…AI-generated summary Reinforcement learning fine-tuning has become the dominant approach for aligning diffusion models with human preferences. However, assessing images is intrinsically a multi-dimensional task , and multiple evaluation criteria…
…training and evaluating next-generation autonomous driving policies. We additionally show preliminary results indicating that a world-action model (WAM) post-trained from OmniDreams achieves strong performance on the Physical AI Autonomous…
…attention models face challenges with information decay and convergence, which are addressed through a momentum-based approach that improves training efficiency and performance over existing models like Mamba2 and GDN. AI-generated…
…After training, MindZero internalizes model-based reasoning into fast single-pass inference. We evaluate MindZero against baselines across challenging mental reasoning and AI assistance tasks in gridworld and household domains . We found…
…adaptation training and serving by keeping base models resident and moving lightweight adapter revisions, scaling across multiple dimensions including large model architectures, reduced storage requirements, and distributed policy management. AI-generated summary…
…are being updated during training. GradSentry requires no clustering, operates effectively across all poison ratios (1%--90%), and introduces minimal computational overhead (20-50ms per sample for 7B model). Evaluation on four…
…AI-generated summary On-policy distillation offers dense, per-token supervision for training reasoning models; however, it remains unclear under which conditions this signal is beneficial and under which it is detrimental…
…information seeking via search and browser tools achieve superior performance across diverse domains while maintaining data efficiency and robustness. AI-generated summary Most existing large language models (LLMs) are expensive to adapt…
…POISE enables stable and efficient policy optimization for large reasoning models by estimating baselines using internal model signals, reducing computational overhead while maintaining performance comparable to existing methods. AI-generated summary Reinforcement…
…https://github.com/PrimeIntellect-ai/prime-rl/blob/main/src/prime_rl/trainer/models/layers/lora/multi_moe.py . vLLM releases have supported per-expert LoRA loading and serving for MoEs for…