Papers
On Path to Multimodal Generalist: General-Level and General-Bench
Hao Fei, Yuan Zhou, Juncheng Li et al.
On Teacher Hacking in Language Model Distillation
Daniil Tiapkin, Daniele Calandriello, Johan Ferret et al.
On Temperature Scaling and Conformal Prediction of Deep Classifiers
Lahav Dabah, Tom Tirer
On the Adversarial Robustness of Multi-Kernel Clustering
Hao Yu, Weixuan Liang, Ke Liang et al.
On the Alignment between Fairness and Accuracy: from the Perspective of Adversarial Robustness
Junyi Chai, Taeuk Jang, Jing Gao et al.
On the Benefits of Active Data Collection in Operator Learning
Unique Subedi, Ambuj Tewari
On The Concurrence of Layer-wise Preconditioning Methods and Provable Feature Learning
Thomas Tck Zhang, Behrad Moniri, Ansh Nagwekar et al.
On the Convergence of Continuous Single-timescale Actor-critic
Xuyang Chen, Lin Zhao
On the Diversity of Adversarial Ensemble Learning
Jun-Qi Guo, Meng-Zhang Qian, Wei Gao et al.
On the Duality between Gradient Transformations and Adapters
Lucas Torroba Hennigen, Hunter Lang, Han Guo et al.
On the Dynamic Regret of Following the Regularized Leader: Optimism with History Pruning
Naram Mhaisen, George Iosifidis
On the Emergence of Position Bias in Transformers
Xinyi Wu, Yifei Wang, Stefanie Jegelka et al.
On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention for Long-Context LLM Serving
Yeonju Ro, Zhenyu Zhang, Souvik Kundu et al.
On the Generalization Ability of Next-Token-Prediction Pretraining
Zhihao Li, Xue Jiang, Liyuan Liu et al.
On the Guidance of Flow Matching
Ruiqi Feng, Chenglei Yu, Wenhao Deng et al.
On the Impact of Performative Risk Minimization for Binary Random Variables
Nikita Tsoy, Ivan Kirev, Negin Rahimiyazdi et al.
On the Importance of Embedding Norms in Self-Supervised Learning
Andrew Draganov, Sharvaree Vadgama, Sebastian Damrich et al.
On the Importance of Gaussianizing Representations
Daniel Eftekhari, Vardan Papyan
On the Learnability of Distribution Classes with Adaptive Adversaries
Tosca Lechner, Alex Bie, Gautam Kamath
On the Local Complexity of Linear Regions in Deep ReLU Networks
Niket Nikul Patel, Guido Montufar
On the Out-of-Distribution Generalization of Self-Supervised Learning
Wenwen Qiang, Jingyao Wang, Zeen Song et al.
On the Power of Context-Enhanced Learning in LLMs
Xingyu Zhu, Abhishek Panigrahi, Sanjeev Arora
On the Power of Learning-Augmented Search Trees
Jingbang Chen, Xinyuan Cao, Alicia Stepin et al.