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Raphael Koster

4 accepted papers

2023

Perception Test: A Diagnostic Benchmark for Multimodal Video Models

NeurIPS 2023poster

We propose a novel multimodal video benchmark - the Perception Test - to evaluate the perception and reasoning skills of pre-trained multimodal models (e.g. Flamingo, BEiT-3, or GPT-4). Compared to existing benchmarks that focus on computational tasks (e.g. classification, detection or tracking), th…

2022

Role of Human-AI Interaction in Selective Prediction

AAAI 2022technical

Recent work has shown the potential benefit of selective prediction systems that can learn to defer to a human when the predictions of the AI are unreliable, particularly to improve the reliability of AI systems in high-stakes applications like healthcare or conservation. However, most prior work a…

2021

Scalable Evaluation of Multi-Agent Reinforcement Learning with Melting Pot

ICML 2021oral

Existing evaluation suites for multi-agent reinforcement learning (MARL) do not assess generalization to novel situations as their primary objective (unlike supervised learning benchmarks). Our contribution, Melting Pot, is a MARL evaluation suite that fills this gap and uses reinforcement learning…

Cited by 117SourcePDFScholar
2018

Inequity aversion improves cooperation in intertemporal social dilemmas

NeurIPS 2018poster

Groups of humans are often able to find ways to cooperate with one another in complex, temporally extended social dilemmas. Models based on behavioral economics are only able to explain this phenomenon for unrealistic stateless matrix games. Recently, multi-agent reinforcement learning has been appl…

Cited by 296SourcePDFScholar