RISE: Adaptive Imagination for World Action Models
Researchers present RISE, an adaptive framework for world action models that dynamically decides when to stop imagination rollouts based on…
Researchers present RISE, an adaptive framework for world action models that dynamically decides when to stop imagination rollouts based on…
Researchers present ReWorld, an interactive world model that addresses the competing demands of real-time control and long-horizon memory through architectural…
Researchers introduce GameXpert-Bench, an evaluation framework with three benchmark tracks assessing coding agents across the game-development lifecycle: initial creation (GameGen,…
Researchers introduce ARC (Advantage Regularization via Conditioning), a training methodology addressing fairness issues when comparing diverse interaction behaviors in reinforcement…
Researchers present AutoResearch, a two-stage autonomous research system combining idea generation with idea execution. In the generation phase, the system…
Researchers present R2-OPD, a method addressing misalignment between teacher-derived rewards and actual reasoning progress in on-policy distillation for language models.…
Researchers introduce LongWoF-Bench, a benchmark of 778 machine-verifiable tasks spanning code generation, agent synthesis, mathematical reasoning, and rule-following, alongside EvoMap,…
Researchers developed AstroPT, a transformer trained on millions of galaxy images, as a controlled testbed for interpretability research. By probing…
Researchers developed RIBOSPAN, a 1.61-billion-parameter RNA foundation model using dense bidirectional self-attention, single-nucleotide tokenization, and attention-isolated sequence packing to process…
Researchers introduce TPO, a face-free presentation-attack-detection dataset built from recordings of vegetables subjected to print, replay, and recapture processes. Using…
Researchers evaluate a hybrid quantum-inspired Kolmogorov-Arnold network (HQKAN) against a standard multilayer perceptron for arrhythmia classification using federated learning on…
Researchers introduce WorldToken, a robotic imitation learning approach that organizes multimodal inputs through a time-first architecture, fusing multiview images, proprioception,…