565 citations · 688 across the 26 of their papers we have counts for
8 papers · 1 filter
Imagining and building wise machines: The centrality of AI metacognition
Samuel G. B. Johnson, Amir-Hossein Karimi, Yoshua Bengio +8
Although AI has become increasingly smart, its wisdom has not kept pace. In this article, we examine what is known about human wisdom and sketch a vision of its AI counterpart. We…
MARPLE: A Benchmark for Long-Horizon Inference
Emily Jin, Zhuoyi Huang, Jan-Philipp Fränken +7
Reconstructing past events requires reasoning across long time horizons. To figure out what happened, we need to use our prior knowledge about the world and human behavior and draw…
Human-like Affective Cognition in Foundation Models
Kanishk Gandhi, Zoe Lynch, Jan-Philipp Fränken +5
Understanding emotions is fundamental to human interaction and experience. Humans easily infer emotions from situations or facial expressions, situations from emotions, and do a va…
PERSONA: A Reproducible Testbed for Pluralistic Alignment
Louis Castricato, Nathan Lile, Rafael Rafailov +2
The rapid advancement of language models (LMs) necessitates robust alignment with diverse user values. However, current preference optimization approaches often fail to capture the…
To Err is Robotic: Rapid Value-Based Trial-and-Error during Deployment
Maximilian Du, Alexander Khazatsky, Tobias Gerstenberg +1
When faced with a novel scenario, it can be hard to succeed on the first attempt. In these challenging situations, it is important to know how to retry quickly and meaningfully. Re…
Self-Supervised Alignment with Mutual Information: Learning to Follow Principles without Preference Labels
Jan-Philipp Fränken, Eric Zelikman, Rafael Rafailov +3
When prompting a language model (LM), users often expect the model to adhere to a set of behavioral principles across diverse tasks, such as producing insightful content while avoi…
Procedural Dilemma Generation for Evaluating Moral Reasoning in Humans and Language Models
Jan-Philipp Fränken, Kanishk Gandhi, Tori Qiu +3
As AI systems like language models are increasingly integrated into decision-making processes affecting people's lives, it's critical to ensure that these systems have sound moral…
STaR-GATE: Teaching Language Models to Ask Clarifying Questions
Chinmaya Andukuri, Jan-Philipp Fränken, Tobias Gerstenberg +1
When prompting language models to complete a task, users often leave important aspects unsaid. While asking questions could resolve this ambiguity (GATE; Li et al., 2023), models o…