Spotlight Papers
1,421 papers found • Page 12 of 29
Personalized Decision Modeling: Utility Optimization or Textualized-Symbolic Reasoning
Yibo Zhao, Yang Zhao, Hongru Du et al.
PhySpec: Physically Consistent Spectral Reconstruction via Orthogonal Subspace Decomposition and Self-Supervised Meta-Auxiliary Learning
Xingxing Yang, Jie Chen, Zaifeng Yang
PhysX-3D: Physical-Grounded 3D Asset Generation
Ziang Cao, Zhaoxi Chen, Liang Pan et al.
PiKE: Adaptive Data Mixing for Large-Scale Multi-Task Learning Under Low Gradient Conflicts
Zeman Li, Yuan Deng, Peilin Zhong et al.
Plasticity as the Mirror of Empowerment
David Abel, Michael Bowling, Andre Barreto et al.
PoE-World: Compositional World Modeling with Products of Programmatic Experts
Top Piriyakulkij, Yichao Liang, Hao Tang et al.
PokéChamp: an Expert-level Minimax Language Agent
Seth Karten, Andy Nguyen, Chi Jin
Policy Compatible Skill Incremental Learning via Lazy Learning Interface
Daehee Lee, Dongsu Lee, TaeYoon Kwack et al.
Policy-labeled Preference Learning: Is Preference Enough for RLHF?
Taehyun Cho, Seokhun Ju, Seungyub Han et al.
Policy Regularization on Globally Accessible States in Cross-Dynamics Reinforcement Learning
Zhenghai Xue, Lang Feng, Jiacheng Xu et al.
Polyline Path Masked Attention for Vision Transformer
Zhongchen Zhao, Chaodong Xiao, Hui LIN et al.
Position: Algebra Unveils Deep Learning - An Invitation to Neuroalgebraic Geometry
Giovanni Luca Marchetti, Vahid Shahverdi, Stefano Mereta et al.
Position: Causal Machine Learning Requires Rigorous Synthetic Experiments for Broader Adoption
Audrey Poinsot, Panayiotis Panayiotou, Alessandro Leite et al.
Position: Deep Learning is Not So Mysterious or Different
Andrew Wilson
Position: Don't Use the CLT in LLM Evals With Fewer Than a Few Hundred Datapoints
Sam Bowyer, Laurence Aitchison, Desi Ivanova
Position: Formal Mathematical Reasoning—A New Frontier in AI
Kaiyu Yang, Gabriel Poesia, Jingxuan He et al.
Position: General Intelligence Requires Reward-based Pretraining
Seungwook Han, Jyothish Pari, Samuel Gershman et al.
Position: Human Baselines in Model Evaluations Need Rigor and Transparency (With Recommendations & Reporting Checklist)
Kevin Wei, Patricia Paskov, Sunishchal Dev et al.
Position: In-House Evaluation Is Not Enough. Towards Robust Third-Party Evaluation and Flaw Disclosure for General-Purpose AI
Shayne Longpre, Kevin Klyman, Ruth Elisabeth Appel et al.
Position: Language model developers should report train-test overlap
Andy Zhang, Kevin Klyman, Yifan Mai et al.
Position: Rethinking LLM Bias Probing Using Lessons from the Social Sciences
Kirsten Morehouse, Siddharth Swaroop, Weiwei Pan
Position: The Categorization of Race in ML is a Flawed Premise
Miriam Doh, Benedikt Höltgen, Piera Riccio et al.
Position: We Can’t Understand AI Using our Existing Vocabulary
John Hewitt, Robert Geirhos, Been Kim
Position: We Need An Algorithmic Understanding of Generative AI
Oliver Eberle, Thomas McGee, Hamza Giaffar et al.
Practical do-Shapley Explanations with Estimand-Agnostic Causal Inference
Álvaro Parafita, Tomas Garriga, Axel Brando et al.
Precise Asymptotics and Refined Regret of Variance-Aware UCB
Yingying Fan, Yuxuan Han, Jinchi Lv et al.
Preconditioned Langevin Dynamics with Score-based Generative Models for Infinite-Dimensional Linear Bayesian Inverse Problems
Lorenzo Baldassari, Josselin Garnier, Knut Solna et al.
Predictable Scale (Part II) --- Farseer: A Refined Scaling Law in LLMs
Houyi Li, Wenzhen Zheng, Qiufeng Wang et al.
Prediction models that learn to avoid missing values
Lena Stempfle, Anton Matsson, Newton Mwai et al.
Predictive Preference Learning from Human Interventions
Haoyuan Cai, Zhenghao (Mark) Peng, Bolei Zhou
Primal-Dual Neural Algorithmic Reasoning
Yu He, Ellen Vitercik
Principled Data Augmentation for Learning to Solve Quadratic Programming Problems
Chendi Qian, Christopher Morris
Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning
Jaehun Jung, Seungju Han, Ximing Lu et al.
Privacy amplification by random allocation
Moshe Shenfeld, Vitaly Feldman
Privacy Amplification by Structured Subsampling for Deep Differentially Private Time Series Forecasting
Jan Schuchardt, Mina Dalirrooyfard, Jed Guzelkabaagac et al.
Private Hyperparameter Tuning with Ex-Post Guarantee
Badih Ghazi, Pritish Kamath, Alexander Knop et al.
Private Set Union with Multiple Contributions
Travis Dick, Haim Kaplan, Alex Kulesza et al.
Probabilistic Factorial Experimental Design for Combinatorial Interventions
Divya Shyamal, Jiaqi Zhang, Caroline Uhler
Probing Neural Combinatorial Optimization Models
Zhiqin Zhang, Yining Ma, Zhiguang Cao et al.
Procurement Auctions via Approximately Optimal Submodular Optimization
Yuan Deng, Amin Karbasi, Vahab Mirrokni et al.
Product Distribution Learning with Imperfect Advice
Arnab Bhattacharyya, XianJun, Davin Choo, Philips George John et al.
Progressive Inference-Time Annealing of Diffusion Models for Sampling from Boltzmann Densities
Tara Akhound-Sadegh, Jungyoon Lee, Joey Bose et al.
Projection-based Lyapunov method for fully heterogeneous weakly-coupled MDPs
Xiangcheng Zhang, Yige Hong, Weina Wang
Projective Equivariant Networks via Second-order Fundamental Differential Invariants
Yikang Li, Yeqing Qiu, Yuxuan Chen et al.
Protein Design with Dynamic Protein Vocabulary
Nuowei Liu, Jiahao Kuang, Yanting Liu et al.
ProtInvTree: Deliberate Protein Inverse Folding with Reward-guided Tree Search
Mengdi Liu, Xiaoxue Cheng, Zhangyang Gao et al.
Provable Benefits of Unsupervised Pre-training and Transfer Learning via Single-Index Models
Taj Jones-McCormick, Aukosh Jagannath, Subhabrata Sen
Provable Gradient Editing of Deep Neural Networks
Zhe Tao, Aditya V Thakur
Provably Efficient RL under Episode-Wise Safety in Constrained MDPs with Linear Function Approximation
Toshinori Kitamura, Arnob Ghosh, Tadashi Kozuno et al.
Proxy-SPEX: Sample-Efficient Interpretability via Sparse Feature Interactions in LLMs
Landon Butler, Abhineet Agarwal, Justin Kang et al.