Pre Trained Language Models
PulseAugur coverage of Pre Trained Language Models — every cluster mentioning Pre Trained Language Models across labs, papers, and developer communities, ranked by signal.
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LLM-based framework generates weak labels for cybersecurity tweets
Researchers have developed a novel teacher-student framework utilizing large language models (LLMs) to generate weak labels for cybersecurity tweets. This approach addresses the bottleneck of manual annotation for cyber…
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Survey maps fake review detection from PLMs to LLMs
A new survey paper examines the evolving landscape of fake review detection, tracing methods from traditional machine learning to advanced techniques utilizing pre-trained language models (PLMs) and large language model…
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Attention expansion boosts keyphrase extraction from long documents
Researchers have developed an "attention expansion" mechanism to improve keyphrase extraction from long documents. This method augments pre-trained language model (PLM) representations with information from surrounding …
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New framework uses SHAP and LLMs to explain teaching quality scores
Researchers have developed a new framework to interpret how automated scoring models assign quality ratings to complex language performances, such as classroom transcripts. This framework combines model-agnostic Shapley…
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SemStruct framework improves schema matching using PLMs and GNNs
Researchers have developed SemStruct, a new framework for schema matching that combines the semantic understanding of pre-trained language models (PLMs) with the structural analysis capabilities of Graph Neural Networks…
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New Fuzzy Fingerprint method enhances PLMs for conversational emotion recognition
Researchers have developed a new method combining pre-trained language models (PLMs) with Fuzzy Fingerprints (FFPs) to improve emotion recognition in conversations. This approach addresses the issue of PLMs frequently m…