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Jul 23, 2023 · Its goal is to identify instances of semantic relations (e.g. a drug affecting an illness, a protein affecting another protein, a head of state ...
Our proposed path-based neural model combines useful properties of convolu- tional and recurrent networks, while resolving several shortcomings of the current ...
Jul 23, 2023 · We are first to incorporate a language model into both existing approaches to this task, namely path-based and distribution-based methods. Our ...
Jul 23, 2023 · Recognizing various semantic relations between terms is crucial for many NLP tasks. While path-based and distributional information sources are ...
Oct 22, 2024 · To address these limitations, we propose fine-tuning using semantic entropy, an uncertainty measure derived from introspection into the model ...
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The GPT and similar models have been shown to capture semantic and syntactic features, and also a notable amount of “common-sense” knowledge, which we ...
Jun 24, 2024 · In this work, fine-tuning addresses the performance problem of the zero-shot LLM prompting approach. (e.g., RAG4RE [8]) in identifying implicit ...
The paper introduces the SUGARCREPE++ dataset to analyze the sensitivity of vision-and-language models (VLMs) and unimodal language models (ULMs) to semantic ...
Prefix and prompt tuning are methods of adapting large pretrained language models to specific tasks or datasets with minimal updates to the model parameters.
Dec 23, 2020 · Sentiment analysis refers to classification of a sample of text based on the sentiment or opinion it expresses. Whenever we write text, ...