arXiv preprints from January 1, 2026 through September 22, 2026 — 10:29:32 EST
The prevailing post-training paradigm for Large Reasoning Models (LRMs) - Supervised Fine-Tuning (SFT) followed by Reinforcement Learning (RL) - suffers from an intrinsic optimization mismatch: the rigid supervision inherent in SFT induces distributional collapse, thereby exhausting the exploration space necessary for subsequent RL....
Digital service providers often prioritize a frictionless user experience by adopting technologies that simplify access to their services. One widely used mechanism is the Short Message Service (SMS) to deliver links (URLs) that enable single-click access to online services with little to no resistance. However, SMS is inherently...
An emerging class of trajectory optimization methods enforces collision avoidance by jointly optimizing the robot's configuration and a separating hyperplane. However, as linear separators only apply to convex sets, these methods require convex approximations of both the robot and obstacles, which becomes an overly conservative...
Robust local feature representations are essential for spatial intelligence tasks such as robot navigation and augmented reality. Establishing reliable correspondences requires descriptors that provide both high discriminative power and computational efficiency. To address this, we introduce Cross-Layer Independent Deformable...
Person identification in forensic investigations becomes very challenging when common identification means for DNA (i.e., hair strands, soft tissue) are not available. Current methods utilize deep learning methods for face recognition. However, these methods lack effective mechanisms to model cross-domain structural correspondence...
Infrared object detection focuses on identifying and locating objects in complex environments (\eg, dark, snow, and rain) where visible imaging cameras are disabled by poor illumination. However, due to low contrast and weak edge information in infrared images, it is challenging to extract discriminative object features for robust...
Geometric Manin's conjecture for complex Fano varieties describes the structure of the moduli space of curves. We propose a version of this conjecture in characteristic $p$ and describe its connection to the Batyrev--Manin--Peyre--Tschinkel conjecture over global fields. This is a survey paper written for a volume of the Summer...
The superorbital modulations (SMs) observed in wind-fed X-ray binaries remain a puzzling phenomenon in astrophysics. To investigate this behavior observationally, we analyzed the long-term hard X-ray light curve from the Swift/BAT 157-Month Hard X-ray Survey in X-ray binary GX 301-2. Using three timing analysis methods--the...
Statistically, green valley (GV) galaxies exhibit lower molecular gas fractions ($f_{gas}$) and reduced star formation efficiency (SFE) compared to star-forming galaxies. However, it remains unclear whether quenching is primarily driven by one factor or results from a combination of mechanisms in individual GV galaxies. In this study,...
We propose a generic axion--driven cogenesis scenario in which both the baryon asymmetry and dark matter abundance originate from the kinetic misalignment. The framework unifies the Peccei--Quinn (PQ) mechanism with a Type--I seesaw sector, where Hubble--induced masses and higher-dimensional PQ--violating operators drive early--time...
This paper presents an adaptive observer design for semilinear hyperbolic rolling contact ODE-PDE systems with uncertain friction characteristics parameterized by a matrix of unknown coefficients appearing in the nonlinear (and possibly non-smooth) PDE source terms. Under appropriate assumptions of forward completeness and boundary...
In this work, we investigate the performance of polar codes with the assistance of feedback in communication systems. Although it is well known that feedback does not improve the capacity of memoryless channels, we show that the finite length performance of polar codes can be significantly improved as feedback enables genie-aided...
The magneto-optical Kerr effect (MOKE) is a powerful probe of magnetism. Its contact-free optical nature makes it potentially well suitable for measurements under pulsed magnetic fields if various difficulties are overcome. In this paper, we report the establishment of MOKE measurements under bipolar pulsed magnetic fields up to 13.1...
Marked Temporal Point Processes (MTPPs) arise naturally in medical, social, commercial, and financial domains. However, existing Transformer-based methods mostly inject temporal information only via positional encodings, relying on shared or parametric decay structures, which limits their ability to capture heterogeneous and...
The \emph{Tree Augmentation Problem (TAP)} is given a tree $T=(V,E_T)$ and additional set of {\em links} $E$ on $V\times V$, find $F \subseteq E$ such that $T \cup F$ is $2$-edge-connected, and $|F|$ is minimum. The problem is APX-hard \cite{r} even in if links are only between leaves \cite{r}. The best known approximation ratio for...
We present new sub-arcsecond ($\sim$0.3-1 arcsec; $\sim$1--3\,kpc) VLA imaging at 1.4\,GHz and 6\,GHz of 29 optically-selected, [O~{\sc iii}] luminous ($L_{\rm [O III]}$ > 10$^{42.1}$\,erg\,s$^{-1}$), $z<0.2$ quasars drawn from the expanded Quasar Feedback Survey (QFeedS; with $L_\mathrm{1.4\,GHz} =...
High-level synthesis (HLS) is a powerful tool for developing efficient hardware accelerators that rely on specialized memory systems to achieve sufficient on-chip data reuse and off-chip bandwidth utilization. However, even with HLS, designing such systems still requires careful manual tuning, as automatic optimizations provided by...
Data scarcity and unreliable self-reporting -- such as concealment or exaggeration -- pose fundamental challenges to psychiatric intake and assessment. We propose a multi-agent synthesis framework that explicitly models patient deception to generate high-fidelity, publicly releasable synthetic psychiatric intake records. Starting from...
User simulators serve as the critical interactive environment for agent post-training, and an ideal user simulator generalizes across domains and proactively engages in negotiation by challenging or bargaining. However, current methods exhibit two issues. They rely on static and context-unaware profiles, necessitating extensive manual...
We study branching random walk on $\mathbb{Z}$ in a bounded i.i.d. random environment. For this process, we prove that, for almost every realization of the environment, the distributions of the maximally displaced particle (re-centered around their medians) are tight. This extends the result of arXiv:2408.01555 , where tightness was...
Reconstructing natural visual scenes from neural activity is a key challenge in neuroscience and computer vision. We present SpikeVAEDiff, a novel two-stage framework that combines a Very Deep Variational Autoencoder (VDVAE) and the Versatile Diffusion model to generate high-resolution and semantically meaningful image reconstructions...
Despite significant progress in autoregressive image generation, inference remains slow due to the sequential nature of AR models and the ambiguity of image tokens, even when using speculative decoding. Recent works attempt to address this with relaxed speculative decoding but lack theoretical grounding. In this paper, we establish...
This paper addresses the problem of affordance grounding from RGBD images of an object, which aims to localize surface regions corresponding to a text query that describes an action on the object. While existing methods predict affordance regions only on visible surfaces, we propose Affostruction, a generative framework that...
We propose a variational formulation of an inverse problem in continuous-time stochastic control, aimed at identifying control costs consistent with a given distribution over trajectories. The formulation is based on minimizing the suboptimality gap of observed behavior. We establish a connection between the inverse problem and a...
White-Light Imaging (WLI) is the standard for endoscopic cancer screening, but Narrow-Band Imaging (NBI) offers superior diagnostic details. A key challenge is transferring knowledge from NBI to enhance WLI-only models, yet existing methods are critically hampered by their reliance on paired NBI-WLI images of the same lesion, a costly...