Papers
11,015 papers found
Towards LLM4QPE: Unsupervised Pretraining of Quantum Property Estimation and A Benchmark
Yehui Tang, Hao Xiong, Nianzu Yang et al.
Towards Lossless Dataset Distillation via Difficulty-Aligned Trajectory Matching
Ziyao Guo, Kai Wang, George Cazenavette et al.
Towards Meta-Pruning via Optimal Transport
Alexander Theus, Olin Geimer, Friedrich Wicke et al.
Towards Non-Asymptotic Convergence for Diffusion-Based Generative Models
Gen Li, Yuting Wei, Yuxin Chen et al.
Towards Offline Opponent Modeling with In-context Learning
Yuheng Jing, Kai Li, Bingyun Liu et al.
Towards Optimal Feature-Shaping Methods for Out-of-Distribution Detection
Qinyu Zhao, Ming Xu, Kartik Gupta et al.
Towards Optimal Regret in Adversarial Linear MDPs with Bandit Feedback
Haolin Liu, Chen-Yu Wei, Julian Zimmert
Towards Poisoning Fair Representations
Tianci Liu, Haoyu Wang, Feijie Wu et al.
Towards Principled Representation Learning from Videos for Reinforcement Learning
Dipendra Misra, Akanksha Saran, Tengyang Xie et al.
Towards Reliable and Efficient Backdoor Trigger Inversion via Decoupling Benign Features
Xiong Xu, Kunzhe Huang, Yiming Li et al.
Towards Robust and Efficient Cloud-Edge Elastic Model Adaptation via Selective Entropy Distillation
Yaofo Chen, Shuaicheng Niu, Yaowei Wang et al.
Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks
Xu Zheng, Farhad Shirani, Tianchun Wang et al.
Towards Robust Multi-Modal Reasoning via Model Selection
Xiangyan Liu, Rongxue LI, Wei Ji et al.
Towards Robust Offline Reinforcement Learning under Diverse Data Corruption
Rui Yang, Han Zhong, Jiawei Xu et al.
Towards Robust Out-of-Distribution Generalization Bounds via Sharpness
Yingtian Zou, Kenji Kawaguchi, Yingnan Liu et al.
Towards Seamless Adaptation of Pre-trained Models for Visual Place Recognition
Feng Lu, Lijun Zhang, Xiangyuan Lan et al.
Towards the Fundamental Limits of Knowledge Transfer over Finite Domains
Qingyue Zhao, Banghua Zhu
Towards Training Without Depth Limits: Batch Normalization Without Gradient Explosion
Alexandru Meterez, Amir Joudaki, Francesco Orabona et al.
Towards Transparent Time Series Forecasting
Krzysztof Kacprzyk, Tennison Liu, Mihaela van der Schaar
Toward Student-oriented Teacher Network Training for Knowledge Distillation
Chengyu Dong, Liyuan Liu, Jingbo Shang
Towards Understanding Factual Knowledge of Large Language Models
Xuming Hu, Junzhe Chen, Xiaochuan Li et al.
Towards Understanding Sycophancy in Language Models
Mrinank Sharma, Meg Tong, Tomasz Korbak et al.
Towards Unified Multi-Modal Personalization: Large Vision-Language Models for Generative Recommendation and Beyond
Tianxin Wei, Bowen Jin, Ruirui Li et al.
Tractable MCMC for Private Learning with Pure and Gaussian Differential Privacy
Yingyu Lin, Yian Ma, Yu-Xiang Wang et al.
Tractable Probabilistic Graph Representation Learning with Graph-Induced Sum-Product Networks
Federico Errica, Mathias Niepert