Optimization

Automated Proof of Polynomial Inequalities via Reinforcement Learning CVPR 2025 Automated Superscalar Processor Design by Learning Data Dependencies IJCAI 2025 Automatic Differentiation of Optimization Algorithms with Time-Varying Updates ICML 2025 Automatic Transmission for LLM Tiers: Optimizing Cost and Accuracy in Large Language Models ACL 2025 AutoMixAlign: Adaptive Data Mixing for Multi-Task Preference Optimization in LLMs ACL 2025 AutoMixer: Checkpoint Artifacts as Automatic Data Mixers ACL 2025 Auto-nnU-Net: Towards Automated Medical Image Segmentation AutoML 2025 Autoregressive Pretraining with Mamba in Vision ICLR 2025 AutoStep: Locally adaptive involutive MCMC ICML 2025 AutoUAD: Hyper-parameter Optimization for Unsupervised Anomaly Detection ICLR 2025 Auto-Weighted Group Relative Preference Optimization for Multi-Objective Text Generation Tasks EMNLP 2025 A Versatile Influence Function for Data Attribution with Non-Decomposable Loss ICML 2025 Avoidance Decoding for Diverse Multi-Branch Story Generation EMNLP 2025 Avoiding Undesired Future with Sequential Decisions IJCAI 2025 Ax: A Platform for Adaptive Experimentation AutoML 2025 AxlePro: Momentum-Accelerated Batched Training of Kernel Machines AISTATS 2025 B2Opt: Learning to Optimize Black-box Optimization with Little Budget AAAI 2025 B4: A Black-Box Scrubbing Attack on LLM Watermarks NAACL 2025 Backdoor Attacks on Neural Networks via One-Bit Flip ICCV 2025 Backdoor Mitigation by Distance-Driven Detoxification ICCV 2025 Backdoor Token Unlearning: Exposing and Defending Backdoors in Pretrained Language Models AAAI 2025 Back on Track: Bundle Adjustment for Dynamic Scene Reconstruction ICCV 2025 BackSlash: Rate Constrained Optimized Training of Large Language Models ICML 2025 Bagged Regularized k-Distances for Anomaly Detection JMLR 2025 Balanced Adaptive Subspace Collaboration for Mixed Pareto-Lexicographic Multi-Objective Problems with Priority Levels AAAI 2025