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- #InsTag_ Instruction Tagging for Analyzing Supervised Fine-tuning of Large Language Models
- $_alpha$TC-VAE_ On the relationship between Disentanglement and Diversity
- $_infty$-Diff_ Infinite Resolution Diffusion with Subsampled Mollified States
- $_mathbb{D}^2$ Pruning_ Message Passing for Balancing Diversity & Difficulty in Data Pruning
- $_mathcal{B}$-Coder_ Value-Based Deep Reinforcement Learning for Program Synthesis
- $_pi$2vec_ Policy Representation with Successor Features
- $_texttt{NAISR}$_ A 3D Neural Additive Model for Interpretable Shape Representation
- $t^3$-Variational Autoencoder_ Learning Heavy-tailed Data with Student's t and Power Divergence
- 3D Feature Prediction for Masked-AutoEncoder-Based Point Cloud Pretraining
- 3D Reconstruction with Generalizable Neural Fields using Scene Priors
- 3D-Aware Hypothesis & Verification for Generalizable Relative Object Pose Estimation
- A 2-Dimensional State Space Layer for Spatial Inductive Bias
- A Benchmark Study on Calibration
- A Benchmark for Learning to Translate a New Language from One Grammar Book
- A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning
- A Branching Decoder for Set Generation
- A Characterization Theorem for Equivariant Networks with Point-wise Activations
- A Cognitive Model for Learning Abstract Relational Structures from Memory-based Decision-Making Tasks
- A Data-Driven Measure of Relative Uncertainty for Misclassification Detection
- A Differentially Private Clustering Algorithm for Well-Clustered Graphs
- A Discretization Framework for Robust Contextual Stochastic Optimization
- A Dynamical View of the Question of Why
- A Fast and Provable Algorithm for Sparse Phase Retrieval
- A Flexible Generative Model for Heterogeneous Tabular EHR with Missing Modality
- A Foundation Model for Error Correction Codes
- A Framework for Inference Inspired by Human Memory Mechanisms
- A General Framework for User-Guided Bayesian Optimization
- A Good Learner can Teach Better_ Teacher-Student Collaborative Knowledge Distillation
- A Graph is Worth 1-bit Spikes_ When Graph Contrastive Learning Meets Spiking Neural Networks
- A Hard-to-Beat Baseline for Training-free CLIP-based Adaptation
- A Hierarchical Bayesian Model for Few-Shot Meta Learning
- A Lie Group Approach to Riemannian Batch Normalization
- A Lightweight Method for Tackling Unknown Participation Statistics in Federated Averaging
- A Linear Algebraic Framework for Counterfactual Generation
- A Multi-Level Framework for Accelerating Training Transformer Models
- A Mutual Information Perspective on Federated Contrastive Learning
- A Neural Framework for Generalized Causal Sensitivity Analysis
- A Newborn Embodied Turing Test for Comparing Object Segmentation Across Animals and Machines
- A Paradigm Shift in Machine Translation_ Boosting Translation Performance of Large Language Models
- A Plug-and-Play Image Registration Network
- A Poincaré Inequality and Consistency Results for Signal Sampling on Large Graphs
- A Policy Gradient Method for Confounded POMDPs
- A Precise Characterization of SGD Stability Using Loss Surface Geometry
- A Primal-Dual Approach to Solving Variational Inequalities with General Constraints
- A Probabilistic Framework for Modular Continual Learning
- A Progressive Training Framework for Spiking Neural Networks with Learnable Multi-hierarchical Model
- A Quadratic Synchronization Rule for Distributed Deep Learning
- A ROBUST DIFFERENTIAL NEURAL ODE OPTIMIZER
- A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesis
- A Recipe for Improved Certifiable Robustness