Prépublication
· 2026 arXiv
EN
Venus and Mars are unique laboratories for understanding the evolution and diversity of terrestrial planets. Despite their broadly similar rocky compositions, their atmospheres, climates, and surface environments have evolved into dramatically different states...
Hideo Sagawa, Arianna Piccialli et al.
#astro-ph.IM
Prépublication
· 2026 arXiv
EN
Mutual coupling between elements of low-frequency arrays is a leading systematic for 21 cm cosmology, leaking bright foregrounds into otherwise clean regions of the power spectrum. Many mitigation models describe coupling as a linear combination of uncoupled s...
Vincent MacKay, Robert Pascua et al.
#astro-ph.IM
Prépublication
· 2026 arXiv
EN
Reverberation mapping of active galactic nuclei uses the time taken for variability to travel through the system as a measure of system size, with this size being used to inform estimates of the mass of the central black hole, a technique that has graduated to...
Hugh McDougall, Tamara M. Davis et al.
#astro-ph.GA
Prépublication
· 2026 arXiv
EN
The initial chemical composition of planets, primitive bodies in our solar system, and exoplanets is ultimately set by their nascent protoplanetary disks. Yet observing key carbon-, oxygen-, and nitrogen-bearing molecules (as well as rarer but important sulphu...
Catherine Walsh, Maria Drozdovskaya et al.
#astro-ph.IM
Prépublication
· 2026 arXiv
EN
Simulating chaotic planetary system evolution requires resolving small time-scales due to close encounters, scattering, collisions, and more. Simulations typically assign fixed timesteps to all particles, however, which is inefficient and wastes compute resour...
David M. Hernandez, Tenri Jinno et al.
#astro-ph.EP
Prépublication
· 2026 arXiv
EN
Recent advances in robot learning have driven rapid progress in humanoid control, enabling increasingly agile behaviors in the real world. However, humanoid control networks are typically obtained through conventional training procedures, while comparatively l...
Huixuan Cheng, Bike Zhang et al.
#cs.RO
Prépublication
· 2026 arXiv
EN
Scaling up transformers has produced models with broad capabilities, deployed across heterogeneous hardware and fluctuating workloads. Yet, model families offer only a few fixed sizes (e.g., S, B, L), forcing users to commit to a model based on hardware and la...
Walter Simoncini, Dheeraj Varghese et al.
#cs.LG
Prépublication
· 2026 arXiv
EN
An agentic market is a decentralized serving-time market where AI agents bid to claim each user prompt. An agent's bid is based on its expected value for the prompt, which is the expectation of the reward for its response minus its inference costs. First-price...
Shubhendu Trivedi, Jacob Eisenstein et al.
#cs.GT
Prépublication
· 2026 arXiv
EN
We introduce Continuum Attention (CA), a causal Transformer attention operator that replaces discrete key and value lookup with integration over a continuous, piecewise linear memory curve. Each query induces an exponential relevance density along the curve. I...
Afshin Khadangi
#cs.LG
Prépublication
· 2026 arXiv
EN
Post-training binds the competence of an LLM agent to the interface it was trained on. Semantics-preserving perturbations of that interface, such as renaming an action or changing the notation, leave the underlying task unchanged yet make the agent worse at it...
Artin Tajdini, Manpreet Kaur et al.
#cs.LG
Prépublication
· 2026 arXiv
EN
Brazilian Portuguese remains underserved by open-source language models, and the few that are safety-aligned rarely document what did not work or validate comparisons with statistical significance. We present Manacá-1B-Instruct-2, the second-generation post-tr...
Bruno Leonardo Santos Menezes, Carlos Leonardo Souza Cardoso et al.
#cs.CL
Prépublication
· 2026 arXiv
EN
Understanding the social intelligence of large language models (LLMs) is increasingly important for applications involving human-AI interaction and multi-agent environments. Social intelligence comprises two aspects: cognitive intelligence, the ability to infe...
Ali Zamani, Soroush Esfahanian et al.
#cs.CL