215 citations · 2.3k across the 165 of their papers we have counts for
167 papers
Music-to-Dance Generation via Atomic Movements
Xinhao Cai, Yixuan Sun, Minghang Zheng +4
Music-driven dance generation aims to produce human motion that is both rhythmically synchronized and semantically consistent with music. While recent neural approaches have achiev…
CORE: Common Random Reconstruction for Distributed Optimization with Provable Low Communication Complexity
Pengyun Yue, Hanzhen Zhao, Cong Fang +4
With distributed machine learning being a prominent technique for large-scale machine learning tasks, communication complexity has become a major bottleneck for speeding up trainin…
MindAgent: Emergent Gaming Interaction
Ran Gong, Qiuyuan Huang, Xiaojian Ma +8
Large Language Models (LLMs) have the capacity of performing complex scheduling in a multi-agent system and can coordinate these agents into completing sophisticated tasks that req…
Sim2Plan: Robot Motion Planning via Message Passing between Simulation and Reality
Yizhou Zhao, Yuanhong Zeng, Qian Long +2
Simulation-to-real is the task of training and developing machine learning models and deploying them in real settings with minimal additional training. This approach is becoming in…
Brain in a Vat: On Missing Pieces Towards Artificial General Intelligence in Large Language Models
Yuxi Ma, Chi Zhang, Song-Chun Zhu
In this perspective paper, we first comprehensively review existing evaluations of Large Language Models (LLMs) using both standardized tests and ability-oriented benchmarks. We pi…
Large Language Models are In-Context Semantic Reasoners rather than Symbolic Reasoners
Xiaojuan Tang, Zilong Zheng, Jiaqi Li +4
The emergent few-shot reasoning capabilities of Large Language Models (LLMs) have excited the natural language and machine learning community over recent years. Despite of numerous…