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c9e123a970a81f481ccab2519cc1af26a1819d6207bfca10de3c9c1234d42013 | 2026-01-21T00:00:00-05:00 | BlocksecRT-DETR: Decentralized Privacy-Preserving and Token-Efficient Federated Transformer Learning for Secure Real-Time Object Detection in ITS | arXiv:2601.12693v1 Announce Type: new Abstract: Federated real-time object detection using transformers in Intelligent Transportation Systems (ITS) faces three major challenges: (1) missing-class non-IID data heterogeneity from geographically diverse traffic environments, (2) latency constraints on edge hardware for hi... | https://arxiv.org/abs/2601.12693 | Academic Papers | svg |
1a812d31940e63df4cd06825e948b4311282bb17186565f5c9dbb87b726d6d4a | 2026-01-21T00:00:00-05:00 | Closed-loop Uplink Radio Resource Management in CF-O-RAN Empowered 5G Aerial Corridor | arXiv:2601.12694v1 Announce Type: new Abstract: In this paper, we investigate the uplink (UL) radio resource management for 5G aerial corridors with an open-radio access network (O-RAN)-enabled cell-free (CF) massive multiple-input multiple-output (mMIMO) system. Our objective is to maximize the minimum spectral effici... | https://arxiv.org/abs/2601.12694 | Academic Papers | svg |
1e0ac78fa5acc8350a8459e080129556bac25e56716e448341aeb4ffddaffd59 | 2026-01-21T00:00:00-05:00 | From Noise to Knowledge: System Identification with Systematic Polytope Construction via Cyclic Reformulation | arXiv:2601.12695v1 Announce Type: new Abstract: Model-based control requires accurate mathematical models to guarantee control performance and stability. However, obtaining accurate models is challenging due to process and sensor noise. This paper proposes a novel identification algorithm that derives polytopic uncerta... | https://arxiv.org/abs/2601.12695 | Academic Papers | svg |
39613efb29252c7d9aa4c8415860997bbd547290da2f7357a1826de950c0cb0c | 2026-01-21T00:00:00-05:00 | UbuntuGuard: A Culturally-Grounded Policy Benchmark for Equitable AI Safety in African Languages | arXiv:2601.12696v1 Announce Type: new Abstract: Current guardian models are predominantly Western-centric and optimized for high-resource languages, leaving low-resource African languages vulnerable to evolving harms, cross-lingual safety failures, and cultural misalignment. Moreover, most guardian models rely on rigid... | https://arxiv.org/abs/2601.12696 | Academic Papers | svg |
6a325245df613f5fac54163b31ceb321c9e9ac4063a99dc8c8b33e1016448742 | 2026-01-21T00:00:00-05:00 | Fusing in 3D: Free-Viewpoint Fusion Rendering with a 3D Infrared-Visible Scene Representation | arXiv:2601.12697v1 Announce Type: new Abstract: Infrared-visible image fusion aims to integrate infrared and visible information into a single fused image. Existing 2D fusion methods focus on fusing images from fixed camera viewpoints, neglecting a comprehensive understanding of complex scenarios, which results in the ... | https://arxiv.org/abs/2601.12697 | Academic Papers | svg |
6ec44d56276bf0f4c48fd2b0478ca7518c9a77741e4db126359fa32c7229f948 | 2026-01-21T00:00:00-05:00 | A Two-Stage GPU Kernel Tuner Combining Semantic Refactoring and Search-Based Optimization | arXiv:2601.12698v1 Announce Type: new Abstract: GPU code optimization is a key performance bottleneck for HPC workloads as well as large-model training and inference. Although compiler optimizations and hand-written kernels can partially alleviate this issue, achieving near-hardware-limit performance still relies heavi... | https://arxiv.org/abs/2601.12698 | Academic Papers | svg |
13b360b6f22c31c0fe09a18a9be8d6526cf5350ef4b9b58c236e7e7b3f0484ed | 2026-01-21T00:00:00-05:00 | Resource-Conscious RL Algorithms for Deep Brain Stimulation | arXiv:2601.12699v1 Announce Type: new Abstract: Deep Brain Stimulation (DBS) has proven to be a promising treatment of Parkinson's Disease (PD). DBS involves stimulating specific regions of the brain's Basal Ganglia (BG) using electric impulses to alleviate symptoms of PD such as tremors, rigidity, and bradykinesia. Al... | https://arxiv.org/abs/2601.12699 | Academic Papers | svg |
1549f248db05a045fc217e73ea9e75a1ed22afdfa85b10ffcae3b6fa4fb12b57 | 2026-01-21T00:00:00-05:00 | RPT*: Global Planning with Probabilistic Terminals for Target Search in Complex Environments | arXiv:2601.12701v1 Announce Type: new Abstract: Routing problems such as Hamiltonian Path Problem (HPP), seeks a path to visit all the vertices in a graph while minimizing the path cost. This paper studies a variant, HPP with Probabilistic Terminals (HPP-PT), where each vertex has a probability representing the likelih... | https://arxiv.org/abs/2601.12701 | Academic Papers | svg |
f771acab1e1a7b9721b3ec9506a73631e49b82e89dfc6ed637bb86d09dfca07f | 2026-01-21T00:00:00-05:00 | Towards Spectroscopy: Susceptibility Clusters in Language Models | arXiv:2601.12703v1 Announce Type: new Abstract: Spectroscopy infers the internal structure of physical systems by measuring their response to perturbations. We apply this principle to neural networks: perturbing the data distribution by upweighting a token $y$ in context $x$, we measure the model's response via suscept... | https://arxiv.org/abs/2601.12703 | Academic Papers | svg |
37ac5d6c9706895fbe50442ca5073b8309ccd778cebfe10e765ce7fc4f25e129 | 2026-01-21T00:00:00-05:00 | Adaptively trained Physics-informed Radial Basis Function Neural Networks for Solving Multi-asset Option Pricing Problems | arXiv:2601.12704v1 Announce Type: new Abstract: The present study investigates the numerical solution of Black-Scholes partial differential equation (PDE) for option valuation with multiple underlying assets. We develop a physics-informed (PI) machine learning algorithm based on a radial basis function neural network (... | https://arxiv.org/abs/2601.12704 | Academic Papers | svg |
30b0e99ea5c37713e03c0842fdb27a97efcfe31613907ceaafec3a79de6e1779 | 2026-01-21T00:00:00-05:00 | How do the Global South Diasporas Mobilize for Transnational Political Change? | arXiv:2601.12705v1 Announce Type: new Abstract: This paper examines how non-resident Bangladeshis mobilized during the 2024 quota-reform turned pro-democracy movement, leveraging social platforms and remittance flows to challenge state authority. Drawing on semi-structured interviews, we identify four phases of their c... | https://arxiv.org/abs/2601.12705 | Academic Papers | svg |
55ffd237517ea765c2dd4a466a764345c4187d6859812f323a56c363398d0ec9 | 2026-01-21T00:00:00-05:00 | Trend-Adjusted Time Series Models with an Application to Gold Price Forecasting | arXiv:2601.12706v1 Announce Type: new Abstract: Time series data play a critical role in various fields, including finance, healthcare, marketing, and engineering. A wide range of techniques (from classical statistical models to neural network-based approaches such as Long Short-Term Memory (LSTM)) have been employed t... | https://arxiv.org/abs/2601.12706 | Academic Papers | svg |
ded9e55d5d53770c45cc72526710c2a4216b9486eac05e7262d725024a7b2749 | 2026-01-21T00:00:00-05:00 | Decoding Rewards in Competitive Games: Inverse Game Theory with Entropy Regularization | arXiv:2601.12707v1 Announce Type: new Abstract: Estimating the unknown reward functions driving agents' behaviors is of central interest in inverse reinforcement learning and game theory. To tackle this problem, we develop a unified framework for reward function recovery in two-player zero-sum matrix games and Markov g... | https://arxiv.org/abs/2601.12707 | Academic Papers | svg |
3766d3b293b8806695a4b7646e757c4dae46ece0977dcadce661ef57edf3deba | 2026-01-21T00:00:00-05:00 | Neurosymbolic LoRA: Why and When to Tune Weights vs. Rewrite Prompts | arXiv:2601.12711v1 Announce Type: new Abstract: Large language models (LLMs) can be adapted either through numerical updates that alter model parameters or symbolic manipulations that work on discrete prompts or logical constraints. While numerical fine-tuning excels at injecting new factual knowledge, symbolic updates... | https://arxiv.org/abs/2601.12711 | Academic Papers | svg |
aab9f737881d36c5b71b6c2f3850f9401267b8a750b899756bd347f954b729a3 | 2026-01-21T00:00:00-05:00 | Dynamic Detection of Inefficient Data Mapping Patterns in Heterogeneous OpenMP Applications | arXiv:2601.12713v1 Announce Type: new Abstract: With the growing prevalence of heterogeneous computing, CPUs are increasingly being paired with accelerators to achieve new levels of performance and energy efficiency. However, data movement between devices remains a significant bottleneck, complicating application devel... | https://arxiv.org/abs/2601.12713 | Academic Papers | svg |
d2fd03cdf3d762efc63e77d2f7102e02af691c5faa436a8d2889f80e2ffeed01 | 2026-01-21T00:00:00-05:00 | P2L-CA: An Effective Parameter Tuning Framework for Rehearsal-Free Multi-Label Class-Incremental Learning | arXiv:2601.12714v1 Announce Type: new Abstract: Multi-label Class-Incremental Learning aims to continuously recognize novel categories in complex scenes where multiple objects co-occur. However, existing approaches often incur high computational costs due to full-parameter fine-tuning and substantial storage overhead f... | https://arxiv.org/abs/2601.12714 | Academic Papers | svg |
f84471f7467731fe8a3f88b5658d7c0e519d898a95f51a2a5a333bd1adbb9bd3 | 2026-01-21T00:00:00-05:00 | RSOD: Reliability-Guided Sonar Image Object Detection with Extremely Limited Labels | arXiv:2601.12715v1 Announce Type: new Abstract: Object detection in sonar images is a key technology in underwater detection systems. Compared to natural images, sonar images contain fewer texture details and are more susceptible to noise, making it difficult for non-experts to distinguish subtle differences between cl... | https://arxiv.org/abs/2601.12715 | Academic Papers | svg |
017cf5c362c34579b005dba2784811c5f37e2ef3fd60a233b639246d3e01a751 | 2026-01-21T00:00:00-05:00 | CellularSpecSec-Bench: A Staged Benchmark for Evidence-Grounded Interpretation and Security Reasoning over 3GPP Specifications | arXiv:2601.12716v1 Announce Type: new Abstract: Cellular networks are critical infrastructure supporting billions of worldwide users and safety- and mission-critical services. Vulnerabilities in cellular networks can therefore cause service disruption, privacy breaches, and broad societal harm, motivating growing effor... | https://arxiv.org/abs/2601.12716 | Academic Papers | svg |
946e42b6b2a128870a7de05425ba9f034f086d41db009b83ba3412744ee60eef | 2026-01-21T00:00:00-05:00 | Dataset of GenAI-Assisted Information Problem Solving in Education | arXiv:2601.12718v1 Announce Type: new Abstract: Information Problem Solving (IPS) is a critical competency for academic and professional success in education, work, and life. The advent of Generative Artificial Intelligence (GenAI), particularly tools like ChatGPT, has introduced new possibilities for supporting studen... | https://arxiv.org/abs/2601.12718 | Academic Papers | svg |
50a2704ea21ce8ef4fbe3bce1dac4b6153b0733eb815344586922b378ddc80aa | 2026-01-21T00:00:00-05:00 | S2DiT: Sandwich Diffusion Transformer for Mobile Streaming Video Generation | arXiv:2601.12719v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) have recently improved video generation quality. However, their heavy computational cost makes real-time or on-device generation infeasible. In this work, we introduce S2DiT, a Streaming Sandwich Diffusion Transformer designed for efficient, ... | https://arxiv.org/abs/2601.12719 | Academic Papers | svg |
5b17d2e30ce5977f7cdae411ecf2a29d412066fc4d879aea8ad239f7785996a4 | 2026-01-21T00:00:00-05:00 | Teaching Large Reasoning Models Effective Reflection | arXiv:2601.12720v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) have recently shown impressive performance on complex reasoning tasks, often by engaging in self-reflective behaviors such as self-critique and backtracking. However, not all reflections are beneficial-many are superficial, offering little to... | https://arxiv.org/abs/2601.12720 | Academic Papers | svg |
9684b13eee329b1c54941df17814a1d004fadba0ec67fd4b3de7cde9c8d6280b | 2026-01-21T00:00:00-05:00 | An Evolutionary Framework for Automatic Optimization Benchmark Generation via Large Language Models | arXiv:2601.12723v1 Announce Type: new Abstract: Optimization benchmarks play a fundamental role in assessing algorithm performance; however, existing artificial benchmarks often fail to capture the diversity and irregularity of real-world problem structures, while benchmarks derived from real-world problems are costly ... | https://arxiv.org/abs/2601.12723 | Academic Papers | svg |
a734998f3eb660537d6865b71531dd44c0cf76d1849a5334b413d219df109287 | 2026-01-21T00:00:00-05:00 | Explicit Entropic Constructions for Coverage, Facility Location, and Graph Cuts | arXiv:2601.12724v1 Announce Type: new Abstract: Shannon entropy is a polymatroidal set function and lies at the foundation of information theory, yet the class of entropic polymatroids is strictly smaller than the class of all submodular functions. In parallel, submodular and combinatorial information measures (SIMs) h... | https://arxiv.org/abs/2601.12724 | Academic Papers | svg |
83f7010e03c817e48053ca4c2e151c065b3fb2ab6dc42739137be20d0096a223 | 2026-01-21T00:00:00-05:00 | AI-exhibited Personality Traits Can Shape Human Self-concept through Conversations | arXiv:2601.12727v1 Announce Type: new Abstract: Recent Large Language Model (LLM) based AI can exhibit recognizable and measurable personality traits during conversations to improve user experience. However, as human understandings of their personality traits can be affected by their interaction partners' traits, a pot... | https://arxiv.org/abs/2601.12727 | Academic Papers | svg |
d825bc6bc30886a8586be4bebf844b90090b3ae366830147caca48ff4f1cd854 | 2026-01-21T00:00:00-05:00 | DC-VLAQ: Query-Residual Aggregation for Robust Visual Place Recognition | arXiv:2601.12729v1 Announce Type: new Abstract: One of the central challenges in visual place recognition (VPR) is learning a robust global representation that remains discriminative under large viewpoint changes, illumination variations, and severe domain shifts. While visual foundation models (VFMs) provide strong lo... | https://arxiv.org/abs/2601.12729 | Academic Papers | svg |
c783a36518947f51b1c861cf59974df93ceeb07ad9407884af534dc0e6a6f0cc | 2026-01-21T00:00:00-05:00 | Distribution-Centric Policy Optimization Dominates Exploration-Exploitation Trade-off | arXiv:2601.12730v1 Announce Type: new Abstract: The exploration-exploitation (EE) trade-off is a central challenge in reinforcement learning (RL) for large language models (LLMs). With Group Relative Policy Optimization (GRPO), training tends to be exploitation driven: entropy decreases monotonically, samples convergen... | https://arxiv.org/abs/2601.12730 | Academic Papers | svg |
6567ddae2313c96d8eb1fdf5188bf71eb7fb549f344cfb10809f47e45792be04 | 2026-01-21T00:00:00-05:00 | A Shared Geometry of Difficulty in Multilingual Language Models | arXiv:2601.12731v1 Announce Type: new Abstract: Predicting problem-difficulty in large language models (LLMs) refers to estimating how difficult a task is according to the model itself, typically by training linear probes on its internal representations. In this work, we study the multilingual geometry of problem-diffi... | https://arxiv.org/abs/2601.12731 | Academic Papers | svg |
1d18dcfc8caace5b2d297edc36c8d2c1d60ba2695e280c086031000425ed18ab | 2026-01-21T00:00:00-05:00 | Optimal Error Estimates of a Linearized Backward Euler Localized Orthogonal Decomposition for the Landau-Lifshitz Equation | arXiv:2601.12734v1 Announce Type: new Abstract: We introduce a novel spatial discretization technique for the reliable and efficient simulation of magnetization dynamics governed by the Landau-Lifshitz (LL) equation. The overall discretization error is systematically decomposed into temporal and spatial components. The... | https://arxiv.org/abs/2601.12734 | Academic Papers | svg |
9ef78446391a8b3596f5b4c62bbedd3056f18f7f2552b9078cf78455418d5888 | 2026-01-21T00:00:00-05:00 | OpenAI for OpenAPI: Automated generation of REST API specification via LLMs | arXiv:2601.12735v1 Announce Type: new Abstract: REST APIs, based on the REpresentational State Transfer (REST) architecture, are the primary type of Web API. The OpenAPI Specification (OAS) serves as the de facto standard for describing REST APIs and is crucial for multiple software engineering tasks. However, develope... | https://arxiv.org/abs/2601.12735 | Academic Papers | svg |
bf55acf77576eef97c980cf2dd1c2f4e9d88e7d6216a830dd4019b1337c57006 | 2026-01-21T00:00:00-05:00 | KaoLRM: Repurposing Pre-trained Large Reconstruction Models for Parametric 3D Face Reconstruction | arXiv:2601.12736v1 Announce Type: new Abstract: We propose KaoLRM to re-target the learned prior of the Large Reconstruction Model (LRM) for parametric 3D face reconstruction from single-view images. Parametric 3D Morphable Models (3DMMs) have been widely used for facial reconstruction due to their compact and interpre... | https://arxiv.org/abs/2601.12736 | Academic Papers | svg |
3500a990a6e26e2a09368633020b4ce6507fa23dc4f54191fbacb1cba942aefb | 2026-01-21T00:00:00-05:00 | TreeWriter: AI-Assisted Hierarchical Planning and Writing for Long-Form Documents | arXiv:2601.12740v1 Announce Type: new Abstract: Long documents pose many challenges to current intelligent writing systems. These include maintaining consistency across sections, sustaining efficient planning and writing as documents become more complex, and effectively providing and integrating AI assistance to the us... | https://arxiv.org/abs/2601.12740 | Academic Papers | svg |
99563d4d596d997f85cf1df9cc61b8923afc48769199e2f0c63c4f5a82b406f6 | 2026-01-21T00:00:00-05:00 | An Introduction to Razborov's Flag Algebra as a Proof System for Extremal Graph Theory | arXiv:2601.12741v1 Announce Type: new Abstract: Razborov's flag algebra forms a powerful framework for deriving asymptotic inequalities between induced subgraph densities, underpinning many advances in extremal graph theory. This survey introduces flag algebra to computer scientists working in logic, programming langua... | https://arxiv.org/abs/2601.12741 | Academic Papers | svg |
6ea5eda455e7bb3148bdf2b88830e3172d36b6161ef3f8e66f54bfebe3b76358 | 2026-01-21T00:00:00-05:00 | AirHunt: Bridging VLM Semantics and Continuous Planning for Efficient Aerial Object Navigation | arXiv:2601.12742v1 Announce Type: new Abstract: Recent advances in large Vision-Language Models (VLMs) have provided rich semantic understanding that empowers drones to search for open-set objects via natural language instructions. However, prior systems struggle to integrate VLMs into practical aerial systems due to o... | https://arxiv.org/abs/2601.12742 | Academic Papers | svg |
98cd906e2e1253ca608e4a4b2882d1f100cae795dce58b1ad9dd1948ee2c5f8b | 2026-01-21T00:00:00-05:00 | Vision Language Models for Optimization-Driven Intent Processing in Autonomous Networks | arXiv:2601.12744v1 Announce Type: new Abstract: Intent-Based Networking (IBN) allows operators to specify high-level network goals rather than low-level configurations. While recent work demonstrates that large language models can automate configuration tasks, a distinct class of intents requires generating optimizatio... | https://arxiv.org/abs/2601.12744 | Academic Papers | svg |
b77261960475961c224fc17168f49725236d0cf781af8cf6f231f33d31ecacd6 | 2026-01-21T00:00:00-05:00 | A Graph Prompt Fine-Tuning Method for WSN Spatio-Temporal Correlation Anomaly Detection | arXiv:2601.12745v1 Announce Type: new Abstract: Anomaly detection of multi-temporal modal data in Wireless Sensor Network (WSN) can provide an important guarantee for reliable network operation. Existing anomaly detection methods in multi-temporal modal data scenarios have the problems of insufficient extraction of spa... | https://arxiv.org/abs/2601.12745 | Academic Papers | svg |
96526ae299ca04d112564821484e805f1661dd065e19569cd8f1858aaaa8a42e | 2026-01-21T00:00:00-05:00 | SSPFormer: Self-Supervised Pretrained Transformer for MRI Images | arXiv:2601.12747v1 Announce Type: new Abstract: The pre-trained transformer demonstrates remarkable generalization ability in natural image processing. However, directly transferring it to magnetic resonance images faces two key challenges: the inability to adapt to the specificity of medical anatomical structures and ... | https://arxiv.org/abs/2601.12747 | Academic Papers | svg |
8666bb73a7bea5e4298c4fb91001bcd5b041ba5d3c076d0ab9a457df0e9d58a2 | 2026-01-21T00:00:00-05:00 | Towards Robust Process Reward Modeling via Noise-aware Learning | arXiv:2601.12748v1 Announce Type: new Abstract: Process Reward Models (PRMs) have achieved strong results in complex reasoning, but are bottlenecked by costly process-level supervision. A widely used alternative, Monte Carlo Estimation (MCE), defines process rewards as the probability that a policy model reaches the co... | https://arxiv.org/abs/2601.12748 | Academic Papers | svg |
d233dc691e196b61a7bf6b75f5f29b600acaeec7f18c028318f2432cab83b16a | 2026-01-21T00:00:00-05:00 | Efficient Local-to-Global Collaborative Perception via Joint Communication and Computation Optimization | arXiv:2601.12749v1 Announce Type: new Abstract: Autonomous driving relies on accurate perception to ensure safe driving. Collaborative perception improves accuracy by mitigating the sensing limitations of individual vehicles, such as limited perception range and occlusion-induced blind spots. However, collaborative per... | https://arxiv.org/abs/2601.12749 | Academic Papers | svg |
ea756d14cde26f98474ca55a8d66a800713a28ba5e9bfbd3e51eb04e6d29b8c4 | 2026-01-21T00:00:00-05:00 | Approximation Schemes for Sequential Hiring Problems | arXiv:2601.12750v1 Announce Type: new Abstract: The main contribution of this paper resides in providing novel algorithmic advances and analytical insights for the sequential hiring problem, a recently introduced dynamic optimization model where a firm adaptively fills a limited number of positions from a pool of appli... | https://arxiv.org/abs/2601.12750 | Academic Papers | svg |
a7372b710b0a2c2bb5440d80b300e9680bee445b787984062227fcc973796322 | 2026-01-21T00:00:00-05:00 | A Boolean Function-Theoretic Framework for Expressivity in GNNs with Applications to Fair Graph Mining | arXiv:2601.12751v1 Announce Type: new Abstract: We propose a novel expressivity framework for Graph Neural Networks (GNNs) grounded in Boolean function theory, enabling a fine-grained analysis of their ability to capture complex subpopulation structures. We introduce the notion of \textit{Subpopulation Boolean Isomorph... | https://arxiv.org/abs/2601.12751 | Academic Papers | svg |
c1d8a9719132218417f619803a604beed5fa94a0fb57f0d89d017827a1d27da0 | 2026-01-21T00:00:00-05:00 | SoundPlot: An Open-Source Framework for Birdsong Acoustic Analysis and Neural Synthesis with Interactive 3D Visualization | arXiv:2601.12752v1 Announce Type: new Abstract: We present SoundPlot, an open-source framework for analyzing avian vocalizations through acoustic feature extraction, dimensionality reduction, and neural audio synthesis. The system transforms audio signals into a multi-dimensional acoustic feature space, enabling real-t... | https://arxiv.org/abs/2601.12752 | Academic Papers | svg |
2b74664e3246f4c89d415e5d831b896a63674dd4dc37f234d6c2ef93d9a5884e | 2026-01-21T00:00:00-05:00 | PAIR-SAFE: A Paired-Agent Approach for Runtime Auditing and Refining AI-Mediated Mental Health Support | arXiv:2601.12754v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for mental health support, yet they can produce responses that are overly directive, inconsistent, or clinically misaligned, particularly in sensitive or high-risk contexts. Existing approaches to mitigating these risks l... | https://arxiv.org/abs/2601.12754 | Academic Papers | svg |
17eda7325082f9f9f1056d751425683660efee92820b30434bcc879d5a2e6231 | 2026-01-21T00:00:00-05:00 | VISPA: Pluralistic Alignment via Automatic Value Selection and Activation | arXiv:2601.12758v1 Announce Type: new Abstract: As large language models are increasingly used in high-stakes domains, it is essential that their outputs reflect not average} human preference, rather range of varying perspectives. Achieving such pluralism, however, remains challenging. Existing approaches consider limi... | https://arxiv.org/abs/2601.12758 | Academic Papers | svg |
70c5e5d33c3cbbff59198050b594559b3a17cb535c1c0350f65d5af0fe95f0e4 | 2026-01-21T00:00:00-05:00 | Moaw: Unleashing Motion Awareness for Video Diffusion Models | arXiv:2601.12761v1 Announce Type: new Abstract: Video diffusion models, trained on large-scale datasets, naturally capture correspondences of shared features across frames. Recent works have exploited this property for tasks such as optical flow prediction and tracking in a zero-shot setting. Motivated by these finding... | https://arxiv.org/abs/2601.12761 | Academic Papers | svg |
2bbec37bf2664de63297a24f46f29d7a8e64975a242dfe8a956e2079666d7d29 | 2026-01-21T00:00:00-05:00 | Teaching LLMs to Learn Tool Trialing and Execution through Environment Interaction | arXiv:2601.12762v1 Announce Type: new Abstract: Equipping Large Language Models (LLMs) with external tools enables them to solve complex real-world problems. However, the robustness of existing methods remains a critical challenge when confronting novel or evolving tools. Existing trajectory-centric paradigms primarily... | https://arxiv.org/abs/2601.12762 | Academic Papers | svg |
9017a2472e80476e5dda84e372154b7da293e130c0db25b0f9048a6cd2e16c85 | 2026-01-21T00:00:00-05:00 | Towards Unbiased Source-Free Object Detection via Vision Foundation Models | arXiv:2601.12765v1 Announce Type: new Abstract: Source-Free Object Detection (SFOD) has garnered much attention in recent years by eliminating the need of source-domain data in cross-domain tasks, but existing SFOD methods suffer from the Source Bias problem, i.e. the adapted model remains skewed towards the source dom... | https://arxiv.org/abs/2601.12765 | Academic Papers | svg |
f20ac2085a396b50bd9baa484e1f992fd8e32a72fb37941d59e34fafd70efe1e | 2026-01-21T00:00:00-05:00 | Spatial-VLN: Zero-Shot Vision-and-Language Navigation With Explicit Spatial Perception and Exploration | arXiv:2601.12766v1 Announce Type: new Abstract: Zero-shot Vision-and-Language Navigation (VLN) agents leveraging Large Language Models (LLMs) excel in generalization but suffer from insufficient spatial perception. Focusing on complex continuous environments, we categorize key perceptual bottlenecks into three spatial ... | https://arxiv.org/abs/2601.12766 | Academic Papers | svg |
8b68bcec18ac1e8c1234b9171879daf77f8446904ef6ea793b74afd7709b6f00 | 2026-01-21T00:00:00-05:00 | Delving Deeper: Hierarchical Visual Perception for Robust Video-Text Retrieval | arXiv:2601.12768v1 Announce Type: new Abstract: Video-text retrieval (VTR) aims to locate relevant videos using natural language queries. Current methods, often based on pre-trained models like CLIP, are hindered by video's inherent redundancy and their reliance on coarse, final-layer features, limiting matching accura... | https://arxiv.org/abs/2601.12768 | Academic Papers | svg |
1b2dcf0c1a38cf03e81379a09a138bf5b204775f1dff6ef4d70b71952347ffb6 | 2026-01-21T00:00:00-05:00 | Generalizable and Animatable 3D Full-Head Gaussian Avatar from a Single Image | arXiv:2601.12770v1 Announce Type: new Abstract: Building 3D animatable head avatars from a single image is an important yet challenging problem. Existing methods generally collapse under large camera pose variations, compromising the realism of 3D avatars. In this work, we propose a new framework to tackle the novel se... | https://arxiv.org/abs/2601.12770 | Academic Papers | svg |
4829df39ef051dd5d099671aa7b138c63b11a6ecd6ea97429a6e8170cff20fec | 2026-01-21T00:00:00-05:00 | Who Does This Name Remind You of? Nationality Prediction via Large Language Model Associative Memory | arXiv:2601.12771v1 Announce Type: new Abstract: Large language models (LLMs) possess extensive world knowledge, yet methods for effectively eliciting this knowledge remain underexplored. Nationality and region prediction tasks require understanding of not only linguistic features but also cultural and historical backgr... | https://arxiv.org/abs/2601.12771 | Academic Papers | svg |
636031575d235058af40ddbaacc6c5dbc5588d2bdce6940d175e58e20ec2ab35 | 2026-01-21T00:00:00-05:00 | SDN-Blockchain Based Security Routing for UAV Communication via Reinforcement Learning | arXiv:2601.12774v1 Announce Type: new Abstract: The unmanned aerial vehicle (UAV) network plays important roles in emergency communications. However, it is challenging to design reliable routing strategies that ensure low latency, energy efficiency, and security in the dynamic and attack-prone environments. To this end... | https://arxiv.org/abs/2601.12774 | Academic Papers | svg |
e22f5f45c0a1b5474e707b9a76dd31009077d1adcb734be4515471fbb10aff1c | 2026-01-21T00:00:00-05:00 | Eddy-Resolving Global Ocean Forecasting with Multi-Scale Graph Neural Networks | arXiv:2601.12775v1 Announce Type: new Abstract: Research on data-driven ocean models has progressed rapidly in recent years; however, the application of these models to global eddy-resolving ocean forecasting remains limited. The accurate representation of ocean dynamics across a wide range of spatial scales remains a ... | https://arxiv.org/abs/2601.12775 | Academic Papers | svg |
dd47681b2287e094f0be31243125c971f73648601aad015ad1202ca3689f6b1c | 2026-01-21T00:00:00-05:00 | High-order Lagrange multiplier schemes for general Hamiltonian PDEs | arXiv:2601.12776v1 Announce Type: new Abstract: In this paper, we introduce a Lagrange multiplier approach to construct linearly implicit energy-preserving schemes of arbitrary order for general Hamiltonian PDEs. Unlike the widely used auxiliary variable methods, this novel approach does not require the nonlinear part ... | https://arxiv.org/abs/2601.12776 | Academic Papers | svg |
b6671e967d51a5134ab034f606c09b5f7edfae9cae512ce726c9f3ea98e534f8 | 2026-01-21T00:00:00-05:00 | Open Vocabulary Panoptic Segmentation With Retrieval Augmentation | arXiv:2601.12779v1 Announce Type: new Abstract: Given an input image and set of class names, panoptic segmentation aims to label each pixel in an image with class labels and instance labels. In comparison, Open Vocabulary Panoptic Segmentation aims to facilitate the segmentation of arbitrary classes according to user i... | https://arxiv.org/abs/2601.12779 | Academic Papers | svg |
ebdd86c61667ab972c40b4e68845c1e5dfd9892aaca7cdb6c7517305841694df | 2026-01-21T00:00:00-05:00 | Extended Gabidulin-Kronecker Product Codes and Their Application to Cryptosystems | arXiv:2601.12780v1 Announce Type: new Abstract: In this paper, we initiate the study of Extended Gabidulin codes with a Kronecker product structure and propose three enhanced variants of the Rank Quasi-Cyclic (RQC) (Melchor et.al., IEEE IT, 2018) cryptosystem. First, we establish precise bounds on the minimum rank dist... | https://arxiv.org/abs/2601.12780 | Academic Papers | svg |
35b82bd70aefb2f87ec666d96d2639de697d885babe681b7f6b83352d150c10e | 2026-01-21T00:00:00-05:00 | VIRO: Robust and Efficient Neuro-Symbolic Reasoning with Verification for Referring Expression Comprehension | arXiv:2601.12781v1 Announce Type: new Abstract: Referring Expression Comprehension (REC) aims to localize the image region corresponding to a natural-language query. Recent neuro-symbolic REC approaches leverage large language models (LLMs) and vision-language models (VLMs) to perform compositional reasoning, decomposi... | https://arxiv.org/abs/2601.12781 | Academic Papers | svg |
472e0655b116a110a09ced5e34e8bf039dea2cf1f8f6a490f85e39e5bea4bf85 | 2026-01-21T00:00:00-05:00 | Sensing-Limited Control of Noiseless Linear Systems Under Nonlinear Observations | arXiv:2601.12782v1 Announce Type: new Abstract: This paper investigates the fundamental information-theoretic limits for the control and sensing of noiseless linear dynamical systems subject to a broad class of nonlinear observations. We analyze the interactions between the control and sensing components by characteriz... | https://arxiv.org/abs/2601.12782 | Academic Papers | svg |
0c2776707da299f541dfff460b3745ffa927a945909c7445c4fc266ead8888f1 | 2026-01-21T00:00:00-05:00 | Unleashing Efficient Asynchronous RL Post-Training via Staleness-Constrained Rollout Coordination | arXiv:2601.12784v1 Announce Type: new Abstract: Reinforcement learning (RL) post-training has become pivotal for enhancing the capabilities of modern large models. A recent trend is to develop RL systems with a fully disaggregated architecture, which decouples the three RL phases (rollout, reward, and training) onto se... | https://arxiv.org/abs/2601.12784 | Academic Papers | svg |
d9501d7f5c896c3573f1921bd4dfb7d8f890bf706c99b0e8e20e2322f2fc8d03 | 2026-01-21T00:00:00-05:00 | Distilling Time Series Foundation Models for Efficient Forecasting | arXiv:2601.12785v1 Announce Type: new Abstract: Time Series foundation models (TSFMs) deliver strong forecasting performance through large-scale pretraining, but their large parameter sizes make deployment costly. While knowledge distillation offers a natural and effective approach for model compression, techniques dev... | https://arxiv.org/abs/2601.12785 | Academic Papers | svg |
1b9f5b18a53613dbd094ff18c0b79d0ed4a382be46888424ed6b6604e2e7fad8 | 2026-01-21T00:00:00-05:00 | DUAP: Dual-task Universal Adversarial Perturbations Against Voice Control Systems | arXiv:2601.12786v1 Announce Type: new Abstract: Modern Voice Control Systems (VCS) rely on the collaboration of Automatic Speech Recognition (ASR) and Speaker Recognition (SR) for secure interaction. However, prior adversarial attacks typically target these tasks in isolation, overlooking the coupled decision pipeline ... | https://arxiv.org/abs/2601.12786 | Academic Papers | svg |
fea2717f42333bcbb97b4947f9987dbc771d5cc5f45c10909a1b70a2f669e38a | 2026-01-21T00:00:00-05:00 | FocusNav: Spatial Selective Attention with Waypoint Guidance for Humanoid Local Navigation | arXiv:2601.12790v1 Announce Type: new Abstract: Robust local navigation in unstructured and dynamic environments remains a significant challenge for humanoid robots, requiring a delicate balance between long-range navigation targets and immediate motion stability. In this paper, we propose FocusNav, a spatial selective... | https://arxiv.org/abs/2601.12790 | Academic Papers | svg |
430040a0c7de5e70b6876104943aff38c801070f21741d96505aa9ca412d70e6 | 2026-01-21T00:00:00-05:00 | SKANet: A Cognitive Dual-Stream Framework with Adaptive Modality Fusion for Robust Compound GNSS Interference Classification | arXiv:2601.12791v1 Announce Type: new Abstract: As the electromagnetic environment becomes increasingly complex, Global Navigation Satellite Systems (GNSS) face growing threats from sophisticated jamming interference. Although Deep Learning (DL) effectively identifies basic interference, classifying compound interferen... | https://arxiv.org/abs/2601.12791 | Academic Papers | svg |
4be51f430ecc3db05a9d69612a1cbcb162acd2397d3ab2ddfe779cf2ace08ee7 | 2026-01-21T00:00:00-05:00 | Graph Laplacian assisted regularization method under noise level free heuristic and statistical stopping rule | arXiv:2601.12792v1 Announce Type: new Abstract: In this work, we address the solution of both linear and nonlinear ill-posed inverse problems by developing a novel graph-based regularization framework, where the regularization term is formulated through an iteratively updated graph Laplacian. The proposed approach oper... | https://arxiv.org/abs/2601.12792 | Academic Papers | svg |
cf1fd8314dc0138f4d0e90bb45d99c480803b1b47f863f21a7eee28049061b45 | 2026-01-21T00:00:00-05:00 | Two Frameworks and their Fourth Order Implicit Schemes for Time Discretization of Maxwell's Equations | arXiv:2601.12793v1 Announce Type: new Abstract: Our work is about energy conserving fourth-order time discretizations of a three-field formulation of Maxwell's equations in conjunction with a spatial discretization using higher-order and compatible de Rham finite element spaces. Toward this end, we delineate two broad ... | https://arxiv.org/abs/2601.12793 | Academic Papers | svg |
65c183433855ad03935a5f892892ca0692c9a20de29c98d9bccbd8506cbb9d3b | 2026-01-21T00:00:00-05:00 | Combating Noisy Labels through Fostering Self- and Neighbor-Consistency | arXiv:2601.12795v1 Announce Type: new Abstract: Label noise is pervasive in various real-world scenarios, posing challenges in supervised deep learning. Deep networks are vulnerable to such label-corrupted samples due to the memorization effect. One major stream of previous methods concentrates on identifying clean dat... | https://arxiv.org/abs/2601.12795 | Academic Papers | svg |
5ec9c1d4633cf6e513741306743410449c8635912db25301cecd6d0fb136db29 | 2026-01-21T00:00:00-05:00 | Contact-Aware Neural Dynamics | arXiv:2601.12796v1 Announce Type: new Abstract: High-fidelity physics simulation is essential for scalable robotic learning, but the sim-to-real gap persists, especially for tasks involving complex, dynamic, and discontinuous interactions like physical contacts. Explicit system identification, which tunes explicit simu... | https://arxiv.org/abs/2601.12796 | Academic Papers | svg |
c5624cc787b59dcfa02550139ebd679198567fa9cd23a7b11ef8a812e4811343 | 2026-01-21T00:00:00-05:00 | PhyG-MoE: A Physics-Guided Mixture-of-Experts Framework for Energy-Efficient GNSS Interference Recognition | arXiv:2601.12798v1 Announce Type: new Abstract: Complex electromagnetic interference increasingly compromises Global Navigation Satellite Systems (GNSS), threatening the reliability of Space-Air-Ground Integrated Networks (SAGIN). Although deep learning has advanced interference recognition, current static models suffe... | https://arxiv.org/abs/2601.12798 | Academic Papers | svg |
d4ac2fabd9860191281771ef6b30dc665fb5e02dc2c94704cacef7c518e100a8 | 2026-01-21T00:00:00-05:00 | FRoM-W1: Towards General Humanoid Whole-Body Control with Language Instructions | arXiv:2601.12799v1 Announce Type: new Abstract: Humanoid robots are capable of performing various actions such as greeting, dancing and even backflipping. However, these motions are often hard-coded or specifically trained, which limits their versatility. In this work, we present FRoM-W1, an open-source framework desig... | https://arxiv.org/abs/2601.12799 | Academic Papers | svg |
65e5dcc3c4cb0374dcd46f59e63f005d4e332c68a9b1b5655adbd50b8020cafa | 2026-01-21T00:00:00-05:00 | UNMIXX: Untangling Highly Correlated Singing Voices Mixtures | arXiv:2601.12802v1 Announce Type: new Abstract: We introduce UNMIXX, a novel framework for multiple singing voices separation (MSVS). While related to speech separation, MSVS faces unique challenges: data scarcity and the highly correlated nature of singing voices mixture. To address these issues, we propose UNMIXX wit... | https://arxiv.org/abs/2601.12802 | Academic Papers | svg |
fd94dc28341b467cd8dd3717ed57cb4a290d7c5b24ec2326620cd4d02ce4444e | 2026-01-21T00:00:00-05:00 | SL-CBM: Enhancing Concept Bottleneck Models with Semantic Locality for Better Interpretability | arXiv:2601.12804v1 Announce Type: new Abstract: Explainable AI (XAI) is crucial for building transparent and trustworthy machine learning systems, especially in high-stakes domains. Concept Bottleneck Models (CBMs) have emerged as a promising ante-hoc approach that provides interpretable, concept-level explanations by ... | https://arxiv.org/abs/2601.12804 | Academic Papers | svg |
7fb07a73f3303ad287381262f3314db32082681cd21f9f55ef1df9b4cad4d222 | 2026-01-21T00:00:00-05:00 | Semi-supervised Instruction Tuning for Large Language Models on Text-Attributed Graphs | arXiv:2601.12807v1 Announce Type: new Abstract: The emergent reasoning capabilities of Large Language Models (LLMs) offer a transformative paradigm for analyzing text-attributed graphs. While instruction tuning is the prevailing method for adapting pre-trained LLMs to graph learning tasks like node classification, it r... | https://arxiv.org/abs/2601.12807 | Academic Papers | svg |
b32a8ac5a7aa4b75e605129e1906b6317929790a370360cbeedb059bcf91d222 | 2026-01-21T00:00:00-05:00 | Joint Source-Channel-Generation Coding: From Distortion-oriented Reconstruction to Semantic-consistent Generation | arXiv:2601.12808v1 Announce Type: new Abstract: Conventional communication systems, including both separation-based coding and AI-driven joint source-channel coding (JSCC), are largely guided by Shannon's rate-distortion theory. However, relying on generic distortion metrics fails to capture complex human visual percep... | https://arxiv.org/abs/2601.12808 | Academic Papers | svg |
b6ebadf380b4cf99dcf28034a7b032db62b41d320251d820a944792c3f8aa00e | 2026-01-21T00:00:00-05:00 | Left-Right Symmetry Breaking in CLIP-style Vision-Language Models Trained on Synthetic Spatial-Relation Data | arXiv:2601.12809v1 Announce Type: new Abstract: Spatial understanding remains a key challenge in vision-language models. Yet it is still unclear whether such understanding is truly acquired, and if so, through what mechanisms. We present a controllable 1D image-text testbed to probe how left-right relational understand... | https://arxiv.org/abs/2601.12809 | Academic Papers | svg |
0e856bc06f48eb87d443589a1e2f10374a01193fc879a09c3a33b15d55ea62ae | 2026-01-21T00:00:00-05:00 | Docker Does Not Guarantee Reproducibility | arXiv:2601.12811v1 Announce Type: new Abstract: The reproducibility of software environments is a critical concern in modern software engineering, with ramifications ranging from the effectiveness of collaboration workflows to software supply chain security and scientific reproducibility. Containerization technologies ... | https://arxiv.org/abs/2601.12811 | Academic Papers | svg |
77ea147b0771c527dba01cd6817dcf0eca6c42f2b1bf8458f195a81f7b38abce | 2026-01-21T00:00:00-05:00 | Do Clinical Question Answering Systems Really Need Specialised Medical Fine Tuning? | arXiv:2601.12812v1 Announce Type: new Abstract: Clinical Question-Answering (CQA) industry systems are increasingly rely on Large Language Models (LLMs), yet their deployment is often guided by the assumption that domain-specific fine-tuning is essential. Although specialised medical LLMs such as BioBERT, BioGPT, and P... | https://arxiv.org/abs/2601.12812 | Academic Papers | svg |
a06808b5d522539f1c26fa428a61c08259d064d65b9331d6e4e6d07fed407f98 | 2026-01-21T00:00:00-05:00 | A Formally Verified Procedure for Width Inference in FIRRTL | arXiv:2601.12813v1 Announce Type: new Abstract: FIRRTL is an intermediate representation language for Register Transfer Level (RTL) hardware designs. In FIRRTL programs, the bit widths of many components are not specified explicitly and must be inferred during compilation. In mainstream FIRRTL compilers, such as the of... | https://arxiv.org/abs/2601.12813 | Academic Papers | svg |
58a35a8f373bfba79fb4b68210121addb3f25650297176538c6f125fe5766819 | 2026-01-21T00:00:00-05:00 | CSGaussian: Progressive Rate-Distortion Compression and Segmentation for 3D Gaussian Splatting | arXiv:2601.12814v1 Announce Type: new Abstract: We present the first unified framework for rate-distortion-optimized compression and segmentation of 3D Gaussian Splatting (3DGS). While 3DGS has proven effective for both real-time rendering and semantic scene understanding, prior works have largely treated these tasks i... | https://arxiv.org/abs/2601.12814 | Academic Papers | svg |
24b3e13cb1808a0a680c9c585442bab770698378b400aac0e5dc290b295e5b2d | 2026-01-21T00:00:00-05:00 | Multimodal Multi-Agent Empowered Legal Judgment Prediction | arXiv:2601.12815v1 Announce Type: new Abstract: Legal Judgment Prediction (LJP) aims to predict the outcomes of legal cases based on factual descriptions, serving as a fundamental task to advance the development of legal systems. Traditional methods often rely on statistical analyses or role-based simulations but face ... | https://arxiv.org/abs/2601.12815 | Academic Papers | svg |
6780ba1af4d29ca7847343d0a549dc651df8e103b3d597a016777b9e716ca17a | 2026-01-21T00:00:00-05:00 | Fisher-Orthogonal Projected Natural Gradient Descent for Continual Learning | arXiv:2601.12816v1 Announce Type: new Abstract: Continual learning aims to enable neural networks to acquire new knowledge on sequential tasks. However, the key challenge in such settings is to learn new tasks without catastrophically forgetting previously learned tasks. We propose the Fisher-Orthogonal Projected Natur... | https://arxiv.org/abs/2601.12816 | Academic Papers | svg |
2229c253b2670eb7176730c48eed83b22e0e2e6b83955dab09199214002a3b60 | 2026-01-21T00:00:00-05:00 | A Generalist Foundation Model for Total-body PET/CT Enables Diagnostic Reporting and System-wide Metabolic Profiling | arXiv:2601.12820v1 Announce Type: new Abstract: Total-body PET/CT enables system-wide molecular imaging, but heterogeneous anatomical and metabolic signals, approximately 2 m axial coverage, and structured radiology semantics challenge existing medical AI models that assume single-modality inputs, localized fields of v... | https://arxiv.org/abs/2601.12820 | Academic Papers | svg |
0d9cac2b51a978a55abe7ef8ee6b3aba565cad2b27a53961fe8c35555bf81f78 | 2026-01-21T00:00:00-05:00 | MirrorGuard: Toward Secure Computer-Use Agents via Simulation-to-Real Reasoning Correction | arXiv:2601.12822v1 Announce Type: new Abstract: Large foundation models are integrated into Computer Use Agents (CUAs), enabling autonomous interaction with operating systems through graphical user interfaces (GUIs) to perform complex tasks. This autonomy introduces serious security risks: malicious instructions or vis... | https://arxiv.org/abs/2601.12822 | Academic Papers | svg |
4fb28dcdb3f4642b8f6a0a117f2ce4ff2a8247aacd6ba484005900b34c8f41dc | 2026-01-21T00:00:00-05:00 | TreeDGS: Aerial Gaussian Splatting for Distant DBH Measurement | arXiv:2601.12823v1 Announce Type: new Abstract: Aerial remote sensing enables efficient large-area surveying, but accurate direct object-level measurement remains difficult in complex natural scenes. Recent advancements in 3D vision, particularly learned radiance-field representations such as NeRF and 3D Gaussian Splat... | https://arxiv.org/abs/2601.12823 | Academic Papers | svg |
da015ed51e1a8c40106bbadba6ccb3fb9838628b5aaf70022fc10346beed0945 | 2026-01-21T00:00:00-05:00 | Seeing Isn't Always Believing: Analysis of Grad-CAM Faithfulness and Localization Reliability in Lung Cancer CT Classification | arXiv:2601.12826v1 Announce Type: new Abstract: Explainable Artificial Intelligence (XAI) techniques, such as Gradient-weighted Class Activation Mapping (Grad-CAM), have become indispensable for visualizing the reasoning process of deep neural networks in medical image analysis. Despite their popularity, the faithfulne... | https://arxiv.org/abs/2601.12826 | Academic Papers | svg |
0f3ecd77cd1bc293061349369b0525650b153c21b66f8e527ddeca6a6651a3d4 | 2026-01-21T00:00:00-05:00 | The Unfairness of Multifactorial Bias in Recommendation | arXiv:2601.12828v1 Announce Type: new Abstract: Popularity bias and positivity bias are two prominent sources of bias in recommender systems. Both arise from input data, propagate through recommendation models, and lead to unfair or suboptimal outcomes. Popularity bias occurs when a small subset of items receives most ... | https://arxiv.org/abs/2601.12828 | Academic Papers | svg |
e045135365ef7e6bb45fd7b9de773b544bb5f992927143c2d9d3be4b6f1624e3 | 2026-01-21T00:00:00-05:00 | From Design to Deorbit: A Solar-Electric Autonomous Module for Multi-Debris Remediation | arXiv:2601.12830v1 Announce Type: new Abstract: The escalating accumulation of orbital debris threatens the sustainability of space operations, necessitating active removal solutions that overcome the limitations of current fuel-dependent methods. To address this, this study introduces a novel remediation architecture ... | https://arxiv.org/abs/2601.12830 | Academic Papers | svg |
2c53c868c9ccee7bfd58a0257d4ce3df29e14d0194f276afcd8d670b4f133691 | 2026-01-21T00:00:00-05:00 | Data-Consistent Learning of Inverse Problems | arXiv:2601.12831v1 Announce Type: new Abstract: Inverse problems are inherently ill-posed, suffering from non-uniqueness and instability. Classical regularization methods provide mathematically well-founded solutions, ensuring stability and convergence, but often at the cost of reduced flexibility or visual quality. Le... | https://arxiv.org/abs/2601.12831 | Academic Papers | svg |
a93e43bb2589aed6735c7acad31ad4aef248a003189ef4a79b565a6a1e52ddd0 | 2026-01-21T00:00:00-05:00 | Temporal Fair Division of Indivisible Goods with Scheduling | arXiv:2601.12835v1 Announce Type: new Abstract: We study temporal fair division, where agents receive goods over multiple rounds and cumulative fairness is required. We investigate Temporal Envy-Freeness Up to One Good (TEF1) and Up to Any Good (TEFX), its approximation $\alpha$-TEFX, and Temporal Maximin Share (TMMS).... | https://arxiv.org/abs/2601.12835 | Academic Papers | svg |
a5cdc042a4b9cd21ce50a6e0db4bc87c59954e065660857fbbe82afc9f2cea06 | 2026-01-21T00:00:00-05:00 | Knowledge-Integrated Representation Learning for Crypto Anomaly Detection under Extreme Label Scarcity; Relational Domain-Logic Integration with Retrieval-Grounded Context and Path-Level Explanations | arXiv:2601.12839v1 Announce Type: new Abstract: Detecting anomalous trajectories in decentralized crypto networks is fundamentally challenged by extreme label scarcity and the adaptive evasion strategies of illicit actors. While Graph Neural Networks (GNNs) effectively capture local structural patterns, they struggle t... | https://arxiv.org/abs/2601.12839 | Academic Papers | svg |
f9c037702c4e647f6419a07cd64e40d13d0a4a306becd23b9cf0bfc18d041ddb | 2026-01-21T00:00:00-05:00 | Lessons Learned from Structural Design and Vibration Testing of 50-kg Microsatellites Deployed from the International Space Station | arXiv:2601.12840v1 Announce Type: new Abstract: Hokkaido University and Tohoku University have been developing and operating a constellation of 50-cm-class microsatellites for Earth observation. DIWATA-1, launched in 2016, was deployed into a circular orbit at an altitude of approximately 400 km from the International ... | https://arxiv.org/abs/2601.12840 | Academic Papers | svg |
4e80dcb43bed6a0029c54e1f34d51843c8b7e6a6922530d64ac8a6fdf440beda | 2026-01-21T00:00:00-05:00 | SCULPT: Constraint-Guided Pruned MCTS that Carves Efficient Paths for Mathematical Reasoning | arXiv:2601.12842v1 Announce Type: new Abstract: Automated agent workflows can enhance the problem-solving ability of large language models (LLMs), but common search strategies rely on stochastic exploration and often traverse implausible branches. This occurs because current pipelines sample candidate steps from generi... | https://arxiv.org/abs/2601.12842 | Academic Papers | svg |
b2436c844be7519efd440e50bfbd61d918fdf6089919cbdd997e1a44a5b053ae | 2026-01-21T00:00:00-05:00 | Rapport du Projet de Recherche TRAIMA | arXiv:2601.12844v1 Announce Type: new Abstract: The TRAIMA project (TRaitement Automatique des Interactions Multimodales en Apprentissage), conducted between March 2019 and June 2020, investigates the potential of automatic processing of multimodal interactions in educational settings. The project addresses a central m... | https://arxiv.org/abs/2601.12844 | Academic Papers | svg |
518c7b17b0e2f17a3b04044a463397b912524cc337da593713576f59d35d3940 | 2026-01-21T00:00:00-05:00 | Automatic Generation of Formal Specification and Verification Annotations Using LLMs and Test Oracles | arXiv:2601.12845v1 Announce Type: new Abstract: Recent verification tools aim to make formal verification more accessible to software engineers by automating most of the verification process. However, annotating conventional programs with the formal specification and verification constructs (preconditions, postconditio... | https://arxiv.org/abs/2601.12845 | Academic Papers | svg |
14e545bda43358e25a31849c81d65509b835125da5b6b3e243c52faab0fcd43d | 2026-01-21T00:00:00-05:00 | The Cost of EFX: Generalized-Mean Welfare and Complexity Dichotomies with Few Surplus Items | arXiv:2601.12849v1 Announce Type: new Abstract: Envy-freeness up to any good (EFX) is a central fairness notion for allocating indivisible goods, yet its existence is unresolved in general. In the setting with few surplus items, where the number of goods exceeds the number of agents by a small constant (at most three),... | https://arxiv.org/abs/2601.12849 | Academic Papers | svg |
a4a3a1433d5587d7cf66e3bf2ee501f7ed1535ba390d39827dc07fd4c19d650d | 2026-01-21T00:00:00-05:00 | System Analysis and Pre-Flight Evaluation of Deployable Solar Panels for 3U CubeSat HOKUSHIN-1 | arXiv:2601.12851v1 Announce Type: new Abstract: This paper describes the system design methodology derived from the development and evaluation tests of deployable solar panels to be mounted on a 3U CubeSat. The study mainly includes structural analysis, thermal analysis, and a review of vibration test results. Hokkaido... | https://arxiv.org/abs/2601.12851 | Academic Papers | svg |
e4fdebbda71b137987914258d16035dd434dae5d977d47b750b95e016a040e44 | 2026-01-21T00:00:00-05:00 | On Resilient and Efficient Linear Secure Aggregation in Hierarchical Federated Learning | arXiv:2601.12853v1 Announce Type: new Abstract: In this paper, we study the fundamental limits of hierarchical secure aggregation under unreliable communication. We consider a hierarchical network where each client connects to multiple relays, and both client-to-relay and relay-to-server links are intermittent. Under t... | https://arxiv.org/abs/2601.12853 | Academic Papers | svg |
d889067fee3bbbea0ba6779b76162b9edded13415ba02260a9bd72d1252a21cb | 2026-01-21T00:00:00-05:00 | Mining Citywide Dengue Spread Patterns in Singapore Through Hotspot Dynamics from Open Web Data | arXiv:2601.12856v1 Announce Type: new Abstract: Dengue, a mosquito-borne disease, continues to pose a persistent public health challenge in urban areas, particularly in tropical regions such as Singapore. Effective and affordable control requires anticipating where transmission risks are likely to emerge so that interv... | https://arxiv.org/abs/2601.12856 | Academic Papers | svg |
c9ad4128dece44ac66fb55465100eefdc5c7cc956cb1a94b482d41bbcdcfc6be | 2026-01-21T00:00:00-05:00 | Report on Earth Observation Missions and Ground Station Management using On-Demand Satellite Operation System | arXiv:2601.12857v1 Announce Type: new Abstract: Since the launch of its first satellite in 2009, Tohoku University has continuously developed and operated Earth observation satellites and engineering demonstration satellites in the 50cm-class and CubeSat-class (up to 3U). The 50cm-class satellite launched into operatio... | https://arxiv.org/abs/2601.12857 | Academic Papers | svg |
cf2903b0125e9bfe4667d561c7e692e144e16ca9294e752055714fc4322a5ad8 | 2026-01-21T00:00:00-05:00 | Generating Cyclic Conformers with Flow Matching in Cremer-Pople Coordinates | arXiv:2601.12859v1 Announce Type: new Abstract: Cyclic molecules are ubiquitous across applications in chemistry and biology. Their restricted conformational flexibility provides structural pre-organization that is key to their function in drug discovery and catalysis. However, reliably sampling the conformer ensembles... | https://arxiv.org/abs/2601.12859 | Academic Papers | svg |
f3c0029c3b621b838db6edd35962b4cd9ac118bd045be484c2b67782098c0434 | 2026-01-21T00:00:00-05:00 | FGTBT: Frequency-Guided Task-Balancing Transformer for Unified Facial Landmark Detection | arXiv:2601.12863v1 Announce Type: new Abstract: Recently, deep learning based facial landmark detection (FLD) methods have achieved considerable success. However, in challenging scenarios such as large pose variations, illumination changes, and facial expression variations, they still struggle to accurately capture the... | https://arxiv.org/abs/2601.12863 | Academic Papers | svg |
bc30de5d72f34ad2073b8bcdffc85b72376e0b654867ee6867e8991b85420f64 | 2026-01-21T00:00:00-05:00 | Proxy Robustness in Vision Language Models is Effortlessly Transferable | arXiv:2601.12865v1 Announce Type: new Abstract: As a pivotal technique for improving the defense of deep models, adversarial robustness transfer via distillation has demonstrated remarkable success in conventional image classification tasks. However, this paradigm encounters critical challenges when applied to vision-l... | https://arxiv.org/abs/2601.12865 | Academic Papers | svg |
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