of Dialogue Summarization Data Sets
Dialogue summarization is a long-standing task in the field of NLP, and several data sets with dialogues and associated human-written summaries of different styles exist.
Replicability under Near-Perfect Conditions – A Case-Study from Automatic Summarization
Replication of research results has become more and more important in Natural Language Processing.
Autism Detection in Speech - A Survey
We analyse studies from the biomedical, as well as the psychological domain, but also from the NLP domain in order to find linguistic, prosodic and acoustic cues that could indicate autism.
Investigating Bias in Multilingual Language Models: Cross-Lingual Transfer of Debiasing Techniques
This paper investigates the transferability of debiasing techniques across different languages within multilingual models.
Missing Information, Unresponsive Authors, Experimental Flaws: The Impossibility of Assessing the Reproducibility of Previous Human Evaluations in NLP
We report our efforts in identifying a set of previous human evaluations in NLP that would be suitable for a coordinated study examining what makes human evaluations in NLP more/less reproducible.
BLOOM: A 176B-Parameter Open-Access Multilingual Language Model
Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions.
Reviewing Natural Language Processing Research
This tutorial will cover the theory and practice of reviewing research in natural language processing.
A Data Set for the Analysis of Text Quality Dimensions in Summarization Evaluation
Automatic evaluation of summarization focuses on developing a metric to represent the quality of the resulting text.
Language Agnostic Automatic Summarization Evaluation
In our work, we present experiments of adapting available evaluation methods such as ROUGE and PYRAMID to non-English data.
Community Perspective on Replicability in Natural Language Processing
With recent efforts in drawing attention to the task of replicating and/or reproducing results, for example in the context of COLING 2018 and various LREC workshops, the question arises how the NLP community views the topic of replicability in general.
OCR Quality and NLP Preprocessing
We present initial experiments to evaluate the performance of tasks such as Part of Speech Tagging on data corrupted by Optical Character Recognition (OCR).
Optical Character Recognition
Optical Character Recognition (OCR)
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A Quantitative Study of Data in the NLP community
We present results on a quantitative analysis of publications in the NLP domain on collecting, publishing and availability of research data.
Bridging the gap between extractive and abstractive summaries: Creation and evaluation of coherent extracts from heterogeneous sources
Coherent extracts are a novel type of summary combining the advantages of manually created abstractive summaries, which are fluent but difficult to evaluate, and low-quality automatically created extractive summaries, which lack coherence and structure.
