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NoiseBench: Benchmarking the Impact of Real Label Noise on Named Entity Recognition
Available training data for named entity recognition (NER) often contains a significant percentage of incorrect labels for entity types and entity boundaries.
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Instruction-tuned Large Language Models (LLMs) have recently showcased remarkable advancements in their ability to generate fitting responses to natural language instructions.
OpinionGPT: Modelling Explicit Biases in Instruction-Tuned LLMs
The demo will answer this question using a model fine-tuned on text representing each of the selected biases, allowing side-by-side comparison.
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