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1. Large Generative Graph Models

2. 3D-GRAND: Towards Better Grounding and Less Hallucination for 3D-LLMs

3. Compositional Curvature Bounds for Deep Neural Networks

4. The Expanding Scope of the Stability Gap: Unveiling its Presence in Joint Incremental Learning of Homogeneous Tasks

5. LLavaGuard: VLM-based Safeguards for Vision Dataset Curation and Safety Assessment

6. Adapting Physics-Informed Neural Networks To Optimize ODEs in Mosquito Population Dynamics

7. SUMIE: A Synthetic Benchmark for Incremental Entity Summarization

8. Provably Better Explanations with Optimized Aggregation of Feature Attributions

9. Optimizing Time Series Forecasting Architectures: A Hierarchical Neural Architecture Search Approach

10. Linearization Turns Neural Operators into Function-Valued Gaussian Processes

11. Massively Multiagent Minigames for Training Generalist Agents

12. Progressive Entropic Optimal Transport Solvers

13. Pretraining Decision Transformers with Reward Prediction for In-Context Multi-task Structured Bandit Learning

14. Hints-In-Browser: Benchmarking Language Models for Programming Feedback Generation

15. Online Frequency Scheduling by Learning Parallel Actions

16. A Tensor Decomposition Perspective on Second-order RNNs

17. Gradient Descent on Logistic Regression with Non-Separable Data and Large Step Sizes

18. TimeSieve: Extracting Temporal Dynamics through Information Bottlenecks

19. Efficient 3D Shape Generation via Diffusion Mamba with Bidirectional SSMs

20. Optimizing Automatic Differentiation with Deep Reinforcement Learning


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