Tootfinder

Reasoning Like an Economist: Post-Training on Economic Problems Induces Strategic Generalization in LLMs
Yufa Zhou, Shaobo Wang, Xingyu Dong, Xiangqi Jin, Yifang Chen, Yue Min, Kexin Yang, Xingzhang Ren, Dayiheng Liu, Linfeng Zhang
https://arxiv.org/abs/2506.00577

Reasoning Like an Economist: Post-Training on Economic Problems Induces Strategic Generalization in LLMs
Directly training Large Language Models (LLMs) for Multi-Agent Systems (MAS) remains challenging due to intricate reward modeling, dynamic agent interactions, and demanding generalization requirements. This paper explores whether post-training techniques, specifically Supervised Fine-Tuning (SFT) and Reinforcement Learning with Verifiable Rewards (RLVR), can effectively $\textit{generalize}$ to multi-agent scenarios. We use economic reasoning as a testbed, leveraging its strong foundations in m…

Globally Consistent RGB-D SLAM with 2D Gaussian Splatting
Xingguang Zhong, Yue Pan, Liren Jin, Marija Popovi\'c, Jens Behley, Cyrill Stachniss
https://arxiv.org/abs/2506.00970

Globally Consistent RGB-D SLAM with 2D Gaussian Splatting
Recently, 3D Gaussian splatting-based RGB-D SLAM displays remarkable performance of high-fidelity 3D reconstruction. However, the lack of depth rendering consistency and efficient loop closure limits the quality of its geometric reconstructions and its ability to perform globally consistent mapping online. In this paper, we present 2DGS-SLAM, an RGB-D SLAM system using 2D Gaussian splatting as the map representation. By leveraging the depth-consistent rendering property of the 2D variant, we pr…

From Pixels to Camera: Scaling Superconducting Nanowire Single-Photon Detectors for Imaging at the Quantum-Limit
Jun Gao, Jin Chang, Bruno Lopez Rodriguez, Iman Esmaeil Zadeh, Val Zwiller, Ali W. Elshaari
https://arxiv.org/abs/2505.24725

From Pixels to Camera: Scaling Superconducting Nanowire Single-Photon Detectors for Imaging at the Quantum-Limit
Superconducting nanowire single-photon detectors (SNSPDs) have emerged as essential devices that push the boundaries of photon detection with unprecedented sensitivity, ultrahigh timing precision, and broad spectral response. Recent advancements in materials engineering, superconducting electronics integration, and cryogenic system design are enabling the evolution of SNSPDs from single-pixel detectors toward scalable arrays and large-format single-photon time tagging cameras. This perspective …

GeneBreaker: Jailbreak Attacks against DNA Language Models with Pathogenicity Guidance
Zaixi Zhang, Zhenghong Zhou, Ruofan Jin, Le Cong, Mengdi Wang
https://arxiv.org/abs/2505.23839

GeneBreaker: Jailbreak Attacks against DNA Language Models with Pathogenicity Guidance
DNA, encoding genetic instructions for almost all living organisms, fuels groundbreaking advances in genomics and synthetic biology. Recently, DNA Foundation Models have achieved success in designing synthetic functional DNA sequences, even whole genomes, but their susceptibility to jailbreaking remains underexplored, leading to potential concern of generating harmful sequences such as pathogens or toxin-producing genes. In this paper, we introduce GeneBreaker, the first framework to systematic…

TRAPDOC: Deceiving LLM Users by Injecting Imperceptible Phantom Tokens into Documents
Hyundong Jin, Sicheol Sung, Shinwoo Park, SeungYeop Baik, Yo-Sub Han
https://arxiv.org/abs/2506.00089

TRAPDOC: Deceiving LLM Users by Injecting Imperceptible Phantom Tokens into Documents
The reasoning, writing, text-editing, and retrieval capabilities of proprietary large language models (LLMs) have advanced rapidly, providing users with an ever-expanding set of functionalities. However, this growing utility has also led to a serious societal concern: the over-reliance on LLMs. In particular, users increasingly delegate tasks such as homework, assignments, or the processing of sensitive documents to LLMs without meaningful engagement. This form of over-reliance and misuse is em…

Beyond the LUMIR challenge: The pathway to foundational registration models
Junyu Chen, Shuwen Wei, Joel Honkamaa, Pekka Marttinen, Hang Zhang, Min Liu, Yichao Zhou, Zuopeng Tan, Zhuoyuan Wang, Yi Wang, Hongchao Zhou, Shunbo Hu, Yi Zhang, Qian Tao, Lukas F\"orner, Thomas Wendler, Bailiang Jian, Benedikt Wiestler, Tim Hable, Jin Kim, Dan Ruan, Frederic Madesta, Thilo Sentker, Wiebke Heyer, Lianrui Zuo, Yuwei Dai, Jing Wu, Jerry L. Prince, Harrison Bai, Yong Du, Yihao Liu, Alessa He…

Beyond the LUMIR challenge: The pathway to foundational registration models
Medical image challenges have played a transformative role in advancing the field, catalyzing algorithmic innovation and establishing new performance standards across diverse clinical applications. Image registration, a foundational task in neuroimaging pipelines, has similarly benefited from the Learn2Reg initiative. Building on this foundation, we introduce the Large-scale Unsupervised Brain MRI Image Registration (LUMIR) challenge, a next-generation benchmark designed to assess and advance u…

Faster negative length shortest paths by bootstrapping hop reducers
Yufan Huang, Peter Jin, Kent Quanrud
https://arxiv.org/abs/2506.00428 https://

Faster negative length shortest paths by bootstrapping hop reducers
The textbook algorithm for real-weighted single-source shortest paths takes $O(m n)$ time on a graph with $m$ edges and $n$ vertices. The breakthrough algorithm by Fineman [Fin24] takes $\tilde{O}(m n^{8/9})$ randomized time. The running time was subsequently improved to $\tilde{O}(mn^{4/5})$ [HJQ25]. We build on [Fin24; HJQ25] to obtain an $\tilde{O}(m n^{3/4} + m^{4/5} n)$ randomized running time. (Equivalently, $\tilde{O}(mn^{3/4})$ for $m \geq n^{5/4}$, and $\tilde{O}(m^{4/5} n)$ for $m \…

Photostriction-tunable Polarization and Structural Dynamics in Interlayer Sliding Ferroelectrics
Kun Yang, Jianxin Yu, Jia Zhang, Sheng Meng, Jin Zhang
https://arxiv.org/abs/2505.24186

Photostriction-tunable Polarization and Structural Dynamics in Interlayer Sliding Ferroelectrics
Two-dimensional ferroelectrics with robust polarization offer promising opportunities for non-volatile memory, field-effect transistors, and optoelectronic devices. However, the impact of lattice deformation on polarization and photoinduced structural response remains poorly understood. Here, we employ first-principles calculations to demonstrate photodoping-induced lattice expansion in rhombohedrally stacked bilayer MoS2, revealing a strong coupling between photodoping carrier and lattice stru…

Subgyrogroups within the product spaces of paratopological gyrogroups
Yingying Jin, Lihong Xie
https://arxiv.org/abs/2506.00024 https://

Subgyrogroups within the product spaces of paratopological gyrogroups
We present a characterization of paratopological gyrogroups that can be topologically embedded as subgyrogroups into a product of first-countable $T_{i}$ paratopological gyrogroups for $i = 0, 1, 2$. Specifically, we demonstrate that a strongly paratopological gyrogroup $G$ is topologically isomorphic to a subgyrogroup of a topological product of first-countable $T_1$ strongly paratopological gyrogroups if and only if $G$ is $T_1$, $ω$-balanced and the weakly Hausdorff number of $G$ is countab…

Exploring the potential for kinematically colder HI component as a tracer for star-forming gas in nearby galaxies
Hye-Jin Park, Andrew J. Battisti, Antoine Marchal, Luca Cortese, Emily Wisnioski, Mark Seibert, Shin-Jeong Kim, Naomi McClure-Griffiths, W. J. G. de Blok, Kathryn Grasha, Barry F. Madore, Jeff A. Rich, Rachael L. Beaton
https://

Exploring the potential for kinematically colder HI component as a tracer for star-forming gas in nearby galaxies
Atomic hydrogen (HI) dominates the mass of the cold interstellar medium, undergoing thermal condensation to form molecular gas and fuel star formation. Kinematically colder HI components, identified via kinematic decomposition of HI 21 cm data cubes, serve as a crucial transition phase between diffuse warm neutral gas and molecular hydrogen (H$_{2}$). We analyse these colder HI components by decomposing HI 21 cm data cubes of seven nearby galaxies - Sextans A, NGC 6822, WLM, NGC 5068, NGC 7793,…

High resolution up-conversion imaging in the 10 {\mu}m band under incoherent illumination
Zhao-Qi-Zhi Han, Xiao-Hua Wang, Jin-Peng Li, Bo-Wen Liu, Zheng-He Zhou, He Zhang, Yin-Hai Li, Zhi-Yuan Zhou, Bao-Sen Shi
https://arxiv.org/abs/2505.24367

High resolution up-conversion imaging in the 10 μm band under incoherent illumination
Long-wavelength infrared band exhibits significant utility in thermal signature acquisition and molecular spectral analysis, among other applications. The up-conversion detection technique enables effective signal transduction into the detection bandwidth of silicon-based photodetectors, thereby facilitating high-sensitivity photonic measurements. We realized high-resolution up-conversion imaging for incoherent thermal targets in the 10 μm spectral regime for the first time. Furthermore, this …

New Physics Search at the CEPC: a General Perspective
Stefan Antusch, Peter Athron, Daniele Barducci, Long Chen, Mingshui Chen, Xiang Chen, Huajie Cheng, Kingman Cheung, Joao Guimaraes da Costa, Arindam Das, Frank F. Deppisch, P. S. Bhupal Dev, Xiaokang Du, Yong Du, Yaquan Fang, Andrew Fowlie, Yu Gao, Bruce Mellado Garcia, Shao-Feng Ge, Jiayin Gu, Yu-Chen Guo, Jan Hajer, Chengcheng Han, Tao Han, Sven Heinemeyer, Fa Peng Huang, Yanping Huang, Jianfeng Jiang, Shan Jin, Liang Li, Lingfeng…

New Physics Search at the CEPC: a General Perspective
The Circular Electron-Positron Collider (CEPC), a proposed next-generation Higgs factory, provides new opportunities to explore physics beyond the Standard Model (SM). With its clean electron-positron collision environment and the ability to collect large samples of Higgs, W, and Z bosons, the CEPC enables precision measurements and searches for new physics. This white paper outlines the CEPC's discovery potential, including studies of exotic decays of the Higgs, Z, and top quarks, dark matter …

NbTiN Nanowire Resonators for Spin-Photon Coupling on Solid Neon
Y. Tian, I. Grytsenko, A. Jennings, J. Wang, H. Ikegami, X. Zhou, S. Tamate, H. Terai, H. Kutsuma, D. Jin, M. Benito, E. Kawakami
https://arxiv.org/abs/2505.24303

NbTiN Nanowire Resonators for Spin-Photon Coupling on Solid Neon
Electrons floating on a solid neon exhibit long charge coherence times, making them attractive for hybrid quantum systems. When combined with high-quality, high-impedance superconducting resonators and a local magnetic field gradient, this platform enables strong charge-photon and spin-charge coupling -- key ingredients for scalable spin qubit architectures. In this work, we fabricated NbTiN superconducting nanowire resonators and measured internal quality factors around $10^5$. We successfully…

Heterodyne detection of low-frequency fields via Rydberg EIT with phase demodulation
Shenchao Jin, Xiayang Fan, Xin Wang, Yi Song, Yuan Sun
https://arxiv.org/abs/2505.24268

Max Entropy Moment Kalman Filter for Polynomial Systems with Arbitrary Noise
Sangli Teng, Harry Zhang, David Jin, Ashkan Jasour, Ram Vasudevan, Maani Ghaffari, Luca Carlone
https://arxiv.org/abs/2506.00838

Max Entropy Moment Kalman Filter for Polynomial Systems with Arbitrary Noise
Designing optimal Bayes filters for nonlinear non-Gaussian systems is a challenging task. The main difficulties are: 1) representing complex beliefs, 2) handling non-Gaussian noise, and 3) marginalizing past states. To address these challenges, we focus on polynomial systems and propose the Max Entropy Moment Kalman Filter (MEM-KF). To address 1), we represent arbitrary beliefs by a Moment-Constrained Max-Entropy Distribution (MED). The MED can asymptotically approximate almost any distribution…

PseudoVC: Improving One-shot Voice Conversion with Pseudo Paired Data
Songjun Cao, Qinghua Wu, Jie Chen, Jin Li, Long Ma
https://arxiv.org/abs/2506.01039 h…

PseudoVC: Improving One-shot Voice Conversion with Pseudo Paired Data
As parallel training data is scarce for one-shot voice conversion (VC) tasks, waveform reconstruction is typically performed by various VC systems. A typical one-shot VC system comprises a content encoder and a speaker encoder. However, two types of mismatches arise: one for the inputs to the content encoder during training and inference, and another for the inputs to the speaker encoder. To address these mismatches, we propose a novel VC training method called \textit{PseudoVC} in this paper. …

Perspectives for hyperon and hypernuclei physics
Jin-Hui Chen, Li-Sheng Geng, Emiko Hiyama, Zhi-Wei Liu, Josef Pochodzalla
https://arxiv.org/abs/2506.00864

Perspectives for hyperon and hypernuclei physics
Hypernuclei, nuclei containing one or more hyperons, serve as unique laboratories for probing the non-perturbative quantum chromodynamics (QCD). Recent progress in hypernuclear physics, driven by advanced experimental techniques and theoretical innovations, is briefly reviewed with a focus on key findings and unresolved challenges, such as the precise determination of the hypertriton binding energy, investigations of charge symmetry breaking in mirror hypernuclei, and the search for exotic syst…

DriveMind: A Dual-VLM based Reinforcement Learning Framework for Autonomous Driving
Dawood Wasif, Terrence J Moore, Chandan K Reddy, Jin-Hee Cho
https://arxiv.org/abs/2506.00819

DriveMind: A Dual-VLM based Reinforcement Learning Framework for Autonomous Driving
End-to-end autonomous driving systems map sensor data directly to control commands, but remain opaque, lack interpretability, and offer no formal safety guarantees. While recent vision-language-guided reinforcement learning (RL) methods introduce semantic feedback, they often rely on static prompts and fixed objectives, limiting adaptability to dynamic driving scenes. We present DriveMind, a unified semantic reward framework that integrates: (i) a contrastive Vision-Language Model (VLM) encoder…

Towards Structure-aware Model for Multi-modal Knowledge Graph Completion
Linyu Li, Zhi Jin, Yichi Zhang, Dongming Jin, Chengfeng Dou, Yuanpeng He, Xuan Zhang, Haiyan Zhao
https://arxiv.org/abs/2505.21973

Towards Structure-aware Model for Multi-modal Knowledge Graph Completion
Knowledge graphs (KGs) play a key role in promoting various multimedia and AI applications. However, with the explosive growth of multi-modal information, traditional knowledge graph completion (KGC) models cannot be directly applied. This has attracted a large number of researchers to study multi-modal knowledge graph completion (MMKGC). Since MMKG extends KG to the visual and textual domains, MMKGC faces two main challenges: (1) how to deal with the fine-grained modality information interacti…

Algebraic aspects of the polynomial Littlewood-Offord problem
Zhihan Jin, Matthew Kwan, Lisa Sauermann, Yiting Wang
https://arxiv.org/abs/2505.23335 https:…

Algebraic aspects of the polynomial Littlewood-Offord problem
Consider a degree-$d$ polynomial $f(ξ_1,\dots,ξ_n)$ of independent Rademacher random variables $ξ_1,\dots,ξ_n$. To what extent can $f(ξ_1,\dots,ξ_n)$ concentrate on a single point? This is the so-called polynomial Littlewood-Offord problem. A nearly optimal bound was proved by Meka, Nguyen and Vu: the point probabilities are always at most about $1/\sqrt n$, unless $f$ is "close to the zero polynomial" (having only $o(n^d)$ nonzero coefficients). In this paper we prove several results s…

Unified Network-Based Representation of BIM Models for Embedding Semantic, Spatial, and Topological Data
Jin Han, Xin-Zheng Lu, Jia-Rui Lin
https://arxiv.org/abs/2505.22670

Unified Network-Based Representation of BIM Models for Embedding Semantic, Spatial, and Topological Data
Building Information Modeling (BIM) has revolutionized the construction industry by providing a comprehensive digital representation of building structures throughout their lifecycle. However, existing research lacks effective methods for capturing the complex spatial and topological relationships between components in BIM models, which are essential for understanding design patterns and enhancing decision-making. This study proposes a unified network-based representation method that integrates…

Representing Higher-Order Networks with Spectral Moments
Hao Tian, Shengmin Jin, Reza Zafarani
https://arxiv.org/abs/2505.23691 https://

Representing Higher-Order Networks with Spectral Moments
The spectral properties of traditional (dyadic) graphs, where an edge connects exactly two vertices, are widely studied in different applications. These spectral properties are closely connected to the structural properties of dyadic graphs. We generalize such connections and characterize higher-order networks by their spectral information. We first split the higher-order graphs by their ``edge orders" into several uniform hypergraphs. For each uniform hypergraph, we extract the corresponding s…

The Narrow Formation Pathway of Hot Saturns: Constraints on Initial Planetary Properties
Minghao Xie, Sheng Jin, Dong-Hong Wu
https://arxiv.org/abs/2505.23148

The Narrow Formation Pathway of Hot Saturns: Constraints on Initial Planetary Properties
The observed exoplanet population exhibits a scarcity of short-period Saturn-mass planets, a phenomenon referred to as the ``hot Saturn desert". This observational scarcity can be utilized to validate the theories regarding the formation and evolution of gas planets. In this study, we conduct large-scale numerical simulations to explore how the initial conditions of gas planets orbiting solar-type and M-dwarf stars influence their evolutionary trajectories in the semi-major axis versus planetar…

On the discrete Hilbert-type operators
Jianjun Jin
https://arxiv.org/abs/2505.22972 https://arxiv.org/pdf/2505.22972

On the discrete Hilbert-type operators
Recently, Bansah and Sehba studied in [3] the boundedness of a family of Hilbert-type integral operators, in which they characterized the $L^{p}-L^{q}$ boundedness of the operators for $1\leq p\leq q\leq \infty$. In this paper, we deal with the corresponding discrete Hilbert-type operators acting on the weighted sequence spaces. We establish some sufficient and necessary conditions for the $l^{p}-l^{q}$ boundedness of the operators for $1\leq p\leq q\leq \infty$. We find out that the conditions…

A Silicon Microstrip Detector for Power-Limited and Large Sensitive Area Applications
Dexing Miao, Zijun Xu, Zhiyu Xiang, Pingcheng Liu, Giovanni Ambrosi, Mattia Barbanera, Mengke Cai, Xudong Cai, Hsin-Yi Chou, Matteo Duranti, Valerio Formato, Maria Ionica, Yaozu Jiang, Liangchenglong Jin, Vladimir Koutsenko, Qinze Li, Cong Liu, Xingjian Lv, Alberto Oliva, Wenxi Peng, Rui Qiao, Gianluigi Silvestre, Zibing Wu, Xuhao Yuan, Hongyu Zhang, Xiyuan Zhang, Jianchun Wang

A Silicon Microstrip Detector for Power-Limited and Large Sensitive Area Applications
A silicon microstrip detector (SSD) has been developed to have state of the art spatial resolution and a large sensitive area under stringent power constraints. The design incorporates three floating strips with their bias resistors inserted between two aluminum readout strips. Beam test measurements with the single sensor confirmed that this configuration achieves a total detection efficiency of $99.8 \, \%$ and spatial resolution $7.6 \, \mathrm{μm}$ for MIPs. A double-$η$ algorithm was dev…

Dominant Kitaev interaction and field-induced quantum phase transitions in triangular-lattice KCeSe2
Mingtai Xie, Zheng Zhang, Weizhen Zhuo, Wei Xu, Jinfeng Zhu, Jan Embs, Lei Wang, Zikang Li, Huanpeng Bu, Anmin Zhang, Feng Jin, Jianting Ji, Zhongwen Ouyang, Liusuo Wu, Jie Ma, Qingming Zhang
https://arxiv.org/abs/2505.23502

Dominant Kitaev interaction and field-induced quantum phase transitions in triangular-lattice KCeSe2
Realizing Kitaev interactions on triangular lattices offers a compelling platform for exploring quantum-spin-liquid physics beyond the conventional honeycomb lattice framework. Here, we investigate the triangular-lattice antiferromagnet KCeSe2, where multiple probes reveal strong magnetic anisotropy suggesting significant Kitaev physics. Through detailed and combined analysis of magnetization, neutron scattering, and thermodynamic experiments, we identify dominant ferromagnetic Kitaev ($K = -1.…

A Synthetic Business Cycle Approach to Counterfactual Analysis with Nonstationary Macroeconomic Data
Zhentao Shi, Jin Xi, Haitian Xie
https://arxiv.org/abs/2505.22388

A Synthetic Business Cycle Approach to Counterfactual Analysis with Nonstationary Macroeconomic Data
This paper investigates the use of synthetic control methods for causal inference in macroeconomic settings when dealing with possibly nonstationary data. While the synthetic control approach has gained popularity for estimating counterfactual outcomes, we caution researchers against assuming a common nonstationary trend factor across units for macroeconomic outcomes, as doing so may result in misleading causal estimation-a pitfall we refer to as the spurious synthetic control problem. To addre…

MOA-2022-BLG-091Lb and KMT-2024-BLG-1209Lb: Microlensing planets detected through weak caustic-crossing signals
Cheongho Han, Chung-Uk Lee, Andrzej Udalski, Ian A. Bond, Hongjing Yang, Michael D. Albrow, Sun-Ju Chung, Andrew Gould, Youn Kil Jung, Kyu-Ha Hwang, Yoon-Hyun Ryu, Yossi Shvartzvald, In-Gu Shin, Jennifer C. Yee, Weicheng Zang, Tanagodchaporn Inyanya, Sang-Mok Cha, Doeon Kim, Dong-Jin Kim, Seung-Lee Kim, Dong-Joo Lee, Yongseok Lee, Byeong-Gon Park, Richard W. Pogge, Przemek Mr…

MOA-2022-BLG-091Lb and KMT-2024-BLG-1209Lb: Microlensing planets detected through weak caustic-crossing signals
The light curves of the microlensing events MOA-2022-BLG-091 and KMT-2024-BLG-1209 exhibit anomalies with very similar features. These anomalies appear near the peaks of the light curves, where the magnifications are moderately high, and are distinguished by weak caustic-crossing features with minimal distortion while the source remains inside the caustic. To achieve a deeper understanding of these anomalies, we conducted a comprehensive analysis of the lensing events. We carried out binary-len…

Retrieval-Augmented Generation in Biomedicine: A Survey of Technologies, Datasets, and Clinical Applications
Jiawei He, Boya Zhang, Hossein Rouhizadeh, Yingjian Chen, Rui Yang, Jin Lu, Xudong Chen, Nan Liu, Irene Li, Douglas Teodoro
https://arxiv.org/abs/2505.01146

Retrieval-Augmented Generation in Biomedicine: A Survey of Technologies, Datasets, and Clinical Applications
Recent advances in large language models (LLMs) have demonstrated remarkable capabilities in natural language processing tasks. However, their application in the biomedical domain presents unique challenges, particularly regarding factual accuracy and up-to-date knowledge integration. Retrieval Augmented Generation (RAG) has emerged as a promising solution to address these challenges by combining the generative capabilities of LLMs with external knowledge retrieval. This comprehensive survey ex…