5 papers
Positive Alignment: Artificial Intelligence for Human Flourishing
Ruben Laukkonen, Seb Krier, Chloé Bakalar +13
Existing alignment research is dominated by concerns about safety and preventing harm: safeguards, controllability, and compliance. This paradigm of alignment parallels early psych…
TRACE: Temporal Rule-Anchored Chain-of-Evidence on Knowledge Graphs for Interpretable Stock Movement Prediction
Qianggang Ding, Haochen Shi, Luis Castejón Lozano +7
We present a Temporal Rule-Anchored Chain-of-Evidence (TRACE) on knowledge graphs for interpretable stock movement prediction that unifies symbolic relational priors, dynamic graph…
Small Encoders Can Rival Large Decoders in Detecting Groundedness
Istabrak Abbes, Gabriele Prato, Quentin Fournier +4
Augmenting large language models (LLMs) with external context significantly improves their performance in natural language processing (NLP) tasks. However, LLMs struggle to answer…
Contemplative Artificial Intelligence
Ruben Laukkonen, Fionn Inglis, Shamil Chandaria +5
As artificial intelligence (AI) improves, traditional alignment strategies may falter in the face of unpredictable self-improvement, hidden subgoals, and the sheer complexity of in…
An LLM-Based Approach for Insight Generation in Data Analysis
Alberto Sánchez Pérez, Alaa Boukhary, Paolo Papotti +2
Generating insightful and actionable information from databases is critical in data analysis. This paper introduces a novel approach using Large Language Models (LLMs) to automatic…