The rapid development in large language models (LLMs) has transformed the landscape of natural language processing and understanding (NLP/NLU), offering significant benefits across various domains. However, when applied to scientific research, these powerful models exhibit critical failure modes related to … Continued
Large language models (LLMs) provide a compelling foundation for building generally-capable AI agents. These agents may soon be deployed at scale in the real world, representing the interests of individual humans (e.g., AI assistants) or groups of humans (e.g., AI-accelerated … Continued
Knowledge Tracing (KT) is a research field that aims to estimate a student’s knowledge state through learning interactions-a crucial component of Intelligent Tutoring Systems (ITSs). Despite significant advancements, no current KT models excel in both predictive accuracy and interpretability. Meanwhile, … Continued
In this paper, we investigate whether current state-of-the-art large language models (LLMs) are effective as AI tutors and whether they demonstrate pedagogical abilities necessary for good AI tutoring in educational dialogues. Previous efforts towards evaluation have been limited to subjective … Continued
With the continuous development of technological and educational innovation, learners nowadays can obtain a variety of support from agents such as teachers, peers, education technologies, and recently, generative artificial intelligence such as ChatGPT. The concept of hybrid intelligence is still … Continued
The UNESCO Recommendations for Open Science define it as an inclusive framework that integrates movements and practices aimed at making multilingual scientific knowledge openly accessible, reusable, and collaborative for the benefit of science and society. This approach emphasizes transparency, collaboration, … Continued
Objectivity is widely regarded as crucial for scientific practice, yet it remains poorly understood in scientific methodology and, as a result, has limited impact on research practices. Building on recent developments in the philosophy of science, we have created a … Continued
We articulate fundamental mismatches between technical methods for machine unlearning in Generative AI, and documented aspirations for broader impact that these methods could have for law and policy. These aspirations are both numerous and varied, motivated by issues that pertain … Continued
How do language models use information provided as context when generating a response? Can we infer whether a particular generated statement is actually grounded in the context, a misinterpretation, or fabricated? To help answer these questions, we introduce the problem … Continued
Ryan Watkins and Eran Barak-Medina recently published AI’s Influence on Human Creative Agency in the Creativity Research Journal. Abstract: Emerging Artificial Intelligence (AI) capabilities are redefining roles traditionally assigned to humans or tools in numerous tasks, and thereby creating tensions … Continued