6 papers
FlashPDE: A Drop-In Fused Triton Operator Library for Neural PDE Solvers
Peiyu Zang, Bosen Xie, Ruoxiang Xu +1
Physics-Informed Neural Networks (PINNs) solve PDEs by incorporating physical constraints into neural-network training, but large-scale problems are limited by automatic-differenti…
PraMem: Practice-derived Experiential Memory for Long-horizon Behavior Prediction
Zhuoqun Li, Boxi Cao, Jiawei Chen +11
Long-horizon behavior prediction aims to infer a user's next action based on a lengthy historical sequence, playing a crucial role in artificial intelligence field. The rise of lar…
Towards Real-world Human Behavior Simulation: Benchmarking Large Language Models on Long-horizon, Cross-scenario, Heterogeneous Behavior Traces
Jiawei Chen, Ruoxi Xu, Boxi Cao +11
The emergence of Large Language Models (LLMs) has illuminated the potential for a general-purpose user simulator. However, existing benchmarks remain constrained to isolated scenar…
Vocabulary In-Context Learning in Transformers: Benefits of Positional Encoding
Qian Ma, Ruoxiang Xu, Yongqiang Cai
Numerous studies have demonstrated that the Transformer architecture possesses the capability for in-context learning (ICL). In scenarios involving function approximation, context…
Memorizing is Not Enough: Deep Knowledge Injection Through Reasoning
Ruoxi Xu, Yunjie Ji, Boxi Cao +7
Although large language models (LLMs) excel in knowledge recall and reasoning, their static nature leads to outdated information as the real world evolves or when adapting to domai…
Large Language Models Often Say One Thing and Do Another
Ruoxi Xu, Hongyu Lin, Xianpei Han +4
As large language models (LLMs) increasingly become central to various applications and interact with diverse user populations, ensuring their reliable and consistent performance i…