Papers
11,951 papers found
Training Free Exponential Context Extension via Cascading KV Cache
Jeffrey Willette, Heejun Lee, Youngwan Lee et al.
Training Free Guided Flow-Matching with Optimal Control
Luran Wang, Chaoran Cheng, Yizhen Liao et al.
Training-free LLM-generated Text Detection by Mining Token Probability Sequences
Yihuai Xu, Yongwei Wang, Yifei Bi et al.
Training-Free Message Passing for Learning on Hypergraphs
Bohan Tang, Zexi Liu, Keyue Jiang et al.
Training Language Models on Synthetic Edit Sequences Improves Code Synthesis
Ulyana Piterbarg, Lerrel Pinto, Rob Fergus
Training Language Models to Self-Correct via Reinforcement Learning
Aviral Kumar, Vincent Zhuang, Rishabh Agarwal et al.
Training Large Language Models for Retrieval-Augmented Question Answering through Backtracking Correction
Huawen Feng, ZekunYao, Junhao Zheng et al.
Training Neural Networks as Recognizers of Formal Languages
Alexandra Butoi, Ghazal Khalighinejad, Anej Svete et al.
Training Nonlinear Transformers for Chain-of-Thought Inference: A Theoretical Generalization Analysis
Hongkang Li, Songtao Lu, Pin-Yu Chen et al.
Training One-Dimensional Graph Neural Networks is NP-Hard
Robert Ganian, Mathis Rocton, Simon Wietheger
Training on the Test Task Confounds Evaluation and Emergence
Ricardo Dominguez-Olmedo, Florian E. Dorner, Moritz Hardt
Training Robust Ensembles Requires Rethinking Lipschitz Continuity
Ali Ebrahimpour-Boroojeny, Hari Sundaram, Varun Chandrasekaran
Train Small, Infer Large: Memory-Efficient LoRA Training for Large Language Models
Jun Zhang, Jue WANG, Huan Li et al.
Trajectory attention for fine-grained video motion control
Zeqi Xiao, Wenqi Ouyang, Yifan Zhou et al.
Trajectory-Class-Aware Multi-Agent Reinforcement Learning
Hyungho Na, Kwanghyeon Lee, Sumin Lee et al.
Trajectory-LLM: A Language-based Data Generator for Trajectory Prediction in Autonomous Driving
Kairui Yang, Zihao Guo, Gengjie Lin et al.
Transformer Block Coupling and its Correlation with Generalization in LLMs
Murdock Aubry, Haoming Meng, Anton Sugolov et al.
Transformer Encoder Satisfiability: Complexity and Impact on Formal Reasoning
Marco Sälzer, Eric Alsmann, Martin Lange
Transformer Learns Optimal Variable Selection in Group-Sparse Classification
Chenyang Zhang, Xuran Meng, Yuan Cao
Transformer Meets Twicing: Harnessing Unattended Residual Information
Laziz Abdullaev, Tan Minh Nguyen
Transformers are Universal In-context Learners
Takashi Furuya, Maarten V. de Hoop, Gabriel Peyré
Transformers Can Learn Temporal Difference Methods for In-Context Reinforcement Learning
Jiuqi Wang, Ethan Blaser, Hadi Daneshmand et al.
Transformers Handle Endogeneity in In-Context Linear Regression
Haodong Liang, Krishna Balasubramanian, Lifeng Lai
Transformers Learn Low Sensitivity Functions: Investigations and Implications
Bhavya Vasudeva, Deqing Fu, Tianyi Zhou et al.
Transformers Learn to Implement Multi-step Gradient Descent with Chain of Thought
Jianhao Huang, Zixuan Wang, Jason D. Lee