Papers by Joseph Cornelius
UZH@CRAFT-ST: a Sequence-labeling Approach to Concept Recognition (D19-57)
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| Challenge: | CRAFT shared task 2019: concept recognition using named entity recognition and normalization . a biLSTM-based network and a transformer system were used to tackle both tasks in a single model . |
| Approach: | They propose two different neural approaches to concept recognition . they propose a BiLSTM-based network and a bioBERT-based system for NER and normalization . |
| Outcome: | The proposed systems model the task as a sequence labeling problem. |
BUST: Benchmark for the evaluation of detectors of LLM-Generated Text (2024.naacl-long)
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| Challenge: | Using the benchmark, we evaluated 5 detectors and found substantial performance variance across tasks. |
| Approach: | They propose to evaluate detectors of texts generated by instruction-tuned large language models (LLMs) using a benchmark dataset, they evaluated 5 detectors and found substantial performance variance across tasks. |
| Outcome: | The proposed benchmarks evaluated 5 detectors and found substantial performance variance across tasks. |