48 citations · 77 across the 10 of their papers we have counts for
11 papers
ComBodied Agents: a New Paradigm of Human-Centric Agentic AI
Qianggang Ding, Xingyao Wang, Rui Feng +19
After an older adult misses a medication dose, a software agent can send another reminder and an embodied agent can bring the medication. Yet neither explains whether the person fo…
Mixture of States: Routing Token-Level Dynamics for Multimodal Generation
Haozhe Liu, Ding Liu, Mingchen Zhuge +16
We introduce MoS (Mixture of States), a novel fusion paradigm for multimodal diffusion models that merges modalities using flexible, state-based interactions. The core of MoS is a…
Scaling Sequence-to-Sequence Generative Neural Rendering
Shikun Liu, Kam Woh Ng, Wonbong Jang +9
We present Kaleido, a family of generative models designed for photorealistic, unified object- and scene-level neural rendering. Kaleido operates on the principle that 3D can be re…
QuantBench: Benchmarking AI Methods for Quantitative Investment
Saizhuo Wang, Hao Kong, Jiadong Guo +7
The field of artificial intelligence (AI) in quantitative investment has seen significant advancements, yet it lacks a standardized benchmark aligned with industry practices. This…
Learning Compiler Pass Orders using Coreset and Normalized Value Prediction
Youwei Liang, Kevin Stone, Ali Shameli +8
Finding the optimal pass sequence of compilation can lead to a significant reduction in program size and/or improvement in program efficiency. Prior works on compilation pass order…
CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research
Chris Cummins, Bram Wasti, Jiadong Guo +9
Interest in applying Artificial Intelligence (AI) techniques to compiler optimizations is increasing rapidly, but compiler research has a high entry barrier. Unlike in other domain…
Safe Exploration by Solving Early Terminated MDP
Hao Sun, Ziping Xu, Meng Fang +4
Safe exploration is crucial for the real-world application of reinforcement learning (RL). Previous works consider the safe exploration problem as Constrained Markov Decision Proce…
Risk-Averse Trust Region Optimization for Reward-Volatility Reduction
Lorenzo Bisi, Luca Sabbioni, Edoardo Vittori +2
In real-world decision-making problems, for instance in the fields of finance, robotics or autonomous driving, keeping uncertainty under control is as important as maximizing expec…
Unsupervised Star Galaxy Classification with Cascade Variational Auto-Encoder
Hao Sun, Jiadong Guo, Edward J. Kim +1
The increasing amount of data in astronomy provides great challenges for machine learning research. Previously, supervised learning methods achieved satisfactory recognition accura…
Bayesian Symbolic Regression
Ying Jin, Weilin Fu, Jian Kang +2
Interpretability is crucial for machine learning in many scenarios such as quantitative finance, banking, healthcare, etc. Symbolic regression (SR) is a classic interpretable machi…
Adaptive Regularization of Labels
Qianggang Ding, Sifan Wu, Hao Sun +2
Recently, a variety of regularization techniques have been widely applied in deep neural networks, such as dropout, batch normalization, data augmentation, and so on. These methods…