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Stick to your Role! Stability of Personal Values Expressed in Large Language Models
In this paper, we present a case-study about the stability of value expression over different contexts (simulated conversations on different topics), and as measured using a standard psychology questionnaire (PVQ) and a behavioral downstream task.
The SocialAI School: Insights from Developmental Psychology Towards Artificial Socio-Cultural Agents
Developmental psychologists have long-established the importance of socio-cognitive abilities in human intelligence.
Large Language Models as Superpositions of Cultural Perspectives
We introduce the concept of perspective controllability, which refers to a model's affordance to adopt various perspectives with differing values and personality traits.
SocialAI: Benchmarking Socio-Cognitive Abilities in Deep Reinforcement Learning Agents
In this paper, we argue that aiming towards human-level AI requires a broader set of key social skills: 1) language use in complex and variable social contexts; 2) beyond language, complex embodied communication in multimodal settings within constantly evolving social worlds.
SocialAI 0.1: Towards a Benchmark to Stimulate Research on Socio-Cognitive Abilities in Deep Reinforcement Learning Agents
Building embodied autonomous agents capable of participating in social interactions with humans is one of the main challenges in AI.
GRIMGEP: Learning Progress for Robust Goal Sampling in Visual Deep Reinforcement Learning
However, a currently known limitation of agents trying to maximize the diversity of sampled goals is that they tend to get attracted to noise or more generally to parts of the environments that cannot be controlled (distractors).
