Papers
11,015 papers found
TorchTitan: One-stop PyTorch native solution for production ready LLM pretraining
Wanchao Liang, Tianyu Liu, Less Wright et al.
To Tackle Adversarial Transferability: A Novel Ensemble Training Method with Fourier Transformation
Wanlin Zhang, Weichen Lin, Ruomin Huang et al.
To Trust or Not to Trust? Enhancing Large Language Models' Situated Faithfulness to External Contexts
Yukun Huang, Sanxing Chen, Hongyi Cai et al.
ToVE: Efficient Vision-Language Learning via Knowledge Transfer from Vision Experts
Yuanchen Wu, Junlong Du, Ke Yan et al.
Toward Exploratory Inverse Constraint Inference with Generative Diffusion Verifiers
Runyi Zhao, Sheng Xu, Bo Yue et al.
Toward Generalizing Visual Brain Decoding to Unseen Subjects
Xiangtao Kong, Kexin Huang, Ping Li et al.
Toward Guidance-Free AR Visual Generation via Condition Contrastive Alignment
Huayu Chen, Hang Su, Peize Sun et al.
Towards a General Time Series Anomaly Detector with Adaptive Bottlenecks and Dual Adversarial Decoders
Qichao Shentu, Beibu Li, Kai Zhao et al.
Towards a learning theory of representation alignment
Francesco Insulla, Shuo Huang, Lorenzo Rosasco
Towards a Unified and Verified Understanding of Group-Operation Networks
Wilson Wu, Louis Jaburi, jacob drori et al.
Towards Automated Knowledge Integration From Human-Interpretable Representations
Kasia Kobalczyk, Mihaela van der Schaar
Towards Auto-Regressive Next-Token Prediction: In-context Learning Emerges from Generalization
Zixuan Gong, Xiaolin Hu, Huayi Tang et al.
Towards Bridging Generalization and Expressivity of Graph Neural Networks
Shouheng Li, Floris Geerts, Dongwoo Kim et al.
Towards Calibrated Deep Clustering Network
Yuheng Jia, Jianhong Cheng, Hui LIU et al.
Towards Certification of Uncertainty Calibration under Adversarial Attacks
Cornelius Emde, Francesco Pinto, Thomas Lukasiewicz et al.
Towards Continuous Reuse of Graph Models via Holistic Memory Diversification
Ziyue Qiao, Junren Xiao, Qingqiang Sun et al.
Towards counterfactual fairness through auxiliary variables
Bowei Tian, Ziyao Wang, Shwai He et al.
Towards Domain Adaptive Neural Contextual Bandits
Ziyan Wang, Xiaoming Huo, Hao Wang
Towards Effective Evaluations and Comparisons for LLM Unlearning Methods
Qizhou Wang, Bo Han, Puning Yang et al.
Towards Empowerment Gain through Causal Structure Learning in Model-Based Reinforcement Learning
Hongye Cao, Fan Feng, Meng Fang et al.
Towards Explaining the Power of Constant-depth Graph Neural Networks for Structured Linear Programming
Qian Li, Minghui Ouyang, Tian Ding et al.
Towards Faster Decentralized Stochastic Optimization with Communication Compression
Rustem Islamov, Yuan Gao, Sebastian U Stich