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Typed-decision models score options that the caller supplies at request time, so their accuracy depends on label wording that the model's developer does not control. We compare two releases of a 307M-parameter multilingu…
Neural networks are likely to be among the most consequential artefacts in human history. As these systems become more capable and autonomous, their potential to cause societal harm also grows, making AI safety one of th…
In this work, we evaluate a simple inference-time scaling approach based on textit{turn-level best-of-N sampling} (method) for large language model (LLM) agents on complex, long-horizon tasks. We instantiate this using a…
Automated identification of individual animals is moving from small curated studies toward shared benchmarks and reusable foundation models. This progress is useful, but current evaluation leaves the evidence behind a ma…
Self-Driving Chemical Laboratories (SDCLs) are moving chemical experimentation toward embodied automation, where machines must perceive laboratory scenes, reason about experimental states, and act under physical, procedu…
AI agents are playing an increasingly important role in physics research. However, existing physics benchmarks only evaluate fixed questions, isolated sub-tasks, or paper reproduction with given solutions, and rarely che…
Humanoid robots have the potential to automate a wide range of physical tasks. Progress toward generalist humanoid autonomy, however, remains constrained by a data bottleneck: mapping pixels and free-form language to low…
Knowing that a pedestrian is occluded is useful to a robot even when the detector cannot recover the hidden pixels, but occlusion estimators are normally trained on occlusion annotations that deployment settings rarely h…
Automation is often justified as relief from dull, dirty, and dangerous work. I examine how these conditions relate to occupational AI exposure using 21 O*NET items across 754 US occupations. Higher exposure is associate…
Error correcting codes are a fundamental component of communication systems, enabling reliable data transmission over noisy channels. Recently, neural decoders have demonstrated notable performance gains over classical i…
Radyoterapide makine öğrenimi modelleri, cevapları bilinen vakalar üzerinde test edilerek devreye alınır; bu, test vakalarının eğitim verileriyle paylaştığı bir kısayolu ortaya çıkarmayabilir. Sınır dil modellerinin yakı…
Tıbbi fizikçiler bir reçeteyi verilen doza dönüştürür ve birbirlerinin hesaplamalarını kontrol ederler çünkü ışın kalibrasyonunda veya monitör ünitesi (MU) hesaplamasındaki bir hata, onunla tedavi edilen her hastayı etki…
Efficient preconditioning plays an important role in large-scale first-order optimization. In this paper, we propose an adaptive accelerated optimistic dual averaging ($text{A}^2$ODA) method for unconstrained convex opti…
Teleoperation remains the default way to collect robot demonstrations, but every episode costs robot and operator time, and every new task starts from scratch. We ask whether a coding agent can take over the teleoperator…
In LLM-based recommendation, memory acts as a user-level agent in a memory-augmented backbone. Yet users and items remain asymmetric: only the user is given a structured profile; it enters a bandwidth-limited reranker pr…