4 papers
Evaluating Communicative Belief Updates in Large Language Models via Implicature Recognition and Cancellation
Cesare Spinoso-Di Piano, Verna Dankers, Marius Mosbach +1
Human language is driven by unspoken beliefs and belief updates, making these critical to model for successful communication between large language models (LLMs) and their users. I…
Can Vision Language Models Be Adaptive in Mathematics Education? A Learner Model-based Rubric Study
Jie Gao, Yongan Yu, Junzhu Su +3
Adaptive learning refers to educational technologies that track learners' learning progress and adapt the instructional process based on individual learners' learning performance.…
Identifying and Analyzing Performance-Critical Tokens in Large Language Models
Yu Bai, Heyan Huang, Cesare Spinoso-Di Piano +4
In-context learning (ICL) has emerged as an effective solution for few-shot learning with large language models (LLMs). However, how LLMs leverage demonstrations to specify a task…
Neither Valid nor Reliable? Investigating the Use of LLMs as Judges
Khaoula Chehbouni, Mohammed Haddou, Jackie Chi Kit Cheung +1
Evaluating natural language generation (NLG) systems remains a core challenge of natural language processing (NLP), further complicated by the rise of large language models (LLMs)…