5 papers
Aligning Stuttered-Speech Research with End-User Needs: Scoping Review, Survey, and Guidelines
Hawau Olamide Toyin, Mutiah Apampa, Toluwani Aremu +6
Atypical speech is receiving greater attention in speech technology research, but much of this work unfolds with limited interdisciplinary dialogue. For stuttered speech in particu…
RECALL: Library-Like Behavior In Language Models is Enhanced by Self-Referencing Causal Cycles
Munachiso Nwadike, Zangir Iklassov, Toluwani Aremu +6
We introduce the concept of the self-referencing causal cycle (abbreviated RECALL) - a mechanism that enables large language models (LLMs) to bypass the limitations of unidirection…
All Languages Matter: Evaluating LMMs on Culturally Diverse 100 Languages
Ashmal Vayani, Dinura Dissanayake, Hasindri Watawana +66
Existing Large Multimodal Models (LMMs) generally focus on only a few regions and languages. As LMMs continue to improve, it is increasingly important to ensure they understand cul…
On the Reliability of Large Language Models to Misinformed and Demographically-Informed Prompts
Toluwani Aremu, Oluwakemi Akinwehinmi, Chukwuemeka Nwagu +4
We investigate and observe the behaviour and performance of Large Language Model (LLM)-backed chatbots in addressing misinformed prompts and questions with demographic information…
Optimizing Adaptive Attacks against Watermarks for Language Models
Abdulrahman Diaa, Toluwani Aremu, Nils Lukas
Large Language Models (LLMs) can be misused to spread unwanted content at scale. Content watermarking deters misuse by hiding messages in content, enabling its detection using a se…