36 citations · 63 across the 32 of their papers we have counts for
9 papers · 1 filter
PICLe: Pseudo-Annotations for In-Context Learning in Low-Resource Named Entity Detection
Sepideh Mamooler, Syrielle Montariol, Alexander Mathis +1
In-context learning (ICL) enables Large Language Models (LLMs) to perform tasks using few demonstrations, facilitating task adaptation when labeled examples are hard to obtain. How…
Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation
Shivalika Singh, Angelika Romanou, Clémentine Fourrier +21
Cultural biases in multilingual datasets pose significant challenges for their effectiveness as global benchmarks. These biases stem not only from differences in language but also…
INCLUDE: Evaluating Multilingual Language Understanding with Regional Knowledge
Angelika Romanou, Negar Foroutan, Anna Sotnikova +56
The performance differential of large language models (LLM) between languages hinders their effective deployment in many regions, inhibiting the potential economic and societal val…
Creativity in AI: Progresses and Challenges
Mete Ismayilzada, Debjit Paul, Antoine Bosselut +1
Creativity is the ability to produce novel, useful, and surprising ideas, and has been widely studied as a crucial aspect of human cognition. Machine creativity on the other hand h…
Evaluating Morphological Compositional Generalization in Large Language Models
Mete Ismayilzada, Defne Circi, Jonne Sälevä +6
Large language models (LLMs) have demonstrated significant progress in various natural language generation and understanding tasks. However, their linguistic generalization capabil…
LLMs Are In-Context Bandit Reinforcement Learners
Giovanni Monea, Antoine Bosselut, Kianté Brantley +1
Large Language Models (LLMs) excel at in-context learning (ICL), a supervised learning technique that relies on adding annotated examples to the model context. We investigate a con…
Could ChatGPT get an Engineering Degree? Evaluating Higher Education Vulnerability to AI Assistants
Beatriz Borges, Negar Foroutan, Deniz Bayazit +87
AI assistants are being increasingly used by students enrolled in higher education institutions. While these tools provide opportunities for improved teaching and education, they a…
A Logical Fallacy-Informed Framework for Argument Generation
Luca Mouchel, Debjit Paul, Shaobo Cui +3
Despite the remarkable performance of Large Language Models (LLMs) in natural language processing tasks, they still struggle with generating logically sound arguments, resulting in…
Making Reasoning Matter: Measuring and Improving Faithfulness of Chain-of-Thought Reasoning
Debjit Paul, Robert West, Antoine Bosselut +1
Large language models (LLMs) have been shown to perform better when asked to reason step-by-step before answering a question. However, it is unclear to what degree the model's fina…