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- $H$-Consistency Guarantees for Regression
- $S^2$IP-LLM_ Semantic Space Informed Prompt Learning with LLM for Time Series Forecasting
- $_bfΦ__textrmFlow$_ Differentiable Simulations for PyTorch, TensorFlow and Jax
- $_mathttVITS$ _ Variational Inference Thompson Sampling for contextual bandits
- $_rm E(3)$-Equivariant Actor-Critic Methods for Cooperative Multi-Agent Reinforcement Learning
- $_textttMoE-RBench$_ Towards Building Reliable Language Models with Sparse Mixture-of-Experts
- $f$-Divergence Based Classification_ Beyond the Use of Cross-Entropy
- 3D Geometric Shape Assembly via Efficient Point Cloud Matching
- 3D-VLA_ A 3D Vision-Language-Action Generative World Model
- A Bayesian Approach to Online Planning
- A Bias-Variance-Covariance Decomposition of Kernel Scores for Generative Models
- A Circuit Domain Generalization Framework for Efficient Logic Synthesis in Chip Design
- A Closer Look at the Limitations of Instruction Tuning
- A Computational Framework for Solving Wasserstein Lagrangian Flows
- A Contextual Combinatorial Bandit Approach to Negotiation
- A Dense Reward View on Aligning Text-to-Image Diffusion with Preference
- A Differentiable Partially Observable Generalized Linear Model with Forward-Backward Message Passing
- A Diffusion Model Framework for Unsupervised Neural Combinatorial Optimization
- A Distributional Analogue to the Successor Representation
- A Doubly Recursive Stochastic Compositional Gradient Descent Method for Federated Multi-Level Compositional Optimization
- A Dual-module Framework for Counterfactual Estimation over Time
- A Dynamic Algorithm for Weighted Submodular Cover Problem
- A Dynamical Model of Neural Scaling Laws
- A Federated Stochastic Multi-level Compositional Minimax Algorithm for Deep AUC Maximization
- A Field Guide for Pacing Budget and ROS Constraints
- A Fine-grained Analysis of Fitted Q-evaluation_ Beyond Parametric Models
- A Fixed-Point Approach for Causal Generative Modeling
- A Fresh Take on Stale Embeddings_ Improving Dense Retriever Training with Corrector Networks
- A General Framework for Learning from Weak Supervision
- A General Framework for Sequential Decision-Making under Adaptivity Constraints
- A General Online Algorithm for Optimizing Complex Performance Metrics
- A General Theory for Softmax Gating Multinomial Logistic Mixture of Experts
- A Generative Approach for Treatment Effect Estimation under Collider Bias_ From an Out-of-Distribution Perspective
- A Geometric Decomposition of Finite Games_ Convergence vs. Recurrence under Exponential Weights
- A Geometric Explanation of the Likelihood OOD Detection Paradox
- A Global Geometric Analysis of Maximal Coding Rate Reduction
- A Graph is Worth $K$ Words_ Euclideanizing Graph using Pure Transformer
- A Hierarchical Adaptive Multi-Task Reinforcement Learning Framework for Multiplier Circuit Design
- A Human-Inspired Reading Agent with Gist Memory of Very Long Contexts
- A Language Model’s Guide Through Latent Space
- A Linear Time and Space Local Point Cloud Geometry Encoder via Vectorized Kernel Mixture (VecKM)
- A Mechanistic Understanding of Alignment Algorithms_ A Case Study on DPO and Toxicity
- A Minimaximalist Approach to Reinforcement Learning from Human Feedback
- A Multimodal Automated Interpretability Agent
- A Near-Linear Time Approximation Algorithm for Beyond-Worst-Case Graph Clustering
- A Nearly Optimal Single Loop Algorithm for Stochastic Bilevel Optimization under Unbounded Smoothness
- A Neural-Guided Dynamic Symbolic Network for Exploring Mathematical Expressions from Data
- A Neural-Preconditioned Poisson Solver for Mixed Dirichlet and Neumann Boundary Conditions
- A New Branch-and-Bound Pruning Framework for $_ell_0$-Regularized Problems
- A New Computationally Efficient Algorithm to solve Feature Selection for Functional Data Classification in High-dimensional Spaces