Tootfinder

VLM-Empowered Multi-Mode System for Efficient and Safe Planetary Navigation
Sinuo Cheng, Ruyi Zhou, Wenhao Feng, Huaiguang Yang, Haibo Gao, Zongquan Deng, Liang Ding
https://arxiv.org/abs/2506.16703

VLM-Empowered Multi-Mode System for Efficient and Safe Planetary Navigation
The increasingly complex and diverse planetary exploration environment requires more adaptable and flexible rover navigation strategy. In this study, we propose a VLM-empowered multi-mode system to achieve efficient while safe autonomous navigation for planetary rovers. Vision-Language Model (VLM) is used to parse scene information by image inputs to achieve a human-level understanding of terrain complexity. Based on the complexity classification, the system switches to the most suitable naviga…

This https://arxiv.org/abs/2506.06197 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Metainformation in Quantum Guessing Games
Quantum guessing games offer a structured approach to analyzing quantum information processing, where information is encoded in quantum states and extracted through measurement. An additional aspect of this framework is the influence of partial knowledge about the input on the optimal measurement strategies. This kind of side information can significantly influence the guessing strategy and earlier work has shown that the timing of such side information, whether revealed before or after the mea…

Thresholds for sensitive optimality and Blackwell optimality in stochastic games
St\'ephane Gaubert, Julien Grand-Cl\'ement, Ricardo D. Katz
https://arxiv.org/abs/2506.18545

Thresholds for sensitive optimality and Blackwell optimality in stochastic games
We investigate refinements of the mean-payoff criterion in two-player zero-sum perfect-information stochastic games. A strategy is Blackwell optimal if it is optimal in the discounted game for all discount factors sufficiently close to $1$. The notion of $d$-sensitive optimality interpolates between mean-payoff optimality (corresponding to the case $d=-1$) and Blackwell optimality ($d=+\infty$). The Blackwell threshold $α_{\sf Bw} \in [0,1[$ is the discount factor above which all optimal strat…

YOLOv11-RGBT: Towards a Comprehensive Single-Stage Multispectral Object Detection Framework
Dahang Wan, Rongsheng Lu, Yang Fang, Xianli Lang, Shuangbao Shu, Jingjing Chen, Siyuan Shen, Ting Xu, Zecong Ye
https://arxiv.org/abs/2506.14696

YOLOv11-RGBT: Towards a Comprehensive Single-Stage Multispectral Object Detection Framework
Multispectral object detection, which integrates information from multiple bands, can enhance detection accuracy and environmental adaptability, holding great application potential across various fields. Although existing methods have made progress in cross-modal interaction, low-light conditions, and model lightweight, there are still challenges like the lack of a unified single-stage framework, difficulty in balancing performance and fusion strategy, and unreasonable modality weight allocatio…

UCD: Unlearning in LLMs via Contrastive Decoding
Vinith M. Suriyakumar, Ayush Sekhari, Ashia Wilson
https://arxiv.org/abs/2506.12097 https://

UCD: Unlearning in LLMs via Contrastive Decoding
Machine unlearning aims to remove specific information, e.g. sensitive or undesirable content, from large language models (LLMs) while preserving overall performance. We propose an inference-time unlearning algorithm that uses contrastive decoding, leveraging two auxiliary smaller models, one trained without the forget set and one trained with it, to guide the outputs of the original model using their difference during inference. Our strategy substantially improves the tradeoff between unlearni…

Metainformation in Quantum Guessing Games
Teiko Heinosaari, Hanwool Lee
https://arxiv.org/abs/2506.06197 https://arxiv.org/pdf/2506.0…

Metainformation in Quantum Guessing Games
Quantum guessing games offer a structured approach to analyzing quantum information processing, where information is encoded in quantum states and extracted through measurement. An additional aspect of this framework is the influence of partial knowledge about the input on the optimal measurement strategies. This kind of side information can significantly influence the guessing strategy and earlier work has shown that the timing of such side information, whether revealed before or after the mea…

Private Memorization Editing: Turning Memorization into a Defense to Strengthen Data Privacy in Large Language Models
Elena Sofia Ruzzetti, Giancarlo A. Xompero, Davide Venditti, Fabio Massimo Zanzotto
https://arxiv.org/abs/2506.10024

Private Memorization Editing: Turning Memorization into a Defense to Strengthen Data Privacy in Large Language Models
Large Language Models (LLMs) memorize, and thus, among huge amounts of uncontrolled data, may memorize Personally Identifiable Information (PII), which should not be stored and, consequently, not leaked. In this paper, we introduce Private Memorization Editing (PME), an approach for preventing private data leakage that turns an apparent limitation, that is, the LLMs' memorization ability, into a powerful privacy defense strategy. While attacks against LLMs have been performed exploiting previou…

A variable dimension sketching strategy for nonlinear least-squares
Stefania Bellavia, Greta Malaspina, Benedetta Morini
https://arxiv.org/abs/2506.03965 h…

A variable dimension sketching strategy for nonlinear least-squares
We present a stochastic inexact Gauss-Newton method for the solution of nonlinear least-squares. To reduce the computational cost with respect to the classical method, at each iteration the proposed algorithm approximately minimizes the local model on a random subspace. The dimension of the subspace varies along the iterations, and two strategies are considered for its update: the first is based solely on the Armijo condition, the latter is based on information from the true Gauss-Newton model.…

This https://arxiv.org/abs/2409.06990 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

SIS: Seam-Informed Strategy for T-shirt Unfolding
Seams are information-rich components of garments. The presence of different types of seams and their combinations helps to select grasping points for garment handling. In this paper, we propose a new Seam-Informed Strategy (SIS) for finding actions for handling a garment, such as grasping and unfolding a T-shirt. Candidates for a pair of grasping points for a dual-arm manipulator system are extracted using the proposed Seam Feature Extraction Method (SFEM). A pair of grasping points for the ro…

Higher-Order Uncoupled Learning Dynamics and Nash Equilibrium
Sarah A. Toonsi, Jeff S. Shamma
https://arxiv.org/abs/2506.10874 https://

Higher-Order Uncoupled Learning Dynamics and Nash Equilibrium
We study learnability of mixed-strategy Nash Equilibrium (NE) in general finite games using higher-order replicator dynamics as well as classes of higher-order uncoupled heterogeneous dynamics. In higher-order uncoupled learning dynamics, players have no access to utilities of opponents (uncoupled) but are allowed to use auxiliary states to further process information (higher-order). We establish a link between uncoupled learning and feedback stabilization with decentralized control. Using this…

Learn Like Feynman: Developing and Testing an AI-Driven Feynman Bot
Akshaya Rajesh, Sumbul Khan
https://arxiv.org/abs/2506.09055 https://

Learn Like Feynman: Developing and Testing an AI-Driven Feynman Bot
The Feynman learning technique is an active learning strategy that helps learners simplify complex information through student-led teaching and discussion. In this paper, we present the development and usability testing of the Feynman Bot, which uses the Feynman technique to assist self-regulated learners who lack peer or instructor support. The Bot embodies the Feynman learning technique by encouraging learners to discuss their lecture material in a question-answer-driven discussion format. Th…

Blind Passive Beamforming for MIMO System
Wenhai Lai, Jiawei Yao, Kaiming Shen
https://arxiv.org/abs/2506.00987 https://arxiv.org/pdf…

Blind Passive Beamforming for MIMO System
Passive beamforming for the intelligent surface (IS)-aided multiple-input multiple-output (MIMO) communication is a difficult nonconvex problem. It becomes even more challenging under the practical discrete constraints on phase shifts. Unlike most of the existing approaches that rely on the channel state information (CSI), this work advocates a blind beamforming strategy without any CSI. Simply put, we propose a statistical method that learns the main feature of the wireless environment from th…

This https://arxiv.org/abs/2505.16652 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

Seeing Far and Clearly: Mitigating Hallucinations in MLLMs with Attention Causal Decoding
Recent advancements in multimodal large language models (MLLMs) have significantly improved performance in visual question answering. However, they often suffer from hallucinations. In this work, hallucinations are categorized into two main types: initial hallucinations and snowball hallucinations. We argue that adequate contextual information can be extracted directly from the token interaction process. Inspired by causal inference in the decoding strategy, we propose to leverage causal masks …

This https://arxiv.org/abs/2505.11292 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepe…

Status of the International Linear Collider
This paper is not a proposal for a CERN future project but provides information on the International Linear Collider (ILC) considered for Japan in order to facilitate the European Strategy discussion in a global context. It describes progress to date, ongoing engineering studies, updated cost estimate for the machine at $\sqrt{s}=250~\rm GeV$ and the situation in Japan. The physics of the ILC is not presented here, but jointly for all Linear Collider projects in a separate document ``A Linear C…

High-fidelity entanglement and coherent multi-qubit mapping in an atom array
Aruku Senoo, Alexander Baumg\"artner, Joanna W. Lis, Gaurav M. Vaidya, Zhongda Zeng, Giuliano Giudici, Hannes Pichler, Adam M. Kaufman
https://arxiv.org/abs/2506.13632

High-fidelity entanglement and coherent multi-qubit mapping in an atom array
Neutral atoms in optical tweezer arrays possess broad applicability for quantum information science, in computing, simulation, and metrology. Among atomic species, Ytterbium-171 is unique as it hosts multiple qubits, each of which is impactful for these distinct applications. Consequently, this atom is an ideal candidate to bridge multiple disciplines, which, more broadly, has been an increasingly effective strategy within the field of quantum science. Realizing the full potential of this syner…

This https://arxiv.org/abs/2505.01875 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

MolQAE: Quantum Autoencoder for Molecular Representation Learning
We introduce Quantum Molecular Autoencoder (MolQAE), the first quantum autoencoder to leverage the complete molecular structures. MolQAE uniquely maps SMILES strings directly to quantum states using parameterized rotation gates, preserving vital structural information. Its quantum encoder-decoder framework enables latent space compression and reconstruction. A dual-objective strategy optimizes fidelity and minimizes trash state deviation. Our evaluations demonstrate effective capture of molecul…