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While generative models have enabled training-free reward alignment, current methods typically excel in local explora...
Safety evaluations for language models increasingly depend on judgments about ambiguous natural-language behaviour: w...
Generative reasoning re-rankers achieve strong recommendation accuracy by emitting a chain-of-thought before re-order...
RL with verifiable rewards (RLVR) has emerged as a powerful paradigm for training LMs on tasks with well-defined succ...
In autonomous laboratories, AI agents suggest the next batch of experiments to do. However, planning and executing th...
We present World from Motion, a method for generating freely renderable dynamic 3D Gaussian representations from mono...
This paper studies real-time robust optimal control for uncertain nonlinear systems, where linear time-varying (LTV) ...
Language models deployed in high-stakes roles can potentially favor certain entities, brands, or viewpoints, steering...
Repository-level performance-optimization benchmarks such as GSO, SWE-Perf and SWE-fficiency evaluate coding agents b...
Current work on robot furniture assembly mostly focuses on toy-scale settings or single-arm manipulation. We introduc...
Transformers use the same forward computation stream to both predict the next token and store useful state for future...
When should an AI system's answer be trusted? Formal proof assistants offer certainty but cannot reach most of the pr...