All Papers
34,598 papers found • Page 617 of 692
Conference
Position: Open-Endedness is Essential for Artificial Superhuman Intelligence
Edward Hughes, Michael Dennis, Jack Parker-Holder et al.
Position: Opportunities Exist for Machine Learning in Magnetic Fusion Energy
Lucas Spangher, Allen Wang, Andrew Maris et al.
Position: Optimization in SciML Should Employ the Function Space Geometry
Johannes Müller, Marius Zeinhofer
Position: Quo Vadis, Unsupervised Time Series Anomaly Detection?
M. Saquib Sarfraz, Mei-Yen Chen, Lukas Layer et al.
Position: Reinforcement Learning in Dynamic Treatment Regimes Needs Critical Reexamination
Zhiyao Luo, Yangchen Pan, Peter Watkinson et al.
Position: Relational Deep Learning - Graph Representation Learning on Relational Databases
Matthias Fey, Weihua Hu, Kexin Huang et al.
Position: Rethinking Post-Hoc Search-Based Neural Approaches for Solving Large-Scale Traveling Salesman Problems
Yifan Xia, Xianliang Yang, Zichuan Liu et al.
Position: Scaling Simulation is Neither Necessary Nor Sufficient for In-the-Wild Robot Manipulation
Homanga Bharadhwaj
Position: Scarce Resource Allocations That Rely On Machine Learning Should Be Randomized
Shomik Jain, Kathleen A. Creel, Ashia Wilson
Position: Social Choice Should Guide AI Alignment in Dealing with Diverse Human Feedback
Vincent Conitzer, Rachel Freedman, Jobstq Heitzig et al.
Position: Social Environment Design Should be Further Developed for AI-based Policy-Making
Edwin Zhang, Sadie Zhao, Tonghan Wang et al.
Position: Standardization of Behavioral Use Clauses is Necessary for the Adoption of Responsible Licensing of AI
Daniel McDuff, Tim Korjakow, Scott Cambo et al.
Position: Stop Making Unscientific AGI Performance Claims
Patrick Altmeyer, Andrew Demetriou, Antony Bartlett et al.
Position: Technical Research and Talent is Needed for Effective AI Governance
Anka Reuel, Lisa Soder, Benjamin Bucknall et al.
Position: Tensor Networks are a Valuable Asset for Green AI
Eva Memmel, Clara Menzen, Jetze Schuurmans et al.
Position: The Causal Revolution Needs Scientific Pragmatism
Joshua Loftus
Position: The No Free Lunch Theorem, Kolmogorov Complexity, and the Role of Inductive Biases in Machine Learning
Micah Goldblum, Marc Finzi, Keefer Rowan et al.
Position: The Platonic Representation Hypothesis
Minyoung Huh, Brian Cheung, Tongzhou Wang et al.
Position: The Reasonable Person Standard for AI
Sunayana Rane
Position: Topological Deep Learning is the New Frontier for Relational Learning
Theodore Papamarkou, Tolga Birdal, Michael Bronstein et al.
Position: Towards Implicit Prompt For Text-To-Image Models
Yue Yang, Yuqi Lin, Hong Liu et al.
Position: Towards Unified Alignment Between Agents, Humans, and Environment
Zonghan Yang, an liu, Zijun Liu et al.
Position: TrustLLM: Trustworthiness in Large Language Models
Yue Huang, Lichao Sun, Haoran Wang et al.
Position: Understanding LLMs Requires More Than Statistical Generalization
Patrik Reizinger, Szilvia Ujváry, Anna Mészáros et al.
Position: Video as the New Language for Real-World Decision Making
Sherry Yang, Jacob C Walker, Jack Parker-Holder et al.
Position: What Can Large Language Models Tell Us about Time Series Analysis
Ming Jin, Yi-Fan Zhang, Wei Chen et al.
Position: What makes an image realistic?
Lucas Theis
Position: Why Tabular Foundation Models Should Be a Research Priority
Boris van Breugel, M van der Schaar
Position: Why We Must Rethink Empirical Research in Machine Learning
Moritz Herrmann, F. Julian D. Lange, Katharina Eggensperger et al.
Position: Will we run out of data? Limits of LLM scaling based on human-generated data
Pablo Villalobos, Anson Ho, Jaime Sevilla et al.
Positive and Unlabeled Learning with Controlled Probability Boundary Fence
Changchun Li, Yuanchao Dai, Lei Feng et al.
Positive Concave Deep Equilibrium Models
Mateusz Gabor, Tomasz Piotrowski, Renato L. G. Cavalcante
Positive-Unlabeled Learning by Latent Group-Aware Meta Disambiguation
Lin Long, Haobo Wang, Zhijie Jiang et al.
Posterior Distillation Sampling
Juil Koo, Chanho Park, Minhyuk Sung
Posterior Sampling-Based Bayesian Optimization with Tighter Bayesian Regret Bounds
Shion Takeno, Yu Inatsu, Masayuki Karasuyama et al.
Posterior Sampling Based on Gradient Flows of the MMD with Negative Distance Kernel
Paul Hagemann, Johannes Hertrich, Fabian Altekrüger et al.
PosterLlama: Bridging Design Ability of Langauge Model to Content-Aware Layout Generation
Jaejung Seol, Seojun Kim, Jaejun Yoo
Post-hoc bias scoring is optimal for fair classification
Wenlong Chen, Yegor Klochkov, Yang Liu
Post-hoc Part-Prototype Networks
Andong Tan, Fengtao ZHOU, Hao Chen
Post-training Quantization with Progressive Calibration and Activation Relaxing for Text-to-Image Diffusion Models
Siao Tang, Xin Wang, Hong Chen et al.
PostureHMR: Posture Transformation for 3D Human Mesh Recovery
Yu-Pei Song, Xiao WU, Zhaoquan Yuan et al.
Potential Based Diffusion Motion Planning
Yunhao Luo, Chen Sun, Josh Tenenbaum et al.
Powerful and Flexible: Personalized Text-to-Image Generation via Reinforcement Learning
Fanyue Wei, Wei Zeng, Zhenyang Li et al.
Power Variable Projection for Initialization-Free Large-Scale Bundle Adjustment
Simon Weber, Je Hyeong Hong, Daniel Cremers
PPAD: Iterative Interactions of Prediction and Planning for End-to-end Autonomous Driving
Zhili Chen, Maosheng Ye, Shuangjie Xu et al.
PPEA-Depth: Progressive Parameter-Efficient Adaptation for Self-Supervised Monocular Depth Estimation
Yue-Jiang Dong, Yuan-Chen Guo, Ying-Tian Liu et al.
PPFLOW: Target-Aware Peptide Design with Torsional Flow Matching
Haitao Lin, Odin Zhang, Huifeng Zhao et al.
PPIDSG: A Privacy-Preserving Image Distribution Sharing Scheme with GAN in Federated Learning
Yuting Ma, Yuanzhi Yao, Xiaohua Xu
PQ-SAM: Post-training Quantization for Segment Anything Model
Xiaoyu Liu, Xin Ding, Lei Yu et al.
PracticalDG: Perturbation Distillation on Vision-Language Models for Hybrid Domain Generalization
Zining Chen, Weiqiu Wang, Zhicheng Zhao et al.