6 papers · 1 filter
Euler: Towards Human-Centered Multi-Agent Mathematical Discovery
Qiuyu Chen, Qi Wang, Liang Xu +3
Mathematical research drives scientific discovery, and recent advances in AI for mathematics have shown that language-model agents can solve challenging problems and develop substa…
EVOKE: Eliciting World Knowledge in Agents for Transferable Decision-Making
Yuhan Guo, Jinming Liu, Liang Xu +8
Large language models (LLMs) are increasingly deployed as agents for multi-step decision-making, yet transfer poorly to unseen environments. World-model methods address this by tra…
Spatiotemporally Decoupled Autoregressive Diffusion Model for Human Motion Generation
Chengqun Yang, Liang Xu, Yanping Li +4
Text-driven human motion synthesis has made substantial development with two core modules of motion representation and generative architecture. For representation, Vector Quantizat…
Inter-X++: A Comprehensive Benchmark for Multimodal Human-Human Interaction Analysis
Liang Xu, Chengqun Yang, Zili Lin +6
The capability to perceive and synthesize human-human interactions is fundamental to developing intelligent digital human systems. However, existing datasets and modeling approache…
MRBench: A Comprehensive Benchmark for Human Motion-Text Retrieval
Fulong Liu, Liang Xu, Chengqun Yang +3
Human motion-text retrieval provides a rigorous means of assessing cross-modal alignment. Prevailing benchmarks are dominated by homogeneous indoor motions, imbalanced motion distr…
ReWorld: Multi-Dimensional Reward Modeling for Embodied World Models
Baorui Peng, Wenyao Zhang, Liang Xu +5
Recently, video-based world models that learn to simulate the dynamics have gained increasing attention in robot learning. However, current approaches primarily emphasize visual ge…