activity
20192024
most citedImproving Factuality and Reasoning in Language Models through Multiagent Debate

94 citations · 477 across the 43 of their papers we have counts for

collaborators
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5 papers · 1 filter

cs.AI2023★ 12 cited

Learning Interactive Real-World Simulators

Sherry Yang, Yilun Du, Kamyar Ghasemipour +4

Generative models trained on internet data have revolutionized how text, image, and video content can be created. Perhaps the next milestone for generative models is to simulate re…

cs.AI2023★ 40 cited

Building Cooperative Embodied Agents Modularly with Large Language Models

Hongxin Zhang, Weihua Du, Jiaming Shan +5

In this work, we address challenging multi-agent cooperation problems with decentralized control, raw sensory observations, costly communication, and multi-objective tasks instanti…

cs.AI2023★ 1 cited

Probabilistic Adaptation of Text-to-Video Models

Mengjiao Yang, Yilun Du, Bo Dai +3

Large text-to-video models trained on internet-scale data have demonstrated exceptional capabilities in generating high-fidelity videos from arbitrary textual descriptions. However…

cs.AI2023★ 52 cited

Foundation Models for Decision Making: Problems, Methods, and Opportunities

Sherry Yang, Ofir Nachum, Yilun Du +3

Foundation models pretrained on diverse data at scale have demonstrated extraordinary capabilities in a wide range of vision and language tasks. When such models are deployed in re…

cs.AI2023★ 29 cited

Learning Universal Policies via Text-Guided Video Generation

Yilun Du, Mengjiao Yang, Bo Dai +5

A goal of artificial intelligence is to construct an agent that can solve a wide variety of tasks. Recent progress in text-guided image synthesis has yielded models with an impress…