most citedControlling Out-of-Domain Gaps in LLMs for Genre Classification and Generated Text Detection

1 citations · 1 across the 3 of their papers we have counts for

collaborators

3 papers

cs.CL2024

NLP-based Regulatory Compliance -- Using GPT 4.0 to Decode Regulatory Documents

Bimal Kumar, Dmitri Roussinov

Large Language Models (LLMs) such as GPT-4.0 have shown significant promise in addressing the semantic complexities of regulatory documents, particularly in detecting inconsistenci…

cs.CL2024★ 1 cited

Controlling Out-of-Domain Gaps in LLMs for Genre Classification and Generated Text Detection

Dmitri Roussinov, Serge Sharoff, Nadezhda Puchnina

This study demonstrates that the modern generation of Large Language Models (LLMs, such as GPT-4) suffers from the same out-of-domain (OOD) performance gap observed in prior resear…

cs.CL2023

BERT Goes Off-Topic: Investigating the Domain Transfer Challenge using Genre Classification

Dmitri Roussinov, Serge Sharoff

While performance of many text classification tasks has been recently improved due to Pre-trained Language Models (PLMs), in this paper we show that they still suffer from a perfor…