5 citations · 7 across the 8 of their papers we have counts for
8 papers
Non-literal Understanding of Number Words by Language Models
Polina Tsvilodub, Kanishk Gandhi, Haoran Zhao +3
Humans naturally interpret numbers non-literally, effortlessly combining context, world knowledge, and speaker intent. We investigate whether large language models (LLMs) interpret…
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…
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…
From Centralized to Self-Supervised: Pursuing Realistic Multi-Agent Reinforcement Learning
Violet Xiang, Logan Cross, Jan-Philipp Fränken +1
In real-world environments, autonomous agents rely on their egocentric observations. They must learn adaptive strategies to interact with others who possess mixed motivations, disc…
Modeling infant object perception as program induction
Jan-Philipp Fränken, Christopher G. Lucas, Neil R. Bramley +1
Infants expect physical objects to be rigid and persist through space and time and in spite of occlusion. Developmentists frequently attribute these expectations to a "core system"…