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Anji Liu
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2020 – today
- 2024
- [c20]Ceyao Zhang, Kaijie Yang, Siyi Hu, Zihao Wang, Guanghe Li, Yihang Sun, Cheng Zhang, Zhaowei Zhang, Anji Liu, Song-Chun Zhu, Xiaojun Chang, Junge Zhang, Feng Yin, Yitao Liang, Yaodong Yang:
ProAgent: Building Proactive Cooperative Agents with Large Language Models. AAAI 2024: 17591-17599 - [c19]Zixia Jia, Junpeng Li, Shichuan Zhang, Anji Liu, Zilong Zheng:
Combining Supervised Learning and Reinforcement Learning for Multi-Label Classification Tasks with Partial Labels. ACL (1) 2024: 13553-13569 - [c18]Zhihao Cao, Zidong Wang, Siwen Xie, Anji Liu, Lifeng Fan:
Smart Help: Strategic Opponent Modeling for Proactive and Adaptive Robot Assistance in Households. CVPR 2024: 18091-18101 - [c17]Shaofei Cai, Bowei Zhang, Zihao Wang, Xiaojian Ma, Anji Liu, Yitao Liang:
GROOT: Learning to Follow Instructions by Watching Gameplay Videos. ICLR 2024 - [c16]Anji Liu, Mathias Niepert, Guy Van den Broeck:
Image Inpainting via Tractable Steering of Diffusion Models. ICLR 2024 - [c15]Yizhe Huang, Anji Liu, Fanqi Kong, Yaodong Yang, Song-Chun Zhu, Xue Feng:
Efficient Adaptation in Mixed-Motive Environments via Hierarchical Opponent Modeling and Planning. ICML 2024 - [c14]Anji Liu, Kareem Ahmed, Guy Van den Broeck:
Scaling Tractable Probabilistic Circuits: A Systems Perspective. ICML 2024 - [i23]Anji Liu, Mathias Niepert, Guy Van den Broeck:
Image Inpainting via Tractable Steering of Diffusion Models. CoRR abs/2401.03349 (2024) - [i22]Zihao Wang, Anji Liu, Haowei Lin, Jiaqi Li, Xiaojian Ma, Yitao Liang:
RAT: Retrieval Augmented Thoughts Elicit Context-Aware Reasoning in Long-Horizon Generation. CoRR abs/2403.05313 (2024) - [i21]Zhihao Cao, Zidong Wang, Siwen Xie, Anji Liu, Lifeng Fan:
Smart Help: Strategic Opponent Modeling for Proactive and Adaptive Robot Assistance in Households. CoRR abs/2404.09001 (2024) - [i20]Vinh Tong, Anji Liu, Trung-Dung Hoang, Guy Van den Broeck, Mathias Niepert:
Learning to Discretize Denoising Diffusion ODEs. CoRR abs/2405.15506 (2024) - [i19]Anji Liu, Kareem Ahmed, Guy Van den Broeck:
Scaling Tractable Probabilistic Circuits: A Systems Perspective. CoRR abs/2406.00766 (2024) - [i18]Yizhe Huang, Anji Liu, Fanqi Kong, Yaodong Yang, Song-Chun Zhu, Xue Feng:
Efficient Adaptation in Mixed-Motive Environments via Hierarchical Opponent Modeling and Planning. CoRR abs/2406.08002 (2024) - [i17]Zixia Jia, Junpeng Li, Shichuan Zhang, Anji Liu, Zilong Zheng:
Combining Supervised Learning and Reinforcement Learning for Multi-Label Classification Tasks with Partial Labels. CoRR abs/2406.16293 (2024) - [i16]Zihao Wang, Shaofei Cai, Zhancun Mu, Haowei Lin, Ceyao Zhang, Xuejie Liu, Qing Li, Anji Liu, Xiaojian Ma, Yitao Liang:
OmniJARVIS: Unified Vision-Language-Action Tokenization Enables Open-World Instruction Following Agents. CoRR abs/2407.00114 (2024) - 2023
- [c13]Anji Liu, Hongming Xu, Guy Van den Broeck, Yitao Liang:
Out-of-Distribution Generalization by Neural-Symbolic Joint Training. AAAI 2023: 12252-12259 - [c12]Shaofei Cai, Zihao Wang, Xiaojian Ma, Anji Liu, Yitao Liang:
Open-World Multi-Task Control Through Goal-Aware Representation Learning and Adaptive Horizon Prediction. CVPR 2023: 13734-13744 - [c11]Anji Liu, Honghua Zhang, Guy Van den Broeck:
Scaling Up Probabilistic Circuits by Latent Variable Distillation. ICLR 2023 - [c10]Xuejie Liu, Anji Liu, Guy Van den Broeck, Yitao Liang:
Understanding the Distillation Process from Deep Generative Models to Tractable Probabilistic Circuits. ICML 2023: 21825-21838 - [c9]Zihao Wang, Shaofei Cai, Guanzhou Chen, Anji Liu, Xiaojian Ma, Yitao Liang:
Describe, Explain, Plan and Select: Interactive Planning with LLMs Enables Open-World Multi-Task Agents. NeurIPS 2023 - [i15]Shaofei Cai, Zihao Wang, Xiaojian Ma, Anji Liu, Yitao Liang:
Open-World Multi-Task Control Through Goal-Aware Representation Learning and Adaptive Horizon Prediction. CoRR abs/2301.10034 (2023) - [i14]Zihao Wang, Shaofei Cai, Anji Liu, Xiaojian Ma, Yitao Liang:
Describe, Explain, Plan and Select: Interactive Planning with Large Language Models Enables Open-World Multi-Task Agents. CoRR abs/2302.01560 (2023) - [i13]Xuejie Liu, Anji Liu, Guy Van den Broeck, Yitao Liang:
Understanding the Distillation Process from Deep Generative Models to Tractable Probabilistic Circuits. CoRR abs/2302.08086 (2023) - [i12]Ceyao Zhang, Kaijie Yang, Siyi Hu, Zihao Wang, Guanghe Li, Yihang Sun, Cheng Zhang, Zhaowei Zhang, Anji Liu, Song-Chun Zhu, Xiaojun Chang, Junge Zhang, Feng Yin, Yitao Liang, Yaodong Yang:
ProAgent: Building Proactive Cooperative AI with Large Language Models. CoRR abs/2308.11339 (2023) - [i11]Shaofei Cai, Bowei Zhang, Zihao Wang, Xiaojian Ma, Anji Liu, Yitao Liang:
GROOT: Learning to Follow Instructions by Watching Gameplay Videos. CoRR abs/2310.08235 (2023) - [i10]Xuejie Liu, Anji Liu, Guy Van den Broeck, Yitao Liang:
Expressive Modeling Is Insufficient for Offline RL: A Tractable Inference Perspective. CoRR abs/2311.00094 (2023) - [i9]Zihao Wang, Shaofei Cai, Anji Liu, Yonggang Jin, Jinbing Hou, Bowei Zhang, Haowei Lin, Zhaofeng He, Zilong Zheng, Yaodong Yang, Xiaojian Ma, Yitao Liang:
JARVIS-1: Open-World Multi-task Agents with Memory-Augmented Multimodal Language Models. CoRR abs/2311.05997 (2023) - 2022
- [c8]Anji Liu, Stephan Mandt, Guy Van den Broeck:
Lossless Compression with Probabilistic Circuits. ICLR 2022 - [c7]Meihua Dang, Anji Liu, Guy Van den Broeck:
Sparse Probabilistic Circuits via Pruning and Growing. NeurIPS 2022 - [c6]Zhizhou Ren, Anji Liu, Yitao Liang, Jian Peng, Jianzhu Ma:
Efficient Meta Reinforcement Learning for Preference-based Fast Adaptation. NeurIPS 2022 - [c5]Meihua Dang, Anji Liu, Xinzhu Wei, Sriram Sankararaman, Guy Van den Broeck:
Tractable and Expressive Generative Models of Genetic Variation Data. RECOMB 2022: 356-357 - [i8]Anji Liu, Honghua Zhang, Guy Van den Broeck:
Scaling Up Probabilistic Circuits by Latent Variable Distillation. CoRR abs/2210.04398 (2022) - [i7]Zhizhou Ren, Anji Liu, Yitao Liang, Jian Peng, Jianzhu Ma:
Efficient Meta Reinforcement Learning for Preference-based Fast Adaptation. CoRR abs/2211.10861 (2022) - [i6]Meihua Dang, Anji Liu, Guy Van den Broeck:
Sparse Probabilistic Circuits via Pruning and Growing. CoRR abs/2211.12551 (2022) - 2021
- [c4]Anji Liu, Guy Van den Broeck:
Tractable Regularization of Probabilistic Circuits. NeurIPS 2021: 3558-3570 - [c3]Antonio Vergari, YooJung Choi, Anji Liu, Stefano Teso, Guy Van den Broeck:
A Compositional Atlas of Tractable Circuit Operations for Probabilistic Inference. NeurIPS 2021: 13189-13201 - [i5]Antonio Vergari, YooJung Choi, Anji Liu, Stefano Teso, Guy Van den Broeck:
A Compositional Atlas of Tractable Circuit Operations: From Simple Transformations to Complex Information-Theoretic Queries. CoRR abs/2102.06137 (2021) - [i4]Anji Liu, Guy Van den Broeck:
Tractable Regularization of Probabilistic Circuits. CoRR abs/2106.02264 (2021) - [i3]Anji Liu, Stephan Mandt, Guy Van den Broeck:
Lossless Compression with Probabilistic Circuits. CoRR abs/2111.11632 (2021) - 2020
- [c2]Anji Liu, Yitao Liang, Guy Van den Broeck:
Off-Policy Deep Reinforcement Learning with Analogous Disentangled Exploration. AAMAS 2020: 753-761 - [c1]Anji Liu, Jianshu Chen, Mingze Yu, Yu Zhai, Xuewen Zhou, Ji Liu:
Watch the Unobserved: A Simple Approach to Parallelizing Monte Carlo Tree Search. ICLR 2020 - [i2]Anji Liu, Yitao Liang, Guy Van den Broeck:
Off-Policy Deep Reinforcement Learning with Analogous Disentangled Exploration. CoRR abs/2002.10738 (2020) - [i1]Anji Liu, Yitao Liang, Ji Liu, Guy Van den Broeck, Jianshu Chen:
On Effective Parallelization of Monte Carlo Tree Search. CoRR abs/2006.08785 (2020)
2010 – 2019
- 2018
- [j1]Anji Liu, Yuanjun Laili:
Balance gate controlled deep neural network. Neurocomputing 320: 183-194 (2018)
Coauthor Index
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