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92ee318350b4bf7d1f787e8bf00a24d575331f053fb45fbc72993f4414dfd561 | 2026-01-21T00:00:00-05:00 | A BERTology View of LLM Orchestrations: Token- and Layer-Selective Probes for Efficient Single-Pass Classification | arXiv:2601.13288v1 Announce Type: new Abstract: Production LLM systems often rely on separate models for safety and other classification-heavy steps, increasing latency, VRAM footprint, and operational complexity. We instead reuse computation already paid for by the serving LLM: we train lightweight probes on its hidde... | https://arxiv.org/abs/2601.13288 | Academic Papers | svg |
00f9450e369fcd5afd9051322123d0543f8ece7b38254229cf72f00fa410f352 | 2026-01-21T00:00:00-05:00 | The Tag is the Signal: URL-Agnostic Credibility Scoring for Messages on Telegram | arXiv:2601.13294v1 Announce Type: new Abstract: Telegram has become one of the leading platforms for disseminating misinformational messages. However, many existing pipelines still classify each message's credibility based on the reputation of its associated domain names or its lexical features. Such methods work well ... | https://arxiv.org/abs/2601.13294 | Academic Papers | svg |
273ece4e73d99592b1f377e734af6c0d6028103ae6f5dd995c63eab5b9ae9c2e | 2026-01-21T00:00:00-05:00 | CooperBench: Why Coding Agents Cannot be Your Teammates Yet | arXiv:2601.13295v1 Announce Type: new Abstract: Resolving team conflicts requires not only task-specific competence, but also social intelligence to find common ground and build consensus. As AI agents increasingly collaborate on complex work, they must develop coordination capabilities to function as effective teammat... | https://arxiv.org/abs/2601.13295 | Academic Papers | svg |
f586a4c90eaa6b580f9cc46526798125b72643e7feec830d1329186fa194212f | 2026-01-21T00:00:00-05:00 | Enginuity: Building an Open Multi-Domain Dataset of Complex Engineering Diagrams | arXiv:2601.13299v1 Announce Type: new Abstract: We propose Enginuity - the first open, large-scale, multi-domain engineering diagram dataset with comprehensive structural annotations designed for automated diagram parsing. By capturing hierarchical component relationships, connections, and semantic elements across dive... | https://arxiv.org/abs/2601.13299 | Academic Papers | svg |
d87a326ee658fe5553121eb079707e871fc5a77008131be7cce259cfcea39515 | 2026-01-21T00:00:00-05:00 | OI-Bench: An Option Injection Benchmark for Evaluating LLM Susceptibility to Directive Interference | arXiv:2601.13300v1 Announce Type: new Abstract: Benchmarking large language models (LLMs) is critical for understanding their capabilities, limitations, and robustness. In addition to interface artifacts, prior studies have shown that LLM decisions can be influenced by directive signals such as social cues, framing, an... | https://arxiv.org/abs/2601.13300 | Academic Papers | svg |
0da895c3aaf5fff580a59f90d0a9afb17e06ff9cbf99a4cfa934b17c83b1a4b5 | 2026-01-21T00:00:00-05:00 | Verifying Local Robustness of Pruned Safety-Critical Networks | arXiv:2601.13303v1 Announce Type: new Abstract: Formal verification of Deep Neural Networks (DNNs) is essential for safety-critical applications, ranging from surgical robotics to NASA JPL autonomous systems. However, the computational cost of verifying large-scale models remains a significant barrier to adoption. This... | https://arxiv.org/abs/2601.13303 | Academic Papers | svg |
b5819ec6dcc2e6033a28c466046dd87bcd8379f6904a7e6873f7dacc0973f025 | 2026-01-21T00:00:00-05:00 | CausalSpatial: A Benchmark for Object-Centric Causal Spatial Reasoning | arXiv:2601.13304v1 Announce Type: new Abstract: Humans can look at a static scene and instantly predict what happens next -- will moving this object cause a collision? We call this ability Causal Spatial Reasoning. However, current multimodal large language models (MLLMs) cannot do this, as they remain largely restrict... | https://arxiv.org/abs/2601.13304 | Academic Papers | svg |
636f23b6aecc9c7af781bf1205a93ac448cd0073dd759acc4404c13546560d38 | 2026-01-21T00:00:00-05:00 | Paid Voices vs. Public Feeds: Interpretable Cross-Platform Theme Modeling of Climate Discourse | arXiv:2601.13317v1 Announce Type: new Abstract: Climate discourse online plays a crucial role in shaping public understanding of climate change and influencing political and policy outcomes. However, climate communication unfolds across structurally distinct platforms with fundamentally different incentive structures: ... | https://arxiv.org/abs/2601.13317 | Academic Papers | svg |
5fdd9b43f96977bf5aee7eda3b6f4b360d7aed7c9d54377e4bd7e9d782ceb160 | 2026-01-21T00:00:00-05:00 | Arab Voices: Mapping Standard and Dialectal Arabic Speech Technology | arXiv:2601.13319v1 Announce Type: new Abstract: Dialectal Arabic (DA) speech data vary widely in domain coverage, dialect labeling practices, and recording conditions, complicating cross-dataset comparison and model evaluation. To characterize this landscape, we conduct a computational analysis of linguistic ``dialectn... | https://arxiv.org/abs/2601.13319 | Academic Papers | svg |
220383102246c26c8efd12c7d9c1d07eae2194a1aa524c0fd9af89d2f7021e17 | 2026-01-21T00:00:00-05:00 | Verifying First-Order Temporal Properties of Infinite-State Systems via Timers and Rankings | arXiv:2601.13325v1 Announce Type: new Abstract: We present a unified deductive verification framework for first-order temporal properties based on well-founded rankings, where verification conditions are discharged using SMT solvers. To that end, we introduce a novel reduction from verification of arbitrary temporal pr... | https://arxiv.org/abs/2601.13325 | Academic Papers | svg |
fd4baeeec417ab379b9004ec44c5c5947d1323fe3df5024c6d9a1ee45bcdf050 | 2026-01-21T00:00:00-05:00 | PepEDiff: Zero-Shot Peptide Binder Design via Protein Embedding Diffusion | arXiv:2601.13327v1 Announce Type: new Abstract: We present PepEDiff, a novel peptide binder generator that designs binding sequences given a target receptor protein sequence and its pocket residues. Peptide binder generation is critical in therapeutic and biochemical applications, yet many existing methods rely heavily... | https://arxiv.org/abs/2601.13327 | Academic Papers | svg |
c937dd243560591c88009d2f8bbfcc9cc2d95ed1ba668e09e5188519a928e9a0 | 2026-01-21T00:00:00-05:00 | Reducing Tokenization Premiums for Low-Resource Languages | arXiv:2601.13328v1 Announce Type: new Abstract: Relative to English, low-resource languages suffer from substantial tokenization premiums in modern LMs, meaning that it generally requires several times as many tokens to encode a sentence in a low-resource language than to encode the analogous sentence in English. This ... | https://arxiv.org/abs/2601.13328 | Academic Papers | svg |
0120d17827ea939309ffebb534e687cc3fe0a2ff37b671269eeee4e032e0edab | 2026-01-21T00:00:00-05:00 | RegCheck: A tool for automating comparisons between study registrations and papers | arXiv:2601.13330v1 Announce Type: new Abstract: Across the social and medical sciences, researchers recognize that specifying planned research activities (i.e., 'registration') prior to the commencement of research has benefits for both the transparency and rigour of science. Despite this, evidence suggests that study ... | https://arxiv.org/abs/2601.13330 | Academic Papers | svg |
6f170ca4148dfdfdf835e174b74f5689bddf3d47b7d24e2d20366151f59064e3 | 2026-01-21T00:00:00-05:00 | MultiST: A Cross-Attention-Based Multimodal Model for Spatial Transcriptomic | arXiv:2601.13331v1 Announce Type: new Abstract: Spatial transcriptomics (ST) enables transcriptome-wide profiling while preserving the spatial context of tissues, offering unprecedented opportunities to study tissue organization and cell-cell interactions in situ. Despite recent advances, existing methods often lack ef... | https://arxiv.org/abs/2601.13331 | Academic Papers | svg |
788d63aa580eeeb37532ccc663cf3a4202efb50e10aa5a3ea6349e3ae89b7ad3 | 2026-01-21T00:00:00-05:00 | SEER: Spectral Entropy Encoding of Roles for Context-Aware Attention-Based Design Pattern Detection | arXiv:2601.13334v1 Announce Type: new Abstract: This paper presents SEER, an upgraded version of our prior method Context Is All You Need for detecting Gang of Four (GoF) design patterns from source code. The earlier approach modeled code as attention-ready sequences that blended lightweight structure with behavioral c... | https://arxiv.org/abs/2601.13334 | Academic Papers | svg |
c7164b52216f63703505782e10518e2fc9fdc5717a1ee0c0dcfa9cfd8a9cc31b | 2026-01-21T00:00:00-05:00 | Towards Natural Language Environment: Understanding Seamless Natural-Language-Based Human-Multi-Robot Interactions | arXiv:2601.13338v1 Announce Type: new Abstract: As multiple robots are expected to coexist in future households, natural language is increasingly envisioned as a primary medium for human-robot and robot-robot communication. This paper introduces the concept of a Natural Language Environment (NLE), defined as an interac... | https://arxiv.org/abs/2601.13338 | Academic Papers | svg |
6ca0baf0898b7f2546fb0c82dd8922db0895a0974f4f6a0b82a74bfddcb1e155 | 2026-01-21T00:00:00-05:00 | Reduction for Structured Concurrent Programs | arXiv:2601.13341v1 Announce Type: new Abstract: Commutativity reasoning based on Lipton's movers is a powerful technique for verification of concurrent programs. The idea is to define a program transformation that preserves a subset of the initial set of interleavings, which is sound modulo reorderings of commutative a... | https://arxiv.org/abs/2601.13341 | Academic Papers | svg |
de4d295ba17d8ed22f50453f202de113a83b2def2256a9e052a11bcae56d63a3 | 2026-01-21T00:00:00-05:00 | Privacy Starts with UI: Privacy Patterns and Designer Perspectives in UI/UX Practice | arXiv:2601.13342v1 Announce Type: new Abstract: In the study of Human-Computer Interaction, privacy is often seen as a core issue, and it has been explored directly in connection with User Interface (UI) and User Experience (UX) design. We systematically investigate the key considerations and factors for privacy in UI/... | https://arxiv.org/abs/2601.13342 | Academic Papers | svg |
93d5168cc3c27e3adc878794164c7e47e71ea94aa7a81070dec72c260435c3e6 | 2026-01-21T00:00:00-05:00 | The Words That Can't Be Shared: Exploring the Design of Unsent Messages | arXiv:2601.13343v1 Announce Type: new Abstract: People often have things they want to say but hold back in conversations, fearing vulnerability or social consequences. Online, this restraint can take a distinctive form: even when such thoughts are written out - in moments of anger, guilt, or longing - people may choose... | https://arxiv.org/abs/2601.13343 | Academic Papers | svg |
2b87ccf56466fe7d0fb1de946a64eff6a28f4dc4449260d6a3afba7576691cd9 | 2026-01-21T00:00:00-05:00 | FlipFlop: A Static Analysis-based Energy Optimization Framework for GPU Kernels | arXiv:2601.13345v1 Announce Type: new Abstract: Artificial Intelligence (AI) applications, such as Large Language Models, are primarily driven and executed by Graphics Processing Units (GPUs). These GPU programs (kernels) consume substantial amounts of energy, yet software developers often lack the hardware expertise a... | https://arxiv.org/abs/2601.13345 | Academic Papers | svg |
4c472bd16a90af4109364dcfa5ad38297e4fa64c173596fde3cb23e126f1ac71 | 2026-01-21T00:00:00-05:00 | AfroScope: A Framework for Studying the Linguistic Landscape of Africa | arXiv:2601.13346v1 Announce Type: new Abstract: Language Identification (LID) is the task of determining the language of a given text and is a fundamental preprocessing step that affects the reliability of downstream NLP applications. While recent work has expanded LID coverage for African languages, existing approache... | https://arxiv.org/abs/2601.13346 | Academic Papers | svg |
dd208c96070807c40ad0710e5d987800a86faefdd3e0cead8e8ba5da08bcd4e1 | 2026-01-21T00:00:00-05:00 | A Scalable Sequential Framework for Dynamic Inverse Problems via Model Parameter Estimation | arXiv:2601.13347v1 Announce Type: new Abstract: Large-scale dynamic inverse problems are often ill-posed due to model complexity and the high dimensionality of the unknown parameters. Regularization is commonly employed to mitigate ill-posedness by incorporating prior information and structural constraints. However, cl... | https://arxiv.org/abs/2601.13347 | Academic Papers | svg |
29d3f50fbaed18fd428a480605cbbf4c16c9ad58b9c29d95acbf92a72e6ba9c7 | 2026-01-21T00:00:00-05:00 | The AI Genie Phenomenon and Three Types of AI Chatbot Addiction: Escapist Roleplays, Pseudosocial Companions, and Epistemic Rabbit Holes | arXiv:2601.13348v1 Announce Type: new Abstract: Recent reports on generative AI chatbot use raise concerns about its addictive potential. An in-depth understanding is imperative to minimize risks, yet AI chatbot addiction remains poorly understood. This study examines how to characterize AI chatbot addiction--why users... | https://arxiv.org/abs/2601.13348 | Academic Papers | svg |
c684a3fff5b21a59307529a6d7138e1adb3a9f9026367bd89ccc0b0be021a40c | 2026-01-21T00:00:00-05:00 | Beyond Mapping : Domain-Invariant Representations via Spectral Embedding of Optimal Transport Plans | arXiv:2601.13350v1 Announce Type: new Abstract: Distributional shifts between training and inference time data remain a central challenge in machine learning, often leading to poor performance. It motivated the study of principled approaches for domain alignment, such as optimal transport based unsupervised domain adap... | https://arxiv.org/abs/2601.13350 | Academic Papers | svg |
cf3813fa64a9fa4c10d987a3950ae2102140372a6dd9643aebd5a27a5c950c43 | 2026-01-21T00:00:00-05:00 | Towards Scalable Federated Container Orchestration: The CODECO Approach | arXiv:2601.13351v1 Announce Type: new Abstract: This paper presents CODECO, a federated orchestration framework for Kubernetes that addresses the limitations of cloud-centric deployment. CODECO adopts a data-compute-network co-orchestration approach to support heterogeneous infrastructures, mobility, and multi-provider... | https://arxiv.org/abs/2601.13351 | Academic Papers | svg |
8699c96aca5f758fabaac927e5af31e8f8cc4acfe376e367980a2dc63aa41fc2 | 2026-01-21T00:00:00-05:00 | LLM-as-RNN: A Recurrent Language Model for Memory Updates and Sequence Prediction | arXiv:2601.13352v1 Announce Type: new Abstract: Large language models are strong sequence predictors, yet standard inference relies on immutable context histories. After making an error at generation step t, the model lacks an updatable memory mechanism that improves predictions for step t+1. We propose LLM-as-RNN, an ... | https://arxiv.org/abs/2601.13352 | Academic Papers | svg |
88e10e762eec268f7b77b7142fb941090727486bfb3225f1d05df6c674ce04b9 | 2026-01-21T00:00:00-05:00 | Guidelines for the Creation of an Annotated Corpus | arXiv:2601.13353v1 Announce Type: new Abstract: This document, based on feedback from UMR TETIS members and the scientific literature, provides a generic methodology for creating annotation guidelines and annotated textual datasets (corpora). It covers methodological aspects, as well as storage, sharing, and valorizati... | https://arxiv.org/abs/2601.13353 | Academic Papers | svg |
c5d15e04793edaa9f80c679e11a091c2baad41dfa5f4aa764efbed2b6a64edab | 2026-01-21T00:00:00-05:00 | Remote Triggers: Misophonia, Technology Non-Use, and Design for Inclusive Digital Spaces | arXiv:2601.13355v1 Announce Type: new Abstract: Misophonia, characterized by intense negative reactions to specific sounds or related visual cues, remains poorly recognized in clinical settings yet profoundly affects daily life. This study examines how individuals with misophonia experience and sometimes avoid technolo... | https://arxiv.org/abs/2601.13355 | Academic Papers | svg |
9df5ff7b7dfbfa0e8e42022c990e87e701656006ed3660d458a908a9e60b610a | 2026-01-21T00:00:00-05:00 | On the Relation of State Space Models and Hidden Markov Models | arXiv:2601.13357v1 Announce Type: new Abstract: State Space Models (SSMs) and Hidden Markov Models (HMMs) are foundational frameworks for modeling sequential data with latent variables and are widely used in signal processing, control theory, and machine learning. Despite their shared temporal structure, they differ fu... | https://arxiv.org/abs/2601.13357 | Academic Papers | svg |
acb6b2a7e4118b9d4316bb5a0a78aec6384cbc786d667e1b466c241d0a68a909 | 2026-01-21T00:00:00-05:00 | The Geometry of Thought: How Scale Restructures Reasoning In Large Language Models | arXiv:2601.13358v1 Announce Type: new Abstract: Scale does not uniformly improve reasoning - it restructures it. Analyzing 25,000+ chain-of-thought trajectories across four domains (Law, Science, Code, Math) and two scales (8B, 70B parameters), we discover that neural scaling laws trigger domain-specific phase transiti... | https://arxiv.org/abs/2601.13358 | Academic Papers | svg |
5f7bca5929c786998e8bc544e92b198616d4f03b6cb600a7bde02c75d1332fbe | 2026-01-21T00:00:00-05:00 | Sockpuppetting: Jailbreaking LLMs Without Optimization Through Output Prefix Injection | arXiv:2601.13359v1 Announce Type: new Abstract: As open-weight large language models (LLMs) increase in capabilities, safeguarding them against malicious prompts and understanding possible attack vectors becomes ever more important. While automated jailbreaking methods like GCG [Zou et al., 2023] remain effective, they... | https://arxiv.org/abs/2601.13359 | Academic Papers | svg |
7fc766a69a3bd8ce0199a679a56ad123b75a9f4eaea160ce6ef31d8a049c7715 | 2026-01-21T00:00:00-05:00 | CLEAR: A Semantic-Geometric Terrain Abstraction for Large-Scale Unstructured Environments | arXiv:2601.13361v1 Announce Type: new Abstract: Long-horizon navigation in unstructured environments demands terrain abstractions that scale to tens of km$^2$ while preserving semantic and geometric structure, a combination existing methods fail to achieve. Grids scale poorly; quadtrees misalign with terrain boundaries... | https://arxiv.org/abs/2601.13361 | Academic Papers | svg |
3e30e1c91d736e7748c89c40a65a981e2a062545198aee46d5ed755d5df62c30 | 2026-01-21T00:00:00-05:00 | Real-Time 4D Radar Perception for Robust Human Detection in Harsh Enclosed Environments | arXiv:2601.13364v1 Announce Type: new Abstract: This paper introduces a novel methodology for generating controlled, multi-level dust concentrations in a highly cluttered environment representative of harsh, enclosed environments, such as underground mines, road tunnels, or collapsed buildings, enabling repeatable mm-w... | https://arxiv.org/abs/2601.13364 | Academic Papers | svg |
2fdcba0f100c28a330bafb9378d37be88845481219d620419d0a2270d4c8e921 | 2026-01-21T00:00:00-05:00 | CausationEntropy: Pythonic Optimal Causation Entropy | arXiv:2601.13365v1 Announce Type: new Abstract: Optimal Causation Entropy (oCSE) is a robust causal network modeling technique that reveals causal networks from dynamical systems and coupled oscillators, distinguishing direct from indirect paths. CausationEntropy is a Python package that implements oCSE and several of ... | https://arxiv.org/abs/2601.13365 | Academic Papers | svg |
1eac6ad6608a8142f7bee38577c8dec073323df8be45df83597ab86063993986 | 2026-01-21T00:00:00-05:00 | Recurrent Confidence Chain: Temporal-Aware Uncertainty Quantification in Large Language Models | arXiv:2601.13368v1 Announce Type: new Abstract: As reasoning modules, such as the chain-of-thought mechanism, are applied to large language models, they achieve strong performance on various tasks such as answering common-sense questions and solving math problems. The main challenge now is to assess the uncertainty of ... | https://arxiv.org/abs/2601.13368 | Academic Papers | svg |
c9111ad0ac04b99e59cb9c48f2a67b456a3d8d2eca01ea0c974daec53d5ae074 | 2026-01-21T00:00:00-05:00 | Spherical Geometry Diffusion: Generating High-quality 3D Face Geometry via Sphere-anchored Representations | arXiv:2601.13371v1 Announce Type: new Abstract: A fundamental challenge in text-to-3D face generation is achieving high-quality geometry. The core difficulty lies in the arbitrary and intricate distribution of vertices in 3D space, making it challenging for existing models to establish clean connectivity and resulting ... | https://arxiv.org/abs/2601.13371 | Academic Papers | svg |
49c5a8f1c6be6c0f344acbbabc216bf303be0757404bf9d0e4afb1a037c91847 | 2026-01-21T00:00:00-05:00 | Influence of Normative Theories of Ethics on the European Union Artificial Intelligence Act: A Transformer-Based Analysis Using Semantic Textual Similarity | arXiv:2601.13372v1 Announce Type: new Abstract: This study investigates the ethical grounding of the European Union Artificial Intelligence (EU AI) Act by using Semantic Textual Similarity (STS) to analyze the alignment between normative ethical theories and regulatory language. Despite being regarded as a significant ... | https://arxiv.org/abs/2601.13372 | Academic Papers | svg |
b371bd6a7ebab250e527b273f0f47796e296786bb9a7c97d49e7aae0e39ceba6 | 2026-01-21T00:00:00-05:00 | A Lightweight Model-Driven 4D Radar Framework for Pervasive Human Detection in Harsh Conditions | arXiv:2601.13373v1 Announce Type: new Abstract: Pervasive sensing in industrial and underground environments is severely constrained by airborne dust, smoke, confined geometry, and metallic structures, which rapidly degrade optical and LiDAR based perception. Elevation resolved 4D mmWave radar offers strong resilience ... | https://arxiv.org/abs/2601.13373 | Academic Papers | svg |
bbe662326bfb0d6898d6ac2a5211bd24b55c3267b537809bf242e03bac2dc8c5 | 2026-01-21T00:00:00-05:00 | Bounded Minds, Generative Machines: Envisioning Conversational AI that Works with Human Heuristics and Reduces Bias Risk | arXiv:2601.13376v1 Announce Type: new Abstract: Conversational AI is rapidly becoming a primary interface for information seeking and decision making, yet most systems still assume idealized users. In practice, human reasoning is bounded by limited attention, uneven knowledge, and reliance on heuristics that are adapti... | https://arxiv.org/abs/2601.13376 | Academic Papers | svg |
b244b1c88c04bde64919be1b5153220c25c46e67f85726ac5af62ea36ba8ac32 | 2026-01-21T00:00:00-05:00 | Practical Insights into Semi-Supervised Object Detection Approaches | arXiv:2601.13380v1 Announce Type: new Abstract: Learning in data-scarce settings has recently gained significant attention in the research community. Semi-supervised object detection(SSOD) aims to improve detection performance by leveraging a large number of unlabeled images alongside a limited number of labeled images... | https://arxiv.org/abs/2601.13380 | Academic Papers | svg |
25fa58db29ecfe26a6c48b7eb6bf4a2d9ba04cb91f26ce93e50d4d4d0486d499 | 2026-01-21T00:00:00-05:00 | A Lightweight Modular Framework for Constructing Autonomous Agents Driven by Large Language Models: Design, Implementation, and Applications in AgentForge | arXiv:2601.13383v1 Announce Type: new Abstract: The emergence of LLMs has catalyzed a paradigm shift in autonomous agent development, enabling systems capable of reasoning, planning, and executing complex multi-step tasks. However, existing agent frameworks often suffer from architectural rigidity, vendor lock-in, and ... | https://arxiv.org/abs/2601.13383 | Academic Papers | svg |
1fd53d69018a2ba494e2ae4f1c87c52a002e02448a77b3b7e37ba0a8a28142fe | 2026-01-21T00:00:00-05:00 | From Completion to Editing: Unlocking Context-Aware Code Infilling via Search-and-Replace Instruction Tuning | arXiv:2601.13384v1 Announce Type: new Abstract: The dominant Fill-in-the-Middle (FIM) paradigm for code completion is constrained by its rigid inability to correct contextual errors and reliance on unaligned, insecure Base models. While Chat LLMs offer safety and Agentic workflows provide flexibility, they suffer from ... | https://arxiv.org/abs/2601.13384 | Academic Papers | svg |
79ba971296115794685fa132ad5f9361b3d3a722a3942f4c1a3637c3e7de77bc | 2026-01-21T00:00:00-05:00 | Organ-Aware Attention Improves CT Triage and Classification | arXiv:2601.13385v1 Announce Type: new Abstract: There is an urgent need for triage and classification of high-volume medical imaging modalities such as computed tomography (CT), which can improve patient care and mitigate radiologist burnout. Study-level CT triage requires calibrated predictions with localized evidence... | https://arxiv.org/abs/2601.13385 | Academic Papers | svg |
c3a7119cbc80590c7ed18bd602eb9130806afaade176bf1262ec1ee2fc0fc26b | 2026-01-21T00:00:00-05:00 | Leveraging Transformer Decoder for Automotive Radar Object Detection | arXiv:2601.13386v1 Announce Type: new Abstract: In this paper, we present a Transformer-based architecture for 3D radar object detection that uses a novel Transformer Decoder as the prediction head to directly regress 3D bounding boxes and class scores from radar feature representations. To bridge multi-scale radar fea... | https://arxiv.org/abs/2601.13386 | Academic Papers | svg |
0143fc38a448f60fa8affc3e06ed08ba01e393034a82305c0bf9abb266cfebb7 | 2026-01-21T00:00:00-05:00 | Confidence over Time: Confidence Calibration with Temporal Logic for Large Language Model Reasoning | arXiv:2601.13387v1 Announce Type: new Abstract: Large Language Models (LLMs) increasingly rely on long-form, multi-step reasoning to solve complex tasks such as mathematical problem solving and scientific question answering. Despite strong performance, existing confidence estimation methods typically reduce an entire r... | https://arxiv.org/abs/2601.13387 | Academic Papers | svg |
6c9a46f1cac37cad19ece4b3f2a21925d231a6286bb1bd524ba4411212e2559c | 2026-01-21T00:00:00-05:00 | Structured Insight from Unstructured Data: Large Language Models for SDOH-Driven Diabetes Risk Prediction | arXiv:2601.13388v1 Announce Type: new Abstract: Social determinants of health (SDOH) play a critical role in Type 2 Diabetes (T2D) management but are often absent from electronic health records and risk prediction models. Most individual-level SDOH data is collected through structured screening tools, which lack the fl... | https://arxiv.org/abs/2601.13388 | Academic Papers | svg |
228e4d035e64f2bd940d359c904abfc5c8bac26cb0447c5ce81e483fccc1ac8b | 2026-01-21T00:00:00-05:00 | Robustness and Resilience Evaluation of Eco-Driving Strategies at Signalized Intersections | arXiv:2601.13389v1 Announce Type: new Abstract: Eco-driving strategies have demonstrated substantial potential for improving energy efficiency and reducing emissions, especially at signalized intersections. However, evaluations of eco-driving methods typically rely on simplified simulation or experimental conditions, w... | https://arxiv.org/abs/2601.13389 | Academic Papers | svg |
e940ca91c25ca2a92c32d9730a8e6ae707cd2a5926fdf0a76a50f1df4c57ac87 | 2026-01-21T00:00:00-05:00 | Beyond Memorization: Testing LLM Reasoning on Unseen Theory of Computation Tasks | arXiv:2601.13392v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated strong performance on formal language tasks, yet whether this reflects genuine symbolic reasoning or pattern matching on familiar constructions remains unclear. We introduce a benchmark for deterministic finite automata (DFA)... | https://arxiv.org/abs/2601.13392 | Academic Papers | svg |
dee116e96e87a758c09bf76c9d33b5856c45a63ceb6957ef43b355939d07445a | 2026-01-21T00:00:00-05:00 | Can LLMs Compress (and Decompress)? Evaluating Code Understanding and Execution via Invertibility | arXiv:2601.13398v1 Announce Type: new Abstract: LLMs demonstrate strong performance on code benchmarks, yet round-trip code execution reveals limitations in their ability to maintain consistent reasoning across forward and backward execution. We present RoundTripCodeEval (RTCE), a comprehensive benchmark consisting of ... | https://arxiv.org/abs/2601.13398 | Academic Papers | svg |
7338e1a946f2a64814743bde1fa30936633613ded159ec0f44eb71ff712249e9 | 2026-01-21T00:00:00-05:00 | QERS: Quantum Encryption Resilience Score for Post-Quantum Cryptography in Computer, IoT, and IIoT Systems | arXiv:2601.13399v1 Announce Type: new Abstract: Post-quantum cryptography (PQC) is becoming essential for securing Internet of Things (IoT) and Industrial IoT (IIoT) systems against quantum-enabled adversaries. However, existing evaluation approaches primarily focus on isolated performance metrics, offering limited sup... | https://arxiv.org/abs/2601.13399 | Academic Papers | svg |
35994a97f9b8df017b9a99c5a8b2679b6ff7e9f09111f9bfad06e9bddb7833cb | 2026-01-21T00:00:00-05:00 | Deep Image Prior with L0 Gradient Regularizer for Image Smoothing | arXiv:2601.13400v1 Announce Type: new Abstract: Image smoothing is a fundamental image processing operation that preserves the underlying structure, such as strong edges and contours, and removes minor details and textures in an image. Many image smoothing algorithms rely on computing local window statistics or solving... | https://arxiv.org/abs/2601.13400 | Academic Papers | svg |
ae2ab4c8828550ace533f716b5210ada4f7b2862ea524489ec3f3cbd15e7b9a0 | 2026-01-21T00:00:00-05:00 | Reasoning with Pixel-level Precision: QVLM Architecture and SQuID Dataset for Quantitative Geospatial Analytics | arXiv:2601.13401v1 Announce Type: new Abstract: Current Vision-Language Models (VLMs) fail at quantitative spatial reasoning because their architectures destroy pixel-level information required for counting and measurements. Vision encoders compress images through patch embeddings, reducing spatial indexing and losing ... | https://arxiv.org/abs/2601.13401 | Academic Papers | svg |
f61745258222fbe9d0cda93dfdda7b14b78fd0af64e3cc97b544f6b14c367616 | 2026-01-21T00:00:00-05:00 | Local-to-Global Logical Explanations for Deep Vision Models | arXiv:2601.13404v1 Announce Type: new Abstract: While deep neural networks are extremely effective at classifying images, they remain opaque and hard to interpret. We introduce local and global explanation methods for black-box models that generate explanations in terms of human-recognizable primitive concepts. Both th... | https://arxiv.org/abs/2601.13404 | Academic Papers | svg |
db20da6b717452078b479e19f113bc53a69c8d7a18463f2546620eec98c1e842 | 2026-01-21T00:00:00-05:00 | Integrating Virtual Reality and Large Language Models for Team-Based Non-Technical Skills Training and Evaluation in the Operating Room | arXiv:2601.13406v1 Announce Type: new Abstract: Although effective teamwork and communication are critical to surgical safety, structured training for non-technical skills (NTS) remains limited compared with technical simulation. The ACS/APDS Phase III Team-Based Skills Curriculum calls for scalable tools that both tea... | https://arxiv.org/abs/2601.13406 | Academic Papers | svg |
c8181cbde5da06814ad6f8e5c0fad16e42f0d4f75fe3d08284def2afb651a627 | 2026-01-21T00:00:00-05:00 | Classifiers in High Dimensional Hilbert Metrics | arXiv:2601.13410v1 Announce Type: new Abstract: Classifying points in high dimensional spaces is a fundamental geometric problem in machine learning. In this paper, we address classifying points in the $d$-dimensional Hilbert polygonal metric. The Hilbert metric is a generalization of the Cayley-Klein hyperbolic distan... | https://arxiv.org/abs/2601.13410 | Academic Papers | svg |
637d9cdc6a87580131c0a4c711a800056e0652ebc46a0279acbece1d98fc4d52 | 2026-01-21T00:00:00-05:00 | Using deep learning for predicting cleansing quality of colon capsule endoscopy images | arXiv:2601.13412v1 Announce Type: new Abstract: In this study, we explore the application of deep learning techniques for predicting cleansing quality in colon capsule endoscopy (CCE) images. Using a dataset of 500 images labeled by 14 clinicians on the Leighton-Rex scale (Poor, Fair, Good, and Excellent), a ResNet-18 ... | https://arxiv.org/abs/2601.13412 | Academic Papers | svg |
c5cc5d9bc5ba9568c92f852947854c8821c4837e385f3a546f579d78ac6ee307 | 2026-01-21T00:00:00-05:00 | Diffusion Representations for Fine-Grained Image Classification: A Marine Plankton Case Study | arXiv:2601.13416v1 Announce Type: new Abstract: Diffusion models have emerged as state-of-the-art generative methods for image synthesis, yet their potential as general-purpose feature encoders remains underexplored. Trained for denoising and generation without labels, they can be interpreted as self-supervised learner... | https://arxiv.org/abs/2601.13416 | Academic Papers | svg |
72f638fab9ccbb29ed0c9a58624cab4e485f6d21e679ab56936178b0264a99ac | 2026-01-21T00:00:00-05:00 | SGW-GAN: Sliced Gromov-Wasserstein Guided GANs for Retinal Fundus Image Enhancement | arXiv:2601.13417v1 Announce Type: new Abstract: Retinal fundus photography is indispensable for ophthalmic screening and diagnosis, yet image quality is often degraded by noise, artifacts, and uneven illumination. Recent GAN- and diffusion-based enhancement methods improve perceptual quality by aligning degraded images... | https://arxiv.org/abs/2601.13417 | Academic Papers | svg |
246c12c581dfee907fd111722aee353cded992ff65fa837f5e8f39f267b3957f | 2026-01-21T00:00:00-05:00 | TrustEnergy: A Unified Framework for Accurate and Reliable User-level Energy Usage Prediction | arXiv:2601.13422v1 Announce Type: new Abstract: Energy usage prediction is important for various real-world applications, including grid management, infrastructure planning, and disaster response. Although a plethora of deep learning approaches have been proposed to perform this task, most of them either overlook the e... | https://arxiv.org/abs/2601.13422 | Academic Papers | svg |
66a32b0d991fbe9fd60f7f1d0061b14ec657e55787bcca2cb0d17850fb2e8611 | 2026-01-21T00:00:00-05:00 | Quantum Encryption Resilience Score (QERS) for MQTT, HTTP, and HTTPS under Post-Quantum Cryptography in Computer, IoT, and IIoT Systems | arXiv:2601.13423v1 Announce Type: new Abstract: Post-quantum cryptography (PQC) introduces significant computational and communication overhead, which poses challenges for resource-constrained computer systems, Internet of Things (IoT), and Industrial IoT (IIoT) devices. This paper presents an experimental evaluation o... | https://arxiv.org/abs/2601.13423 | Academic Papers | svg |
a5fc881f93c81eaeac5fba54571f238f1248c60be0647c86bb07c1e624fe58de | 2026-01-21T00:00:00-05:00 | Driving Computational Efficiency in Large-Scale Platforms using HPC Technologies | arXiv:2601.13424v1 Announce Type: new Abstract: The Latin American Giant Observatory (LAGO) project utilizes extensive High-Performance Computing (HPC) resources for complex astroparticle physics simulations, making resource efficiency critical for scientific productivity and sustainability. This article presents a det... | https://arxiv.org/abs/2601.13424 | Academic Papers | svg |
946175d8cc48fb70e58ad67cf8c907240333fc4d89efd2a72c8a6556c277fff8 | 2026-01-21T00:00:00-05:00 | A Scientific Data Integrity system based on Blockchain | arXiv:2601.13425v1 Announce Type: new Abstract: In most High Performance Computing (HPC) projects nowadays, there is a lot of data obtained from different sources, depending on the project's objectives. Some of that data is very huge in terms of size, so copying such data sometimes is an unrealistic goal. On the other ... | https://arxiv.org/abs/2601.13425 | Academic Papers | svg |
ddd893b358f57159105d19307cdee3a381a3183dc6c87e65a9ffa26cf85d7c8e | 2026-01-21T00:00:00-05:00 | Techniques of Modern Attacks | arXiv:2601.13427v1 Announce Type: new Abstract: The techniques used in modern attacks have become an important factor for investigation. As we advance further into the digital age, cyber attackers are employing increasingly sophisticated and highly threatening methods. These attacks target not only organizations and go... | https://arxiv.org/abs/2601.13427 | Academic Papers | svg |
ae976d050b0f1f321ed8ce838ec13248d3e2850e469642e5b2362150b3afe748 | 2026-01-21T00:00:00-05:00 | Trust Me, I'm an Expert: Decoding and Steering Authority Bias in Large Language Models | arXiv:2601.13433v1 Announce Type: new Abstract: Prior research demonstrates that performance of language models on reasoning tasks can be influenced by suggestions, hints and endorsements. However, the influence of endorsement source credibility remains underexplored. We investigate whether language models exhibit syst... | https://arxiv.org/abs/2601.13433 | Academic Papers | svg |
c84d441cd8d99bbf3060c783b6a3f3d6359442200c464b98dd276dc3e4f0b4df | 2026-01-21T00:00:00-05:00 | A Learnable Wavelet Transformer for Long-Short Equity Trading and Risk-Adjusted Return Optimization | arXiv:2601.13435v1 Announce Type: new Abstract: Learning profitable intraday trading policies from financial time series is challenging due to heavy noise, non-stationarity, and strong cross-sectional dependence among related assets. We propose \emph{WaveLSFormer}, a learnable wavelet-based long-short Transformer that ... | https://arxiv.org/abs/2601.13435 | Academic Papers | svg |
b8b9997a9d20efa7364c1005ee9ae6469b5f547208838f891a484d66e54d6dd7 | 2026-01-21T00:00:00-05:00 | MOSLD-Bench: Multilingual Open-Set Learning and Discovery Benchmark for Text Categorization | arXiv:2601.13437v1 Announce Type: new Abstract: Open-set learning and discovery (OSLD) is a challenging machine learning task in which samples from new (unknown) classes can appear at test time. It can be seen as a generalization of zero-shot learning, where the new classes are not known a priori, hence involving the a... | https://arxiv.org/abs/2601.13437 | Academic Papers | svg |
42f0aa19dfa178b20bd84e505359fc0333b48bd6b2dd1491406f97da1775cd84 | 2026-01-21T00:00:00-05:00 | Analyzing VLM-Based Approaches for Anomaly Classification and Segmentation | arXiv:2601.13440v1 Announce Type: new Abstract: Vision-Language Models (VLMs), particularly CLIP, have revolutionized anomaly detection by enabling zero-shot and few-shot defect identification without extensive labeled datasets. By learning aligned representations of images and text, VLMs facilitate anomaly classificat... | https://arxiv.org/abs/2601.13440 | Academic Papers | svg |
025fb015e68025a12eb2129e494d862a8c11cfc09aa6ac5433c94675df0959f5 | 2026-01-21T00:00:00-05:00 | Explicit Cognitive Allocation: A Principle for Governed and Auditable Inference in Large Language Models | arXiv:2601.13443v1 Announce Type: new Abstract: The rapid adoption of large language models (LLMs) has enabled new forms of AI-assisted reasoning across scientific, technical, and organizational domains. However, prevailing modes of LLM use remain cognitively unstructured: problem framing, knowledge exploration, retrie... | https://arxiv.org/abs/2601.13443 | Academic Papers | svg |
5f220a82d1c94313b320e49316bcc5b157e5814165b065fb4677c38ea9f6fb48 | 2026-01-21T00:00:00-05:00 | BladeSDF : Unconditional and Conditional Generative Modeling of Representative Blade Geometries Using Signed Distance Functions | arXiv:2601.13445v1 Announce Type: new Abstract: Generative AI has emerged as a transformative paradigm in engineering design, enabling automated synthesis and reconstruction of complex 3D geometries while preserving feasibility and performance relevance. This paper introduces a domain-specific implicit generative frame... | https://arxiv.org/abs/2601.13445 | Academic Papers | svg |
abf282f16ef2b51faa288d779c9b090dbb83bb0380cd6eedce7bb388223f9cf2 | 2026-01-21T00:00:00-05:00 | Fairness-informed Pareto Optimization : An Efficient Bilevel Framework | arXiv:2601.13448v1 Announce Type: new Abstract: Despite their promise, fair machine learning methods often yield Pareto-inefficient models, in which the performance of certain groups can be improved without degrading that of others. This issue arises frequently in traditional in-processing approaches such as fairness-t... | https://arxiv.org/abs/2601.13448 | Academic Papers | svg |
c118d23f1d54228b54ff0e38924a566e3cc3363555d6731751854e04a39cf350 | 2026-01-21T00:00:00-05:00 | Event-based Heterogeneous Information Processing for Online Vision-based Obstacle Detection and Localization | arXiv:2601.13451v1 Announce Type: new Abstract: This paper introduces a novel framework for robotic vision-based navigation that integrates Hybrid Neural Networks (HNNs) with Spiking Neural Network (SNN)-based filtering to enhance situational awareness for unmodeled obstacle detection and localization. By leveraging th... | https://arxiv.org/abs/2601.13451 | Academic Papers | svg |
df26d5a0836e930e1d2d7d5e59c9abd8a4e9274b433385908e0f0555132f05ee | 2026-01-21T00:00:00-05:00 | A simulation of urban incidents involving pedestrians and vehicles based on Weighted A* | arXiv:2601.13452v1 Announce Type: new Abstract: This document presents a comprehensive simulation framework designed to model urban incidents involving pedestrians and vehicles. Using a multiagent systems approach, two types of agents (pedestrians and vehicles) are introduced within a 2D grid based urban environment. T... | https://arxiv.org/abs/2601.13452 | Academic Papers | svg |
467a967b1c92a8a82e1e1d959261b5f6bc5ea12232289acf766316fbc8fd5f49 | 2026-01-21T00:00:00-05:00 | PhysicsSolutionAgent: Towards Multimodal Explanations for Numerical Physics Problem Solving | arXiv:2601.13453v1 Announce Type: new Abstract: Explaining numerical physics problems often requires more than text-based solutions; clear visual reasoning can substantially improve conceptual understanding. While large language models (LLMs) demonstrate strong performance on many physics questions in textual form, the... | https://arxiv.org/abs/2601.13453 | Academic Papers | svg |
911ac8bfeb69c8e4755ea3ca30826b738c4f506048ee947a3742ba94a185a3dd | 2026-01-21T00:00:00-05:00 | Federated Learning Under Temporal Drift -- Mitigating Catastrophic Forgetting via Experience Replay | arXiv:2601.13456v1 Announce Type: new Abstract: Federated Learning struggles under temporal concept drift where client data distributions shift over time. We demonstrate that standard FedAvg suffers catastrophic forgetting under seasonal drift on Fashion-MNIST, with accuracy dropping from 74% to 28%. We propose client-... | https://arxiv.org/abs/2601.13456 | Academic Papers | svg |
0c23b6b77378cba940fc6b0132fd6e4425d37711159a178d1ca9f006ee979495 | 2026-01-21T00:00:00-05:00 | A Tool for Automatically Cataloguing and Selecting Pre-Trained Models and Datasets for Software Engineering | arXiv:2601.13460v1 Announce Type: new Abstract: The rapid growth of machine learning assets has made it increasingly difficult for software engineers to identify models and datasets that match their specific needs. Browsing large registries, such as Hugging Face, is time-consuming, error-prone, and rarely tailored to S... | https://arxiv.org/abs/2601.13460 | Academic Papers | svg |
c993842fe8b9e54bc53c3922dc733cc49ba630a91787c46a1fd3ac115ed795b7 | 2026-01-21T00:00:00-05:00 | SpatialBench-UC: Uncertainty-Aware Evaluation of Spatial Prompt Following in Text-to-Image Generation | arXiv:2601.13462v1 Announce Type: new Abstract: Evaluating whether text-to-image models follow explicit spatial instructions is difficult to automate. Object detectors may miss targets or return multiple plausible detections, and simple geometric tests can become ambiguous in borderline cases. Spatial evaluation is nat... | https://arxiv.org/abs/2601.13462 | Academic Papers | svg |
20be1846f962c373295c22d4e5d21087e2e6b0fa811e1f3f00a6747d77adcef3 | 2026-01-21T00:00:00-05:00 | Quantum Qualifiers for Neural Network Model Selection in Hadronic Physics | arXiv:2601.13463v1 Announce Type: new Abstract: As quantum machine-learning architectures mature, a central challenge is no longer their construction, but identifying the regimes in which they offer practical advantages over classical approaches. In this work, we introduce a framework for addressing this question in da... | https://arxiv.org/abs/2601.13463 | Academic Papers | svg |
9e0ddb845f5237dec0f922e35f2e2a6cff4ddba3b344239863c714a394d90f8f | 2026-01-21T00:00:00-05:00 | Context and Transcripts Improve Detection of Deepfake Audios of Public Figures | arXiv:2601.13464v1 Announce Type: new Abstract: Humans use context to assess the veracity of information. However, current audio deepfake detectors only analyze the audio file without considering either context or transcripts. We create and analyze a Journalist-provided Deepfake Dataset (JDD) of 255 public deepfakes wh... | https://arxiv.org/abs/2601.13464 | Academic Papers | svg |
dcd5f0ae69ceabc09041cb5df9e1d525dd9d99096b572a92844b5d1082b99390 | 2026-01-21T00:00:00-05:00 | Graph Neural Networks are Heuristics | arXiv:2601.13465v1 Announce Type: new Abstract: We demonstrate that a single training trajectory can transform a graph neural network into an unsupervised heuristic for combinatorial optimization. Focusing on the Travelling Salesman Problem, we show that encoding global structural constraints as an inductive bias enabl... | https://arxiv.org/abs/2601.13465 | Academic Papers | svg |
73eb49d8cdf5d8333128804f89c8e3fc49918e5cc82724fa60c0ce80cd1522ca | 2026-01-21T00:00:00-05:00 | Governance Matters: Lessons from Restructuring the data.table OSS Project | arXiv:2601.13466v1 Announce Type: new Abstract: Open source software (OSS) forms the backbone of industrial data workflows and enterprise systems. However, many OSS projects face operational risks due to informal or centralized governance. This paper presents a practical case study of data.table, a high-performance R p... | https://arxiv.org/abs/2601.13466 | Academic Papers | svg |
2632d06ae95e81c96ebcf4e4fc1d573ddd4f716d2cd3a27aeca5d6fec0bc6f56 | 2026-01-21T00:00:00-05:00 | Preconditioning Benefits of Spectral Orthogonalization in Muon | arXiv:2601.13474v1 Announce Type: new Abstract: The Muon optimizer, a matrix-structured algorithm that leverages spectral orthogonalization of gradients, is a milestone in the pretraining of large language models. However, the underlying mechanisms of Muon -- particularly the role of gradient orthogonalization -- remai... | https://arxiv.org/abs/2601.13474 | Academic Papers | svg |
c517c7fdfb8c3fcc9fe609a901246496e0e117a893be68fd831b0f7e4cc0aeae | 2026-01-21T00:00:00-05:00 | A Unified Variational Imputation Framework for Electric Vehicle Charging Data Using Retrieval-Augmented Language Model | arXiv:2601.13476v1 Announce Type: new Abstract: The reliability of data-driven applications in electric vehicle (EV) infrastructure, such as charging demand forecasting, hinges on the availability of complete, high-quality charging data. However, real-world EV datasets are often plagued by missing records, and existing... | https://arxiv.org/abs/2601.13476 | Academic Papers | svg |
c460559b103b85ae1afd6758665c463908f6dd47dd2fc31f8b0cdfa7554fe304 | 2026-01-21T00:00:00-05:00 | Elias-type Bounds for Codes in the Symmetric Limited-Magnitude Error Channel | arXiv:2601.13477v1 Announce Type: new Abstract: We study perfect error-correcting codes in $\mathbb{Z}^n$ for the symmetric limited-magnitude error channel, where at most $e$ coordinates of an integer vector may be altered by a value whose magnitude is at most $s$. Geometrically, such codes correspond to tilings of $\m... | https://arxiv.org/abs/2601.13477 | Academic Papers | svg |
4b9aba67a104598a9e8f355368f3989d7142ce244df16593c17f86419462d89a | 2026-01-21T00:00:00-05:00 | Exploring Learners' Expectations and Engagement When Collaborating with Constructively Controversial Peer Agents | arXiv:2601.13479v1 Announce Type: new Abstract: Peer agents can supplement real-time collaborative learning in asynchronous online courses. Constructive Controversy (CC) theory suggests that humans deepen their understanding of a topic by confronting and resolving controversies. This study explores whether CC's benefit... | https://arxiv.org/abs/2601.13479 | Academic Papers | svg |
34f664692f66469713f6c76b0ed176c0ec1745e90876bc845d04506ea857bc1f | 2026-01-21T00:00:00-05:00 | Towards Efficient and Robust Linguistic Emotion Diagnosis for Mental Health via Multi-Agent Instruction Refinement | arXiv:2601.13481v1 Announce Type: new Abstract: Linguistic expressions of emotions such as depression, anxiety, and trauma-related states are pervasive in clinical notes, counseling dialogues, and online mental health communities, and accurate recognition of these emotions is essential for clinical triage, risk assessm... | https://arxiv.org/abs/2601.13481 | Academic Papers | svg |
22cf8d7d715aaaebd513340e2f34ff11a4b81298675209a4f638ce61bbc043d9 | 2026-01-21T00:00:00-05:00 | Spectrum & RAN Sharing: A Measurement-based Case Study of Commercial 5G Networks in Spain | arXiv:2601.13484v1 Announce Type: new Abstract: Radio Access Network (RAN) sharing, which often also includes spectrum sharing, is a strategic cooperative agreement among two or more mobile operators, where one operator may use another's RAN infrastructure to provide mobile services to its users. By mutually sharing ph... | https://arxiv.org/abs/2601.13484 | Academic Papers | svg |
c7e5bbed6c6ce528f97e76aaf5ccba10adcade2a2133c7a16226e4987361a3bc | 2026-01-21T00:00:00-05:00 | The Hidden Toll of Social Media News: Causal Effects on Psychosocial Wellbeing | arXiv:2601.13487v1 Announce Type: new Abstract: News consumption on social media has become ubiquitous, yet how different forms of engagement shape psychosocial outcomes remains unclear. To address this gap, we leveraged a large-scale dataset of ~26M posts and ~45M comments on the BlueSky platform, and conducted a quas... | https://arxiv.org/abs/2601.13487 | Academic Papers | svg |
e47d286a63d6f90389a7cedf4b620da8c1f07643e34b8219fb2c8251ca5a818a | 2026-01-21T00:00:00-05:00 | Bridging the Gap Between Estimated and True Regret Towards Reliable Regret Estimation in Deep Learning based Mechanism Design | arXiv:2601.13489v1 Announce Type: new Abstract: Recent advances, such as RegretNet, ALGnet, RegretFormer and CITransNet, use deep learning to approximate optimal multi item auctions by relaxing incentive compatibility (IC) and measuring its violation via ex post regret. However, the true accuracy of these regret estima... | https://arxiv.org/abs/2601.13489 | Academic Papers | svg |
13fb2841fd65b1a0ab02b3d4825cb9a8859bb4ffbb2008f3b85a61796a80af55 | 2026-01-21T00:00:00-05:00 | Learning-Augmented Online TRP on a Line | arXiv:2601.13494v1 Announce Type: new Abstract: We study the online traveling repairperson problem on a line within the recently proposed learning-augmented framework, which provides predictions on the requests to be served via machine learning. In the original model (with no predictions), there is a stream of requests... | https://arxiv.org/abs/2601.13494 | Academic Papers | svg |
aa21939d79cb1b7fb651599ded7c24622055b55cc092147d172ec29d5442b1fd | 2026-01-21T00:00:00-05:00 | RASC: Enhancing Observability & Programmability in Smart Spaces | arXiv:2601.13496v1 Announce Type: new Abstract: While RPCs form the bedrock of systems stacks, we posit that IoT device collections in smart spaces like homes, warehouses, and office buildings--which are all "user-facing"--require a more expressive abstraction. Orthogonal to prior work, which improved the reliability o... | https://arxiv.org/abs/2601.13496 | Academic Papers | svg |
81fe7db328a2e4cb2f34af6782f1d9ccd564e67ff45222e19358311ffe556845 | 2026-01-21T00:00:00-05:00 | Optical Linear Systems Framework for Event Sensing and Computational Neuromorphic Imaging | arXiv:2601.13498v1 Announce Type: new Abstract: Event vision sensors (neuromorphic cameras) output sparse, asynchronous ON/OFF events triggered by log-intensity threshold crossings, enabling microsecond-scale sensing with high dynamic range and low data bandwidth. As a nonlinear system, this event representation does n... | https://arxiv.org/abs/2601.13498 | Academic Papers | svg |
5c634717627c1f53cfd8bf802941180a4450dc2e509caab0a6355191fbc472b8 | 2026-01-21T00:00:00-05:00 | Concurrent Permissive Strategy Templates | arXiv:2601.13500v1 Announce Type: new Abstract: Two-player games on finite graphs provide a rigorous foundation for modeling the strategic interaction between reactive systems and their environment. While concurrent game semantics naturally capture the synchronous interactions characteristic of many cyber-physical syst... | https://arxiv.org/abs/2601.13500 | Academic Papers | svg |
87952b962fef3f9868d44abd9e4204ec6967748b2b437addf8658c910f66a23e | 2026-01-21T00:00:00-05:00 | Modeling Perpetrators' Fate-to-Fate Contagion in Public Mass Shootings In The United States Using Bivariate Hawkes Processes | arXiv:2601.13501v1 Announce Type: new Abstract: This study examines how the fate of a perpetrator in a public mass shooting influences the fate of subsequent perpetrators. Using data from 1966 to 2024, we classify incidents according to whether the perpetrator died at the scene or survived the attack. Using a bivariate... | https://arxiv.org/abs/2601.13501 | Academic Papers | svg |
cd5f280135943096c4f450137f1e178a1539ac965b5161543e63aecc956d428e | 2026-01-21T00:00:00-05:00 | DIS2: Disentanglement Meets Distillation with Classwise Attention for Robust Remote Sensing Segmentation under Missing Modalities | arXiv:2601.13502v1 Announce Type: new Abstract: The efficacy of multimodal learning in remote sensing (RS) is severely undermined by missing modalities. The challenge is exacerbated by the RS highly heterogeneous data and huge scale variation. Consequently, paradigms proven effective in other domains often fail when co... | https://arxiv.org/abs/2601.13502 | Academic Papers | svg |
5985d361ebb2557be01f9be78a447594149b7ac3dbb2b22d1aeff5c2ed19e88f | 2026-01-21T00:00:00-05:00 | Anonpsy: A Graph-Based Framework for Structure-Preserving De-identification of Psychiatric Narratives | arXiv:2601.13503v1 Announce Type: new Abstract: Psychiatric narratives encode patient identity not only through explicit identifiers but also through idiosyncratic life events embedded in their clinical structure. Existing de-identification approaches, including PHI masking and LLM-based synthetic rewriting, operate at... | https://arxiv.org/abs/2601.13503 | Academic Papers | svg |
f517a2dec43634b9a674b2f0c79abcd286b2e8fc32422abaf085bade47da88ec | 2026-01-21T00:00:00-05:00 | Integrating Vision-Centric Text Understanding for Conversational Recommender Systems | arXiv:2601.13505v1 Announce Type: new Abstract: Conversational Recommender Systems (CRSs) have attracted growing attention for their ability to deliver personalized recommendations through natural language interactions. To more accurately infer user preferences from multi-turn conversations, recent works increasingly e... | https://arxiv.org/abs/2601.13505 | Academic Papers | svg |
763614b77ab19f874a2805711b749f8d8cb45791722c2c6926261d5c8e36758f | 2026-01-21T00:00:00-05:00 | Group Relative Policy Optimization for Robust Blind Interference Alignment with Fluid Antennas | arXiv:2601.13506v1 Announce Type: new Abstract: Fluid antenna system (FAS) leverages dynamic reconfigurability to unlock spatial degrees of freedom and reshape wireless channels. This paper proposes, for the first time, a robust fluid antenna-driven blind interference alignment (BIA) framework for a K-user MISO downlin... | https://arxiv.org/abs/2601.13506 | Academic Papers | svg |
884a4114a863128fa26ea48853dd30d71e92db2d2239e02ce30a1290d67ba677 | 2026-01-21T00:00:00-05:00 | Event Classification by Physics-informed Inpainting for Distributed Multichannel Acoustic Sensor with Partially Degraded Channels | arXiv:2601.13513v1 Announce Type: new Abstract: Distributed multichannel acoustic sensing (DMAS) enables large-scale sound event classification (SEC), but performance drops when many channels are degraded and when sensor layouts at test time differ from training layouts. We propose a learning-free, physics-informed inp... | https://arxiv.org/abs/2601.13513 | Academic Papers | svg |
1691fbf0ed2bd08f77c560ed189752666ffd0ef48ac42d3bd28dc17dbd2bd43a | 2026-01-21T00:00:00-05:00 | Automatic Adjustment of HPA Parameters and Attack Prevention in Kubernetes Using Random Forests | arXiv:2601.13515v1 Announce Type: new Abstract: In this paper, HTTP status codes are used as custom metrics within the HPA as the experimental scenario. By integrating the Random Forest classification algorithm from machine learning, attacks are assessed and predicted, dynamically adjusting the maximum pod parameter in... | https://arxiv.org/abs/2601.13515 | Academic Papers | svg |
0b41656d88183d16aca876fde781e31ded3e2c11b226397d0f0186c9b2c46ecf | 2026-01-21T00:00:00-05:00 | From "Fail Fast" to "Mature Safely:" Expert Perspectives as Secondary Stakeholders on Teen-Centered Social Media Risk Detection | arXiv:2601.13516v1 Announce Type: new Abstract: In addressing various risks on social media, the HCI community has advocated for teen-centered risk detection technologies over platform-based, parent-centered features. However, their real-world viability remains underexplored by secondary stakeholders beyond the family ... | https://arxiv.org/abs/2601.13516 | Academic Papers | svg |
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