Prépublication
· 2026 arXiv
EN
AI learning tools are rapidly entering classrooms, but evidence about whether they help students learn is mixed and rests mostly on test scores. Comparatively less research addresses whether the use of AI changes students' live learning behaviors in class. Her...
Dan J. Wang, Neelam Modi Jain et al.
#cs.HC
Prépublication
· 2026 arXiv
EN
We present FoldBack, a self-correcting masked generative policy for long-horizon garment folding. Existing long-trajectory policies may continue after a missed or slipped grasp even when the garment has not reached the intended configuration. We structure Fold...
Lipeng Zhuang, Shiyu Fan et al.
#cs.RO
Prépublication
· 2026 arXiv
EN
Multi-teacher on-policy distillation (MOPD) is used in two settings. In common-domain composition, several teachers score each student rollout from one prompt domain and their signals form a single target; in routed-domain distillation, prompts from different...
Hejian Sang, Zhengze Zhou et al.
#cs.LG
Prépublication
· 2026 arXiv
EN
Hallucinated information can propagate through multi-stage LLM systems and become part of the context for subsequent reasoning. Existing studies of post-hallucination reasoning (PHR) mainly characterize changes in final outcomes and aggregate reasoning dynamic...
Linghao Meng, Feng He et al.
#cs.CL
Prépublication
· 2026 arXiv
EN
Reinforcement Learning (RL) from outcome rewards suffers from sparse supervision, particularly on difficult, long-horizon tasks where successful trajectories are rare and costly to generate. On-Policy Distillation (OPD) offers an attractive alternative by prov...
Randy Ardywibowo, Arnav Dalal et al.
#cs.LG
Prépublication
· 2026 arXiv
EN
Much knowledge work produces new deliverables from files a workspace already holds, and LLM agents are beginning to take such work over. Through direct corpus interaction, an agent can search and read any of those files from a terminal with no indexing, and pr...
Jinheon Baek, Soyeong Jeong et al.
#cs.AI
Prépublication
· 2026 arXiv
EN
Flow policies capture rich and diverse action distributions, and fine-tuning them with off-policy RL to improve beyond the demonstrations has drawn growing interest. However, fine-tuning a flow policy against a learned value function is not trivial, because th...
Yonghoon Dong, Minsung Yoon et al.
#cs.LG
Prépublication
· 2026 arXiv
EN
Rapid and accurate prediction of urban wind and temperature fields is important for urban microclimate design and climate adaptation. Large-eddy simulation (LES) effectively resolves these instantaneous fields, but its application is limited in iterative desig...
Peng Liu, Shaoxiang Qin et al.
#physics.flu-dyn
Prépublication
· 2026 arXiv
EN
Transient supplies of nutrients to the surface ocean, both natural and artificial, stimulate blooms of phytoplankton and the formation of organic matter, driving air-sea gradients and uptake of CO$_2$. However, quantifying the associated carbon budget remains...
Stefano Campagnola, Stephanie Dutkiewicz et al.
#physics.ao-ph
Prépublication
· 2026 arXiv
EN
We constrain oscillatory features in the primordial power spectrum using the public DESI DR1 galaxy and quasar clustering data. Our analysis is based on a custom pipeline for the redshift-space power spectrum and bispectrum of the six main DESI DR1 tracers, mo...
Shi-Fan Chen, Anton Chudaykin et al.
#astro-ph.CO
Prépublication
· 2026 arXiv
EN
We present an analysis of two planetary microlensing events, KMT-2021-BLG-0247 and MOA-2023-BLG-169, both of which exhibit high magnifications and low planet--host mass ratios, but with markedly different levels of parameter constraint. For KMT-2021-BLG-0247,...
Kansuke Nunota, Andrew Gould et al.
#astro-ph.EP
Prépublication
· 2026 arXiv
EN
We present the angular BAO analysis using DESI DR1 data as a complementary approach to DESI's primary 3D BAO analysis. We perform the analysis using the two-point angular correlation function $w(θ)$ in tomographic redshift shells of $δz = 0.02, 0.05$, spanning...
Anya Paopiamsap, Juan Mena-Fernández et al.
#astro-ph.CO