Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Sheth, Divyanshu"'
We present a generalizable classification approach that leverages Large Language Models (LLMs) to facilitate the detection of implicitly encoded social meaning in conversations. We design a multi-faceted prompt to extract a textual explanation of the
Externí odkaz:
http://arxiv.org/abs/2406.19545
To facilitate evaluation of code generation systems across diverse scenarios, we present CodeBenchGen, a framework to create scalable execution-based benchmarks that only requires light guidance from humans. Specifically, we leverage a large language
Externí odkaz:
http://arxiv.org/abs/2404.00566
Abusive language is a concerning problem in online social media. Past research on detecting abusive language covers different platforms, languages, demographies, etc. However, models trained using these datasets do not perform well in cross-domain ev
Externí odkaz:
http://arxiv.org/abs/2211.17046
We propose a unified framework to generate both homophonic and homographic puns to resolve the split-up in existing works. Specifically, we incorporate three linguistic attributes of puns to the language models: ambiguity, distinctiveness, and surpri
Externí odkaz:
http://arxiv.org/abs/2210.13055
Acronyms and long-forms are commonly found in research documents, more so in documents from scientific and legal domains. Many acronyms used in such documents are domain-specific and are very rarely found in normal text corpora. Owing to this, transf
Externí odkaz:
http://arxiv.org/abs/2112.13237
Abusive language is a concerning problem in online social media. Past research on detecting abusive language covers different platforms, languages, demographies, etc. However, models trained using these datasets do not perform well in cross-domain ev
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8ea0f0d0a01b0dd9796953ee68d5f224