Prépublication
· 2026 arXiv
EN
As executable environments for language agents scale, generating and verifying their rollouts becomes increasingly expensive. Under finite rollout budgets, this raises an important question: can data management at the environment level make agentic reinforceme...
Sihan Yang, Weichen Bai et al.
#cs.LG
Prépublication
· 2026 arXiv
EN
The Dark Energy Spectroscopic Instrument (DESI) measures baryon acoustic oscillations (BAO) in the Lyman-$α$ (Lyman-alpha) forest and provides a robust probe of the expansion history in the matter-dominated era. Yet, non-linear structure formation broadens and...
Boryana Hadzhiyska, Roger de Belsunce
#astro-ph.CO
Prépublication
· 2026 arXiv
EN
Existing sequential recommenders usually allocate a fixed computational budget to every item in a user's interaction history, regardless of the item's contribution to the final prediction. We challenge this de facto design with two diagnostic findings. (1) Non...
Zhanshuo Cao, Jiakai Tang et al.
#cs.IR
Prépublication
· 2026 arXiv
EN
Existing world models typically perceive a scene through current visual frame or a narrow history window. However, these observations may not reveal the physics properties that determine transition dynamics, such as an object's mass distribution, joint damping...
Yunhao Luo, Wentao He et al.
#cs.RO
Prépublication
· 2026 arXiv
EN
Speculative decoding has become a mainstream technique for accelerating large language model (LLM) inference by using a lightweight draft model to generate candidate tokens that are subsequently verified by the target model. However, agentic workloads introduc...
Jiaming Xu, Hanzhen Wang et al.
#cs.CL
Prépublication
· 2026 arXiv
EN
Scalar-induced gravitational waves (SIGWs) provide a powerful probe of the expansion history of the universe prior to the Big Bang. Indeed, the production of such gravity waves depends on the evolution of first-order scalar perturbations within the early unive...
Keith R. Dienes, Fazlollah Hajkarim et al.
#astro-ph.CO
Prépublication
· 2026 arXiv
EN
Automated research with LLM agents has shown promising results in various domains. Through iterative refinement and scored verifiers, LLM agents are capable of discovering new ideas. There are different ways to scale automated research: let one agent iterate f...
Shangyin Tan, Ben Zhou et al.
#cs.AI
Prépublication
· 2026 arXiv
EN
The cosmic reheating is an important epoch in the very early Universe, and has significant impacts on the primordial black hole (PBH) abundance and the scalar-induced gravitational wave (SIGW) spectrum. The relevant energy scale and the constituents of cosmic...
Qi-Lin Yang, Shi-Jie Wang et al.
#astro-ph.CO
Prépublication
· 2026 arXiv
EN
A central challenge in embodied recursive self-improvement is enabling agents to convert interaction history into capabilities that persist beyond one world and transfer to later tasks. A saved memory or successful final action does not by itself establish tha...
Jingwei Song, Zhisheng Chen et al.
#cs.RO
Prépublication
· 2026 arXiv
EN
Streaming Video Large Language Models (VLMs) enable continuous video understanding, yet existing benchmarks focus on low-dynamic scenarios. Under bounded context budgets, models must balance temporal history, spatial resolution, and temporal granularity; spars...
Yuxuan Hu, Weikang Shi et al.
#cs.CV
Prépublication
· 2026 arXiv
EN
Supernovae (SNe) are excellent probes of the physical, chemical, and cosmological context of galaxies across the history of the Universe. The James Webb Space Telescope (JWST ) has a truly unique combination of wavelength, sensitivity, and resolution, providin...
Justin Pierel, David Coulter et al.
#astro-ph.CO
Prépublication
· 2026 arXiv
EN
Real-time robot control demands enough visual history to infer motion and task progress, but processing that history can delay action. We present Long-WAM, a model-system framework for scaling the context of causal world-action models under real-time control c...
Wei Huang, Bohan Zhang et al.
#cs.RO