Dipam Chakraborty — accepted AI-conference papers

2024

Melting Pot Contest: Charting the Future of Generalized Cooperative Intelligence

Rakshit Trivedi, Akbir Khan, Jesse Clifton, Lewis Hammond, Edgar A. Duéñez-Guzmán, Dipam Chakraborty +20

NeurIPS 2024poster

Multi-agent AI research promises a path to develop human-like and human-compatible intelligent technologies that complement the solipsistic view of other approaches, which mostly do not consider interactions between agents. Aiming to make progress in this direction, the Melting Pot contest 2023 focu…

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2023

MABe22: A Multi-Species Multi-Task Benchmark for Learned Representations of Behavior

Jennifer J. Sun, Markus Marks, Andrew Wesley Ulmer, Dipam Chakraborty, Brian Geuther, Edward Hayes +17

ICML 2023poster

We introduce MABe22, a large-scale, multi-agent video and trajectory benchmark to assess the quality of learned behavior representations. This dataset is collected from a variety of biology experiments, and includes triplets of interacting mice (4.7 million frames video+pose tracking data, 10 millio…

Cited by 12 Source ↗PDF ↗code ↗Scholar ↗

2021

The Multi-Agent Behavior Dataset: Mouse Dyadic Social Interactions

Jennifer J. Sun, Tomomi Karigo, Dipam Chakraborty, Sharada Mohanty, Benjamin Wild, Quan Sun +5

NeurIPS 2021poster

Multi-agent behavior modeling aims to understand the interactions that occur between agents. We present a multi-agent dataset from behavioral neuroscience, the Caltech Mouse Social Interactions (CalMS21) Dataset. Our dataset consists of trajectory data of social interactions, recorded from videos of…

Cited by 58 Source ↗code ↗Scholar ↗