7 papers
Effectiveness of Chain-of-Thought in Distilling Reasoning Capability from Large Language Models
Cong-Thanh Do, Rama Doddipatla, Kate Knill
Chain-of-Thought (CoT) prompting is a widely used method to improve the reasoning capability of Large Language Models (LLMs). More recently, CoT has been leveraged in Knowledge Dis…
Data Augmentation for Spoken Grammatical Error Correction
Penny Karanasou, Mengjie Qian, Stefano Bannò +2
While there exist strong benchmark datasets for grammatical error correction (GEC), high-quality annotated spoken datasets for Spoken GEC (SGEC) are still under-resourced. In this…
Natural Language-based Assessment of L2 Oral Proficiency using LLMs
Stefano Bannò, Rao Ma, Mengjie Qian +3
Natural language-based assessment (NLA) is an approach to second language assessment that uses instructions - expressed in the form of can-do descriptors - originally intended for…
End-to-End Spoken Grammatical Error Correction
Mengjie Qian, Rao Ma, Stefano Bannò +2
Grammatical Error Correction (GEC) and feedback play a vital role in supporting second language (L2) learners, educators, and examiners. While written GEC is well-established, spok…
Exploiting the English Vocabulary Profile for L2 word-level vocabulary assessment with LLMs
Stefano Bannò, Kate Knill, Mark Gales
Vocabulary use is a fundamental aspect of second language (L2) proficiency. To date, its assessment by automated systems has typically examined the context-independent, or part-of-…
Universal Acoustic Adversarial Attacks for Flexible Control of Speech-LLMs
Rao Ma, Mengjie Qian, Vyas Raina +2
The combination of pre-trained speech encoders with large language models has enabled the development of speech LLMs that can handle a wide range of spoken language processing task…