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ba2c61a649df442b511c5323307202bfc8919959d98fa177690e3ea4d95acc54 | 2026-01-21T00:00:00-05:00 | PDFInspect: A Unified Feature Extraction Framework for Malicious Document Detection | arXiv:2601.12866v1 Announce Type: new Abstract: The increasing prevalence of malicious Portable Document Format (PDF) files necessitates robust and comprehensive feature extraction techniques for effective detection and analysis. This work presents a unified framework that integrates graph-based, structural, and metada... | https://arxiv.org/abs/2601.12866 | Academic Papers | svg |
3395f9d087105f416c6150a8a9a31463323cfc8973e8fe8af9481efab89be79b | 2026-01-21T00:00:00-05:00 | Race, Ethnicity and Their Implication on Bias in Large Language Models | arXiv:2601.12868v1 Announce Type: new Abstract: Large language models (LLMs) increasingly operate in high-stakes settings including healthcare and medicine, where demographic attributes such as race and ethnicity may be explicitly stated or implicitly inferred from text. However, existing studies primarily document out... | https://arxiv.org/abs/2601.12868 | Academic Papers | svg |
0c568a2c6a80a6e29c0df649946ff6aa8a8eb5be9bd578473a73eebc9cc58664 | 2026-01-21T00:00:00-05:00 | Text2Structure3D: Graph-Based Generative Modeling of Equilibrium Structures with Diffusion Transformers | arXiv:2601.12870v1 Announce Type: new Abstract: This paper presents Text2Structure3D, a graph-based Machine Learning (ML) model that generates equilibrium structures from natural language prompts. Text2Structure3D is designed to support new intuitive ways of design exploration and iteration in the conceptual structural... | https://arxiv.org/abs/2601.12870 | Academic Papers | svg |
2ea3f78ab90a022735c0178dd3e9d63611466278e915289d4fae57232b5baba3 | 2026-01-21T00:00:00-05:00 | Measuring Love Toward AI: Development and Validation of the Love Attitudes Scale toward Artificial Intelligence (LAS-AI) | arXiv:2601.12871v1 Announce Type: new Abstract: Artificial intelligences (AIs) are increasingly capable of emotionally engaging with humans to the point of forming intimate relationships. Yet, current studies on romantic love toward AI lack statistically validated instruments to measure romantic love toward AI, hinderi... | https://arxiv.org/abs/2601.12871 | Academic Papers | svg |
5876664386383692543a0c22222172be2117bd7e72d294ffbfac112a2565a972 | 2026-01-21T00:00:00-05:00 | Quantum Interactive Oracle Proofs | arXiv:2601.12874v1 Announce Type: new Abstract: We initiate the study of quantum Interactive Oracle Proofs (qIOPs), a generalization of both quantum Probabilistically Checkable Proofs and quantum Interactive Proofs, as well as a quantum analogue of classical Interactive Oracle Proofs. In the model of quantum Interactiv... | https://arxiv.org/abs/2601.12874 | Academic Papers | svg |
97444cb7aa6ef82d11265693a9f925b0148c6f6853a61d1ed00fd9eb97b87738 | 2026-01-21T00:00:00-05:00 | SWORD: A Secure LoW-Latency Offline-First Authentication and Data Sharing Scheme for Resource Constrained Distributed Networks | arXiv:2601.12875v1 Announce Type: new Abstract: While many resource-constrained networks, such as Internet of Things (IoT) and Internet of Vehicles (IoV), are inherently distributed, the majority still rely on central servers for fast authentication and data sharing. Blockchain-based solutions offer decentralized alter... | https://arxiv.org/abs/2601.12875 | Academic Papers | svg |
4296f1c62a0bc5838271f4ab2bee09c325c0c2670ce01ce8ccab178871b0b305 | 2026-01-21T00:00:00-05:00 | Exploring Talking Head Models With Adjacent Frame Prior for Speech-Preserving Facial Expression Manipulation | arXiv:2601.12876v1 Announce Type: new Abstract: Speech-Preserving Facial Expression Manipulation (SPFEM) is an innovative technique aimed at altering facial expressions in images and videos while retaining the original mouth movements. Despite advancements, SPFEM still struggles with accurate lip synchronization due to... | https://arxiv.org/abs/2601.12876 | Academic Papers | svg |
f98c5739f63c73adf5e6934f6b530c5177e8910de01917439ebddf2be323c392 | 2026-01-21T00:00:00-05:00 | A hierarchical splitting approach for N-split differential equations | arXiv:2601.12878v1 Announce Type: new Abstract: We propose a hierarchical splitting approach to differential equations that provides a design principle for constructing splitting methods for $N$-split systems by iteratively applying splitting methods for two-split systems. We analyze the convergence order, derive expli... | https://arxiv.org/abs/2601.12878 | Academic Papers | svg |
e2a8045ffeed7cfd07435c035cdf330c96ef3bde0d5a4f925eb9785ce574316e | 2026-01-21T00:00:00-05:00 | Hierarchical Sparse Circuit Extraction from Billion-Parameter Language Models through Scalable Attribution Graph Decomposition | arXiv:2601.12879v1 Announce Type: new Abstract: Mechanistic interpretability seeks to reverse-engineer neural network computations into human-understandable algorithms, yet extracting sparse computational circuits from billion-parameter language models remains challenging due to exponential search complexity and pervas... | https://arxiv.org/abs/2601.12879 | Academic Papers | svg |
bbccacb1a7eed90c3d391cbb302662bf5fc7a93768a74a8c14be2949841ba711 | 2026-01-21T00:00:00-05:00 | YOLO26: An Analysis of NMS-Free End to End Framework for Real-Time Object Detection | arXiv:2601.12882v1 Announce Type: new Abstract: The "You Only Look Once" (YOLO) framework has long served as the benchmark for real-time object detection, yet traditional iterations (YOLOv1 through YOLO11) remain constrained by the latency and hyperparameter sensitivity of Non-Maximum Suppression (NMS) post-processing.... | https://arxiv.org/abs/2601.12882 | Academic Papers | svg |
0d8b77cd8e3b89ed79fd1085c4d606aa5a020b49e315346f408a6e83438fe761 | 2026-01-21T00:00:00-05:00 | Does Motion Intensity Impair Cognition in HCI? The Critical Role of Physical Motion-Visual Target Directional Congruency | arXiv:2601.12884v1 Announce Type: new Abstract: Human-computer interaction (HCI) increasingly occurs in motion-rich environments. The ability to accurately and rapidly respond to directional visual cues is critical in these contexts. How whole-body motion and individual differences affect human perception and reaction ... | https://arxiv.org/abs/2601.12884 | Academic Papers | svg |
2159e04aeeced72c0065c33688a1058bc27102c087e306927f36fb3be9d9e989 | 2026-01-21T00:00:00-05:00 | From Vertices to Convex Hulls: Certifying Set-Wise Compatibility for CBF Constraints | arXiv:2601.12885v1 Announce Type: new Abstract: This paper develops certificates that propagate compatibility of multiple control barrier function (CBF) constraints from sampled vertices to their convex hull. Under mild concavity and affinity assumptions, we present three sufficient feasibility conditions under which f... | https://arxiv.org/abs/2601.12885 | Academic Papers | svg |
81e60d3538ecac0d1d1df606ca98f0ffa1a90d5cd87c98e158ddfe3bf5d7de67 | 2026-01-21T00:00:00-05:00 | Communication Methods in Multi-Agent Reinforcement Learning | arXiv:2601.12886v1 Announce Type: new Abstract: Multi-agent reinforcement learning is a promising research area that extends established reinforcement learning approaches to problems formulated as multi-agent systems. Recently, a multitude of communication methods have been introduced to this field to address problems ... | https://arxiv.org/abs/2601.12886 | Academic Papers | svg |
3757e20656684f81bc3e6eea90c362fdafc55f5bd61a3ad3550b804baacbdb0c | 2026-01-21T00:00:00-05:00 | Simultaneous Detection of LSD and FMD in Cattle Using Ensemble Deep Learning | arXiv:2601.12889v1 Announce Type: new Abstract: Lumpy Skin Disease (LSD) and Foot-and-Mouth Disease (FMD) are highly contagious viral diseases affecting cattle, causing significant economic losses and welfare challenges. Their visual diagnosis is complicated by significant symptom overlap with each other and with benig... | https://arxiv.org/abs/2601.12889 | Academic Papers | svg |
6d843dd0ebbfd77c3f613793ffee336c8c964b1ad8f16739796c6e49e1433e30 | 2026-01-21T00:00:00-05:00 | Efficient Code Analysis via Graph-Guided Large Language Models | arXiv:2601.12890v1 Announce Type: new Abstract: Malicious behavior is often hidden in small, easily overlooked code fragments, especially within large and complex codebases. The cross-file dependencies of these fragments make it difficult for even powerful large language models (LLMs) to detect them reliably. We propos... | https://arxiv.org/abs/2601.12890 | Academic Papers | svg |
9dda35e7851dec6e7620fb9166b29b344c877694b218f98e094df45971ba3e15 | 2026-01-21T00:00:00-05:00 | AdaNODEs: Test Time Adaptation for Time Series Forecasting Using Neural ODEs | arXiv:2601.12893v1 Announce Type: new Abstract: Test time adaptation (TTA) has emerged as a promising solution to adapt pre-trained models to new, unseen data distributions using unlabeled target domain data. However, most TTA methods are designed for independent data, often overlooking the time series data and rarely ... | https://arxiv.org/abs/2601.12893 | Academic Papers | svg |
b48af16991542b76fe865d2ed6eacc9c62ab7379f0f434c8d843574bc7b79676 | 2026-01-21T00:00:00-05:00 | Sparse ActionGen: Accelerating Diffusion Policy with Real-time Pruning | arXiv:2601.12894v1 Announce Type: new Abstract: Diffusion Policy has dominated action generation due to its strong capabilities for modeling multi-modal action distributions, but its multi-step denoising processes make it impractical for real-time visuomotor control. Existing caching-based acceleration methods typicall... | https://arxiv.org/abs/2601.12894 | Academic Papers | svg |
57806b9992041e9f0a2f502ba60b4ba9c0a0c30e61d36b394f36ac989ec31e65 | 2026-01-21T00:00:00-05:00 | TwoHead-SwinFPN: A Unified DL Architecture for Synthetic Manipulation, Detection and Localization in Identity Documents | arXiv:2601.12895v1 Announce Type: new Abstract: The proliferation of sophisticated generative AI models has significantly escalated the threat of synthetic manipulations in identity documents, particularly through face swapping and text inpainting attacks. This paper presents TwoHead-SwinFPN, a unified deep learning ar... | https://arxiv.org/abs/2601.12895 | Academic Papers | svg |
a8ce0db291ec5393ddb24e49b7d51c08f22d6e56993f3e9a2517cff378846bbd | 2026-01-21T00:00:00-05:00 | Supervised Learning for the (s,S) Inventory Model with General Interarrival Demands and General Lead Times | arXiv:2601.12900v1 Announce Type: new Abstract: The continuous-review (s,S) inventory model is a cornerstone of stochastic inventory theory, yet its analysis becomes analytically intractable when dealing with non-Markovian systems. In such systems, evaluating long-run performance measures typically relies on costly sim... | https://arxiv.org/abs/2601.12900 | Academic Papers | svg |
027578e11d0c86233cc0e0dc52f27f78a6d22a029f3999e0ff7629f8936d4cae | 2026-01-21T00:00:00-05:00 | PlannerRFT: Reinforcing Diffusion Planners through Closed-Loop and Sample-Efficient Fine-Tuning | arXiv:2601.12901v1 Announce Type: new Abstract: Diffusion-based planners have emerged as a promising approach for human-like trajectory generation in autonomous driving. Recent works incorporate reinforcement fine-tuning to enhance the robustness of diffusion planners through reward-oriented optimization in a generatio... | https://arxiv.org/abs/2601.12901 | Academic Papers | svg |
7f48d4758df788a01bdc58a14ef34df2eaf66b3040479604f2e007e8aeaad064 | 2026-01-21T00:00:00-05:00 | Audit du syst{\`e}me d'information et du mod{\`e}le de gouvernance de la Biblioth{\`e}que Num{\'e}rique de l'Espace universitaire Francophone (BNEUF) du projet Initiative pour le D{\'e}veloppement du Num{\'e}rique dans l'Espace Universitaire Francophone (IDNEUF) | arXiv:2601.12902v1 Announce Type: new Abstract: This document provides an assessment of the overall structure of the BNEUF system and how it operates within the framework of the Initiative for Digital Development in French speaking Universities (IDNEUF). This report aims to support the AUF's new strategy for 2021-2025,... | https://arxiv.org/abs/2601.12902 | Academic Papers | svg |
74d89418ad84f6fb7499d03401fcbc471352c13731aac4cdc78e050eabd894e3 | 2026-01-21T00:00:00-05:00 | Deep Temporal Graph Clustering: A Comprehensive Benchmark and Datasets | arXiv:2601.12903v1 Announce Type: new Abstract: Temporal Graph Clustering (TGC) is a new task with little attention, focusing on node clustering in temporal graphs. Compared with existing static graph clustering, it can find the balance between time requirement and space requirement (Time-Space Balance) through the int... | https://arxiv.org/abs/2601.12903 | Academic Papers | svg |
037c99fde7e3e5d616a18f187da3f866b3e6681b525b236205cadd802c7d96a9 | 2026-01-21T00:00:00-05:00 | From Prefix Cache to Fusion RAG Cache: Accelerating LLM Inference in Retrieval-Augmented Generation | arXiv:2601.12904v1 Announce Type: new Abstract: Retrieval-Augmented Generation enhances Large Language Models by integrating external knowledge, which reduces hallucinations but increases prompt length. This increase leads to higher computational costs and longer Time to First Token (TTFT). To mitigate this issue, exis... | https://arxiv.org/abs/2601.12904 | Academic Papers | svg |
5082fdd12c7f0d43b2c8ad2a1cac76f84bc5c0bfb8be862dacd6037be15ae7ed | 2026-01-21T00:00:00-05:00 | Gated Differentiable Working Memory for Long-Context Language Modeling | arXiv:2601.12906v1 Announce Type: new Abstract: Long contexts challenge transformers: attention scores dilute across thousands of tokens, critical information is often lost in the middle, and models struggle to adapt to novel patterns at inference time. Recent work on test-time adaptation addresses this by maintaining ... | https://arxiv.org/abs/2601.12906 | Academic Papers | svg |
7652722e274b02dc255b60fa3186bb3ff849147a432fe0e8ef95f60756ca0d7c | 2026-01-21T00:00:00-05:00 | Machine Learning for highly oscillatory differential equations | arXiv:2601.12907v1 Announce Type: new Abstract: Highly oscillatory differential equations, commonly encountered in multi-scale problems, are often too complex to solve analytically. However, several numerical methods have been developed to approximate their solutions. Although these methods have shown their efficiency,... | https://arxiv.org/abs/2601.12907 | Academic Papers | svg |
02c5d1b2b1c3df30308350a619d42a4a4dd021b5d559878416a12ff54ecae25c | 2026-01-21T00:00:00-05:00 | SciCoQA: Quality Assurance for Scientific Paper--Code Alignment | arXiv:2601.12910v1 Announce Type: new Abstract: We present SciCoQA, a dataset for detecting discrepancies between scientific publications and their codebases to ensure faithful implementations. We construct SciCoQA from GitHub issues and reproducibility papers, and to scale our dataset, we propose a synthetic data gene... | https://arxiv.org/abs/2601.12910 | Academic Papers | svg |
492c8aff34f0b0b088b68c422f1c002199632c85056c4f113c3745193f9c1cd4 | 2026-01-21T00:00:00-05:00 | Human Emotion Verification by Action Languages via Answer Set Programming | arXiv:2601.12912v1 Announce Type: new Abstract: In this paper, we introduce the action language C-MT (Mind Transition Language). It is built on top of answer set programming (ASP) and transition systems to represent how human mental states evolve in response to sequences of observable actions. Drawing on well-establish... | https://arxiv.org/abs/2601.12912 | Academic Papers | svg |
2b619278932c73d26bc887b081e08139f0613deffd054d6adc130c8b7081287b | 2026-01-21T00:00:00-05:00 | Actionable Interpretability Must Be Defined in Terms of Symmetries | arXiv:2601.12913v1 Announce Type: new Abstract: This paper argues that interpretability research in Artificial Intelligence is fundamentally ill-posed as existing definitions of interpretability are not *actionable*: they fail to provide formal principles from which concrete modelling and inferential rules can be deriv... | https://arxiv.org/abs/2601.12913 | Academic Papers | svg |
7339fe497fc62886969a914e6ba3b72925bd6e0d5524c3b1d7826574e4418c78 | 2026-01-21T00:00:00-05:00 | Static Detection of Core Structures in Tigress Virtualization-Based Obfuscation Using an LLVM Pass | arXiv:2601.12916v1 Announce Type: new Abstract: Malware often uses obfuscation to hinder security analysis. Among these techniques, virtualization-based obfuscation is particularly strong because it protects programs by translating original instructions into attacker-defined virtual machine (VM) bytecode, producing lon... | https://arxiv.org/abs/2601.12916 | Academic Papers | svg |
678cccc07e8058c070b8f26fe92f1455e18d1a0779e2693a046bd419e75d1fb8 | 2026-01-21T00:00:00-05:00 | CooperLLM: Cloud-Edge-End Cooperative Federated Fine-tuning for LLMs via ZOO-based Gradient Correction | arXiv:2601.12917v1 Announce Type: new Abstract: Large Language Models (LLMs) perform well on many NLP tasks, but fine-tuning them on resource-constrained mobile devices is challenging due to high memory and computation costs, despite growing demands for privacy-preserving personalization. Federated Learning (FL) enable... | https://arxiv.org/abs/2601.12917 | Academic Papers | svg |
afeaff5589961619debac0a3562200d6a9201a9068a3ebdc74d7529a9a6041d1 | 2026-01-21T00:00:00-05:00 | Dynamic Hand Gesture Recognition for Robot Manipulator Tasks | arXiv:2601.12918v1 Announce Type: new Abstract: This paper proposes a novel approach to recognizing dynamic hand gestures facilitating seamless interaction between humans and robots. Here, each robot manipulator task is assigned a specific gesture. There may be several such tasks, hence, several gestures. These gesture... | https://arxiv.org/abs/2601.12918 | Academic Papers | svg |
529119baf9fad26404b0a4a92c654ca774e2e54acbb8a40dafae8833b59bfff9 | 2026-01-21T00:00:00-05:00 | Supervision-by-Hallucination-and-Transfer: A Weakly-Supervised Approach for Robust and Precise Facial Landmark Detection | arXiv:2601.12919v1 Announce Type: new Abstract: High-precision facial landmark detection (FLD) relies on high-resolution deep feature representations. However, low-resolution face images or the compression (via pooling or strided convolution) of originally high-resolution images hinder the learning of such features, th... | https://arxiv.org/abs/2601.12919 | Academic Papers | svg |
765e5c70a7d9a347692f1afaba63041cc449ae6d7dc569d41a3b088fbd7cec2d | 2026-01-21T00:00:00-05:00 | Injecting Knowledge from Social Science Journals to Improve Indonesian Cultural Understanding by LLMs | arXiv:2601.12921v1 Announce Type: new Abstract: Recently there have been intensifying efforts to improve the understanding of Indonesian cultures by large language models (LLMs). An attractive source of cultural knowledge that has been largely overlooked is local journals of social science, which likely contain substan... | https://arxiv.org/abs/2601.12921 | Academic Papers | svg |
ab082bed8727e3ac10084633b07feb0bc65025b11dc700e6870d07d9b6af0763 | 2026-01-21T00:00:00-05:00 | Your Privacy Depends on Others: Collusion Vulnerabilities in Individual Differential Privacy | arXiv:2601.12922v1 Announce Type: new Abstract: Individual Differential Privacy (iDP) promises users control over their privacy, but this promise can be broken in practice. We reveal a previously overlooked vulnerability in sampling-based iDP mechanisms: while conforming to the iDP guarantees, an individual's privacy r... | https://arxiv.org/abs/2601.12922 | Academic Papers | svg |
260293437e4245de4ce469f255e3bbd46fb8a64cb734be50b09eca2f4af553b7 | 2026-01-21T00:00:00-05:00 | ForeDiffusion: Foresight-Conditioned Diffusion Policy via Future View Construction for Robot Manipulation | arXiv:2601.12925v1 Announce Type: new Abstract: Diffusion strategies have advanced visual motor control by progressively denoising high-dimensional action sequences, providing a promising method for robot manipulation. However, as task complexity increases, the success rate of existing baseline models decreases conside... | https://arxiv.org/abs/2601.12925 | Academic Papers | svg |
5aa6caa83b96e714c6e0b175225d7a47f74ed72015fbeaa9e32337e80b7cb08b | 2026-01-21T00:00:00-05:00 | Dual-Stream Collaborative Transformer for Image Captioning | arXiv:2601.12926v1 Announce Type: new Abstract: Current region feature-based image captioning methods have progressed rapidly and achieved remarkable performance. However, they are still prone to generating irrelevant descriptions due to the lack of contextual information and the over-reliance on generated partial desc... | https://arxiv.org/abs/2601.12926 | Academic Papers | svg |
aa795a022f64fe5ee00e10a580cf0f6decb9d054812e09e96be269d0e32b64fc | 2026-01-21T00:00:00-05:00 | A Benchmark for Language Models in Real-World System Building | arXiv:2601.12927v1 Announce Type: new Abstract: During migration across instruction set architectures (ISAs), software package build repair is a critical task for ensuring the reliability of software deployment and the stability of modern operating systems. While Large Language Models (LLMs) have shown promise in tackl... | https://arxiv.org/abs/2601.12927 | Academic Papers | svg |
6bb7aa73547af94a2da199429cd8ef2ba4c7af87d16562e112e8ddec9df85a20 | 2026-01-21T00:00:00-05:00 | An efficient heuristic for geometric analysis of cell deformations | arXiv:2601.12928v1 Announce Type: new Abstract: Sickle cell disease causes erythrocytes to become sickle-shaped, affecting their movement in the bloodstream and reducing oxygen delivery. It has a high global prevalence and places a significant burden on healthcare systems, especially in resource-limited regions. Automa... | https://arxiv.org/abs/2601.12928 | Academic Papers | svg |
48e33f0fcca7872d20409c3431426bc09e1df0925fbad9cd3b9f0b54b367fcfc | 2026-01-21T00:00:00-05:00 | Membership Inference Test: Auditing Training Data in Object Classification Models | arXiv:2601.12929v1 Announce Type: new Abstract: In this research, we analyze the performance of Membership Inference Tests (MINT), focusing on determining whether given data were utilized during the training phase, specifically in the domain of object recognition. Within the area of object recognition, we propose and d... | https://arxiv.org/abs/2601.12929 | Academic Papers | svg |
b71fcb65c73fd15c0dba8a06fb1703b51da1435de42958a04a84ac9cd3fe33bc | 2026-01-21T00:00:00-05:00 | Online Continual Learning for Time Series: a Natural Score-driven Approach | arXiv:2601.12931v1 Announce Type: new Abstract: Online continual learning (OCL) methods adapt to changing environments without forgetting past knowledge. Similarly, online time series forecasting (OTSF) is a real-world problem where data evolve in time and success depends on both rapid adaptation and long-term memory. ... | https://arxiv.org/abs/2601.12931 | Academic Papers | svg |
9f70038ba157fb1d8408b1b7723449a8ba3b952a20341c122ecabf12c6f3b0d0 | 2026-01-21T00:00:00-05:00 | Perception of Deepfakes among Bangladeshi Women | arXiv:2601.12933v1 Announce Type: new Abstract: As deepfake technology becomes more accessible, concerns about its misuse and societal impact are escalating, particularly in regions like the Global South where digital literacy and regulatory measures are often limited. While previous research has explored deepfakes in ... | https://arxiv.org/abs/2601.12933 | Academic Papers | svg |
e56b3582caa5a0a7a6a4a48124581b8951535045fa1571f590bef5736f5a08e1 | 2026-01-21T00:00:00-05:00 | Bangladesh AI Readiness: Perspectives from the Academia, Industry, and Government | arXiv:2601.12934v1 Announce Type: new Abstract: Artificial Intelligence (AI) readiness in the Global South extends beyond infrastructure to include curriculum design, workforce development, and cross-sector collaboration. Bangladesh, ranked 82nd in the 2023 Oxford Insights AI Readiness Index, exhibits significant defic... | https://arxiv.org/abs/2601.12934 | Academic Papers | svg |
1db870a453a42fd83caf6eded358d1b65e035074d875cde73bcbda5401e0a79d | 2026-01-21T00:00:00-05:00 | QASA: Quality-Guided K-Adaptive Slot Attention for Unsupervised Object-Centric Learning | arXiv:2601.12936v1 Announce Type: new Abstract: Slot Attention, an approach that binds different objects in a scene to a set of "slots", has become a leading method in unsupervised object-centric learning. Most methods assume a fixed slot count K, and to better accommodate the dynamic nature of object cardinality, a fe... | https://arxiv.org/abs/2601.12936 | Academic Papers | svg |
7311be2ee64c917687e9a8d8763b5358dac3c6f30eda8138b38b87709d19503e | 2026-01-21T00:00:00-05:00 | On the Evidentiary Limits of Membership Inference for Copyright Auditing | arXiv:2601.12937v1 Announce Type: new Abstract: As large language models (LLMs) are trained on increasingly opaque corpora, membership inference attacks (MIAs) have been proposed to audit whether copyrighted texts were used during training, despite growing concerns about their reliability under realistic conditions. We... | https://arxiv.org/abs/2601.12937 | Academic Papers | svg |
a3f61688b4d159f0aa559ece7235472979596a4fb90bcd88035eab9686bfdf75 | 2026-01-21T00:00:00-05:00 | The Post-Turing Condition: Conceptualising Artificial Subjectivity and Synthetic Sociality | arXiv:2601.12938v1 Announce Type: new Abstract: In the Post-Turing era, artificial intelligence increasingly shapes social coordination and meaning formation rather than merely automating cognitive tasks. The central challenge is therefore not whether machines become conscious, but whether processes of interpretation a... | https://arxiv.org/abs/2601.12938 | Academic Papers | svg |
e5d430f8233aa86aa4b3a57b02797849f01967dc425023cba45997ff8f7e64f2 | 2026-01-21T00:00:00-05:00 | Active Inference-Driven World Modeling for Adaptive UAV Swarm Trajectory Design | arXiv:2601.12939v1 Announce Type: new Abstract: This paper proposes an Active Inference-based framework for autonomous trajectory design in UAV swarms. The method integrates probabilistic reasoning and self-learning to enable distributed mission allocation, route ordering, and motion planning. Expert trajectories gener... | https://arxiv.org/abs/2601.12939 | Academic Papers | svg |
3201535e241695f73b077c5c2cfab0c82ea07224b2a690e20ad59a354d61e070 | 2026-01-21T00:00:00-05:00 | Dependently-Typed AARA: A Non-Affine Approach for Resource Analysis of Higher-Order Programs | arXiv:2601.12943v1 Announce Type: new Abstract: Static resource analysis determines the resource consumption (e.g., time complexity) of a program without executing it. Among the numerous existing approaches for resource analysis, affine type systems have been one dominant approach. However, these affine type systems fa... | https://arxiv.org/abs/2601.12943 | Academic Papers | svg |
c378fbb6de75dd9fe685c2a9ebda8381c44ebfa385a369f142dee7c5251c82fd | 2026-01-21T00:00:00-05:00 | On the Concavity of Tsallis Entropy along the Heat Flow | arXiv:2601.12944v1 Announce Type: new Abstract: We demonstrate the concavity of the Tsallis entropy along the heat flow for general dimensions, expanding upon the findings of Wu et al 2025 and Hung 2022, which were previously limited to the one-dimensional case. The core of the proof is a novel estimate of the terms in... | https://arxiv.org/abs/2601.12944 | Academic Papers | svg |
0c9624a0fe4e4cc4320aec9f4d0c145c471ad258f0e97d9a94adb76bcf1699a1 | 2026-01-21T00:00:00-05:00 | A Component-Based Survey of Interactions between Large Language Models and Multi-Armed Bandits | arXiv:2601.12945v1 Announce Type: new Abstract: Large language models (LLMs) have become powerful and widely used systems for language understanding and generation, while multi-armed bandit (MAB) algorithms provide a principled framework for adaptive decision-making under uncertainty. This survey explores the potential... | https://arxiv.org/abs/2601.12945 | Academic Papers | svg |
bf9bdaa22c0cc2ec08f0048846d3bd8e3edda7c0c2e471b1bfc8ff8a5f8c1bb6 | 2026-01-21T00:00:00-05:00 | AI-generated data contamination erodes pathological variability and diagnostic reliability | arXiv:2601.12946v1 Announce Type: new Abstract: Generative artificial intelligence (AI) is rapidly populating medical records with synthetic content, creating a feedback loop where future models are increasingly at risk of training on uncurated AI-generated data. However, the clinical consequences of this AI-generated ... | https://arxiv.org/abs/2601.12946 | Academic Papers | svg |
9f7faeb154e463efdaa155631d32d430e35382997749217006f40467546b8938 | 2026-01-21T00:00:00-05:00 | GazeD: Context-Aware Diffusion for Accurate 3D Gaze Estimation | arXiv:2601.12948v1 Announce Type: new Abstract: We introduce GazeD, a new 3D gaze estimation method that jointly provides 3D gaze and human pose from a single RGB image. Leveraging the ability of diffusion models to deal with uncertainty, it generates multiple plausible 3D gaze and pose hypotheses based on the 2D conte... | https://arxiv.org/abs/2601.12948 | Academic Papers | svg |
f75b47857e20958be9767a45f67064711a89eb13b0dcc5526669936a3ebd278e | 2026-01-21T00:00:00-05:00 | Beyond Accuracy: Characterizing Code Comprehension Capabilities in (Large) Language Models | arXiv:2601.12951v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly integrated into software engineering workflows, yet current benchmarks provide only coarse performance summaries that obscure the diverse capabilities and limitations of these models. This paper investigates whether LLMs' code... | https://arxiv.org/abs/2601.12951 | Academic Papers | svg |
a641654aa63048a8bed3acbc9f3522eaab3013b6fa834f7dd3bed88c275911f7 | 2026-01-21T00:00:00-05:00 | Imitation learning-based spacecraft rendezvous and docking method with Expert Demonstration | arXiv:2601.12952v1 Announce Type: new Abstract: Existing spacecraft rendezvous and docking control methods largely rely on predefined dynamic models and often exhibit limited robustness in realistic on-orbit environments. To address this issue, this paper proposes an Imitation Learning-based spacecraft rendezvous and d... | https://arxiv.org/abs/2601.12952 | Academic Papers | svg |
e75ebf657667362fb5eae3fb694a697e18f0fc3b3a69c6bd03daaab2b90d8071 | 2026-01-21T00:00:00-05:00 | StyMam: A Mamba-Based Generator for Artistic Style Transfer | arXiv:2601.12954v1 Announce Type: new Abstract: Image style transfer aims to integrate the visual patterns of a specific artistic style into a content image while preserving its content structure. Existing methods mainly rely on the generative adversarial network (GAN) or stable diffusion (SD). GAN-based approaches usi... | https://arxiv.org/abs/2601.12954 | Academic Papers | svg |
8ec170461c9a3694a27a86ae2ea60b723d8529e940f9f86b34394525121e6c66 | 2026-01-21T00:00:00-05:00 | Codes Correcting Few Restricted Errors | arXiv:2601.12959v1 Announce Type: new Abstract: We consider linear codes over a field in which the error values are restricted to a subgroup of its unit group. This scenario captures Lee distance codes as well as codes over the Gaussian or Eisenstein integers. Codes correcting restricted errors gained increased attenti... | https://arxiv.org/abs/2601.12959 | Academic Papers | svg |
f43e91bdd600cd04f9e83bda7bfdf11a066daf64c3406578b0d055e1ddaf1e51 | 2026-01-21T00:00:00-05:00 | Trustworthy Data-driven Chronological Age Estimation from Panoramic Dental Images | arXiv:2601.12960v1 Announce Type: new Abstract: Integrating deep learning into healthcare enables personalized care but raises trust issues due to model opacity. To improve transparency, we propose a system for dental age estimation from panoramic images that combines an opaque and a transparent method within a natural... | https://arxiv.org/abs/2601.12960 | Academic Papers | svg |
1a48122fbb86048390f4d8ef23e6e42904dc9a0aea262989c11c97cfbed70d78 | 2026-01-21T00:00:00-05:00 | Supervised Learning for Game Music Segmentation | arXiv:2601.12961v1 Announce Type: new Abstract: At present, neural network-based models, including transformers, struggle to generate memorable and readily comprehensible music from unified and repetitive musical material due to a lack of understanding of musical structure. Consequently, these models are rarely employe... | https://arxiv.org/abs/2601.12961 | Academic Papers | svg |
f5057c2da0697dc448dcc1e7faeb393dd7f6c21f0ea8be06c23e143f36f22187 | 2026-01-21T00:00:00-05:00 | ACE-Align: Attribute Causal Effect Alignment for Cultural Values under Varying Persona Granularities | arXiv:2601.12962v1 Announce Type: new Abstract: Ensuring that large language models (LLMs) respect diverse cultural values is crucial for social equity. However, existing approaches often treat cultural groups as homogeneous and overlook within-group heterogeneity induced by intersecting demographic attributes, leading... | https://arxiv.org/abs/2601.12962 | Academic Papers | svg |
34343f1d31401d942589d68c48087d3ef0362198105874f5d66182388fc1083c | 2026-01-21T00:00:00-05:00 | Cross-Scale Pretraining: Enhancing Self-Supervised Learning for Low-Resolution Satellite Imagery for Semantic Segmentation | arXiv:2601.12964v1 Announce Type: new Abstract: Self-supervised pretraining in remote sensing is mostly done using mid-spatial resolution (MR) image datasets due to their high availability. Given the release of high-resolution (HR) datasets, we ask how HR datasets can be included in self-supervised pretraining to enhan... | https://arxiv.org/abs/2601.12964 | Academic Papers | svg |
fd86c0b958b066f02f4ed1ae694102ea56b2e96a85b9c47567742f08d9d96753 | 2026-01-21T00:00:00-05:00 | Deterministic Dynamics of Sampling Processes in Score-Based Diffusion Models with Multiplicative Noise Conditioning | arXiv:2601.12965v1 Announce Type: new Abstract: Score-based diffusion models generate new samples by learning the score function associated with a diffusion process. While the effectiveness of these models can be theoretically explained using differential equations related to the sampling process, previous work by Song... | https://arxiv.org/abs/2601.12965 | Academic Papers | svg |
cd50604c97b164fabe62e128e36cf3f3a095b12cb636d6cac753c6d34497d1a3 | 2026-01-21T00:00:00-05:00 | Lombard Speech Synthesis for Any Voice with Controllable Style Embeddings | arXiv:2601.12966v1 Announce Type: new Abstract: The Lombard effect plays a key role in natural communication, particularly in noisy environments or when addressing hearing-impaired listeners. We present a controllable text-to-speech (TTS) system capable of synthesizing Lombard speech for any speaker without requiring e... | https://arxiv.org/abs/2601.12966 | Academic Papers | svg |
463d5ce29d1d485a8b687c59f30382564928392a0cc20cae592c77d4067711d5 | 2026-01-21T00:00:00-05:00 | Sutradhara: An Intelligent Orchestrator-Engine Co-design for Tool-based Agentic Inference | arXiv:2601.12967v1 Announce Type: new Abstract: Agentic applications are LLMs that iteratively invoke external tools to accomplish complex tasks. Such tool-based agents are rapidly becoming the dominant paradigm for deploying language models in production. Unlike traditional single-turn inference, agentic workloads cha... | https://arxiv.org/abs/2601.12967 | Academic Papers | svg |
47195ffdba9df9b460e04f6201a4219572f4e939cf10396612413f7553a45e16 | 2026-01-21T00:00:00-05:00 | Architecture-Optimization Co-Design for Physics-Informed Neural Networks Via Attentive Representations and Conflict-Resolved Gradients | arXiv:2601.12971v1 Announce Type: new Abstract: Physics-Informed Neural Networks (PINNs) provide a learning-based framework for solving partial differential equations (PDEs) by embedding governing physical laws into neural network training. In practice, however, their performance is often hindered by limited representa... | https://arxiv.org/abs/2601.12971 | Academic Papers | svg |
9ad4ee3ca632216f3b2eb2943a7d6cf4ad3ba5ac4777d76ead7fbf220115d44e | 2026-01-21T00:00:00-05:00 | Pardon? Evaluating Conversational Repair in Large Audio-Language Models | arXiv:2601.12973v1 Announce Type: new Abstract: Large Audio-Language Models (LALMs) have demonstrated strong performance in spoken question answering (QA), with existing evaluations primarily focusing on answer accuracy and robustness to acoustic perturbations. However, such evaluations implicitly assume that spoken in... | https://arxiv.org/abs/2601.12973 | Academic Papers | svg |
09ab1952fbdf4ea9ac4b703581bae0aa73f81df07fbb424748ebd93ef8c96b71 | 2026-01-21T00:00:00-05:00 | Bridging the Knowledge-Action Gap by Evaluating LLMs in Dynamic Dental Clinical Scenarios | arXiv:2601.12974v1 Announce Type: new Abstract: The transition of Large Language Models (LLMs) from passive knowledge retrievers to autonomous clinical agents demands a shift in evaluation-from static accuracy to dynamic behavioral reliability. To explore this boundary in dentistry, a domain where high-quality AI advic... | https://arxiv.org/abs/2601.12974 | Academic Papers | svg |
aeb67961e0ff24480bb2c93003cfa9f72248fcfcff8482a4ce3c6b44c07a6eb3 | 2026-01-21T00:00:00-05:00 | Kd-tree Based Wasserstein Distance Approximation for High-Dimensional Data | arXiv:2601.12975v1 Announce Type: new Abstract: The Wasserstein distance is a discrepancy measure between probability distributions, defined by an optimal transport problem. It has been used for various tasks such as retrieving similar items in high-dimensional images or text data. In retrieval applications, however, t... | https://arxiv.org/abs/2601.12975 | Academic Papers | svg |
567b6e6ee92e663dff1f41f795a102dc4b5178443470749b85fc0ff45187855b | 2026-01-21T00:00:00-05:00 | Reproducibility in Event-Log Research: A Parametrised Generator and Benchmark for Event-based Signatures | arXiv:2601.12978v1 Announce Type: new Abstract: Event-based datasets are crucial for cybersecurity analysis. A key use case is detecting event-based signatures, which represent attacks spanning multiple events and can only be understood once the relevant events are identified and linked. Analysing event datasets is ess... | https://arxiv.org/abs/2601.12978 | Academic Papers | svg |
68063f8de08cfae285b8419316632412b89e294fbb41cb72b32a50d51b32a2c9 | 2026-01-21T00:00:00-05:00 | The Bitter Lesson of Diffusion Language Models for Agentic Workflows: A Comprehensive Reality Check | arXiv:2601.12979v1 Announce Type: new Abstract: The pursuit of real-time agentic interaction has driven interest in Diffusion-based Large Language Models (dLLMs) as alternatives to auto-regressive backbones, promising to break the sequential latency bottleneck. However, does such efficiency gains translate into effecti... | https://arxiv.org/abs/2601.12979 | Academic Papers | svg |
0d74e1526814df96705dbc4a7b27e93c9af01fa00d19baf3a2f42e8fe7340863 | 2026-01-21T00:00:00-05:00 | Path to Diversity: A Primer on ISAC-izing Commodity Wi-Fi for Practical Deployments | arXiv:2601.12980v1 Announce Type: new Abstract: Integrated Sensing and Communication (ISAC) has emerged as a key paradigm in next-generation wireless networks. While the ubiquity and low cost of commodity Wi-Fi make it an ideal platform for wide-scale sensing, it is the continuous evolution of Wi-Fi standards-towards h... | https://arxiv.org/abs/2601.12980 | Academic Papers | svg |
172e3605763897c163680585f102813d0c1ea20caa7275557721a4dd294a39c6 | 2026-01-21T00:00:00-05:00 | Early Prediction of Type 2 Diabetes Using Multimodal data and Tabular Transformers | arXiv:2601.12981v1 Announce Type: new Abstract: This study introduces a novel approach for early Type 2 Diabetes Mellitus (T2DM) risk prediction using a tabular transformer (TabTrans) architecture to analyze longitudinal patient data. By processing patients` longitudinal health records and bone-related tabular data, ou... | https://arxiv.org/abs/2601.12981 | Academic Papers | svg |
031ecef6730b883037bb4520a84c35e94adf0775dfd3c7753c66dc444cff93e7 | 2026-01-21T00:00:00-05:00 | ChartAttack: Testing the Vulnerability of LLMs to Malicious Prompting in Chart Generation | arXiv:2601.12983v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are increasingly used to automate chart generation from data tables, enabling efficient data analysis and reporting but also introducing new misuse risks. In this work, we introduce ChartAttack, a novel framework for evaluating how... | https://arxiv.org/abs/2601.12983 | Academic Papers | svg |
b0da570fea1ba603eea29c68dd09203f12ef3a067e85d8201548e149701811ac | 2026-01-21T00:00:00-05:00 | Rules, Resources, and Restrictions: A Taxonomy of Task-Based Information Request Intents | arXiv:2601.12985v1 Announce Type: new Abstract: Understanding and classifying query intents can improve retrieval effectiveness by helping align search results with the motivations behind user queries. However, existing intent taxonomies are typically derived from system log data and capture mostly isolated information... | https://arxiv.org/abs/2601.12985 | Academic Papers | svg |
d535658779a991f3214714f7795c083eea37fa94e0c5591d4ebe75f98e886bfb | 2026-01-21T00:00:00-05:00 | KinGuard: Hierarchical Kinship-Aware Fingerprinting to Defend Against Large Language Model Stealing | arXiv:2601.12986v1 Announce Type: new Abstract: Protecting the intellectual property of large language models requires robust ownership verification. Conventional backdoor fingerprinting, however, is flawed by a stealth-robustness paradox: to be robust, these methods force models to memorize fixed responses to high-per... | https://arxiv.org/abs/2601.12986 | Academic Papers | svg |
8d36c2667d6d444d5ba46ebd20e9bb42cfaba93369256959e992567b62a375a1 | 2026-01-21T00:00:00-05:00 | Guiding vector field-based guidance under wind disturbances applied to a tailsitter UAV | arXiv:2601.12987v1 Announce Type: new Abstract: This paper develops a guidance control law based on a parametric Guiding Vector Field (GVF) and integrates it with a state-of-the-art acceleration and attitude control architecture for tailsitters. The resulting framework enables a direct comparison between traditional tr... | https://arxiv.org/abs/2601.12987 | Academic Papers | svg |
f29f0274fc97b6dd785623a90232ac16399ff8c6335152ddd5b71e90f8a39a44 | 2026-01-21T00:00:00-05:00 | PaperGuide: Making Small Language-Model Paper-Reading Agents More Efficient | arXiv:2601.12988v1 Announce Type: new Abstract: The accelerating growth of the scientific literature makes it increasingly difficult for researchers to track new advances through manual reading alone. Recent progress in large language models (LLMs) has therefore spurred interest in autonomous agents that can read scien... | https://arxiv.org/abs/2601.12988 | Academic Papers | svg |
9dbde8f603935cc54fb624e240e0cd2c15edcb08da2bb247e9a06f8c3cd34df0 | 2026-01-21T00:00:00-05:00 | Enshrined Proposer Builder Separation in the presence of Maximal Extractable Value | arXiv:2601.12989v1 Announce Type: new Abstract: In blockchain systems operating under the Proof-of-Stake (PoS) consensus mechanism, fairness in transaction processing is essential to preserving decentralization and maintaining user trust. However, with the emergence of Maximal Extractable Value (MEV), concerns about ec... | https://arxiv.org/abs/2601.12989 | Academic Papers | svg |
f8e7ad8ef4dd956cd2310e47fece03d5abd23ae354043d90c7f9f5855e059847 | 2026-01-21T00:00:00-05:00 | RAGExplorer: A Visual Analytics System for the Comparative Diagnosis of RAG Systems | arXiv:2601.12991v1 Announce Type: new Abstract: The advent of Retrieval-Augmented Generation (RAG) has significantly enhanced the ability of Large Language Models (LLMs) to produce factually accurate and up-to-date responses. However, the performance of a RAG system is not determined by a single component but emerges f... | https://arxiv.org/abs/2601.12991 | Academic Papers | svg |
b6235a1d082464c75bfe17a40780e427a1138aa681ca640fb39dbd5de5458b11 | 2026-01-21T00:00:00-05:00 | Being-H0.5: Scaling Human-Centric Robot Learning for Cross-Embodiment Generalization | arXiv:2601.12993v1 Announce Type: new Abstract: We introduce Being-H0.5, a foundational Vision-Language-Action (VLA) model designed for robust cross-embodiment generalization across diverse robotic platforms. While existing VLAs often struggle with morphological heterogeneity and data scarcity, we propose a human-centr... | https://arxiv.org/abs/2601.12993 | Academic Papers | svg |
cdfa2045091f36f95e519086b3048db5984c593cd47c78e9cfb88d172fadfaac | 2026-01-21T00:00:00-05:00 | AsyncBEV: Cross-modal Flow Alignment in Asynchronous 3D Object Detection | arXiv:2601.12994v1 Announce Type: new Abstract: In autonomous driving, multi-modal perception tasks like 3D object detection typically rely on well-synchronized sensors, both at training and inference. However, despite the use of hardware- or software-based synchronization algorithms, perfect synchrony is rarely guaran... | https://arxiv.org/abs/2601.12994 | Academic Papers | svg |
4e88ac9a2255248508135da5d43443c91bdc2aa4289ab0d8399438a082206741 | 2026-01-21T00:00:00-05:00 | Graph Reasoning Paradigm: Structured and Symbolic Reasoning with Topology-Aware Reinforcement Learning for Large Language Models | arXiv:2601.12995v1 Announce Type: new Abstract: Long Chain-of-Thought (LCoT), achieved by Reinforcement Learning with Verifiable Rewards (RLVR), has proven effective in enhancing the reasoning capabilities of Large Language Models (LLMs). However, reasoning in current LLMs is primarily generated as plain text, where pe... | https://arxiv.org/abs/2601.12995 | Academic Papers | svg |
44a2b2fedf2cd0fc18f698a396265baf89399a5f8f1a03373f71eae9ff20311a | 2026-01-21T00:00:00-05:00 | OFA-MAS: One-for-All Multi-Agent System Topology Design based on Mixture-of-Experts Graph Generative Models | arXiv:2601.12996v1 Announce Type: new Abstract: Multi-Agent Systems (MAS) offer a powerful paradigm for solving complex problems, yet their performance is critically dependent on the design of their underlying collaboration topology. As MAS become increasingly deployed in web services (e.g., search engines), designing ... | https://arxiv.org/abs/2601.12996 | Academic Papers | svg |
5497ff9098052d465208621ebca38c4c0056cd6002394238e65c4c5e75e7dba7 | 2026-01-21T00:00:00-05:00 | Weighted-Hamming Metric: Bounds and Codes | arXiv:2601.12998v1 Announce Type: new Abstract: The weighted-Hamming metric generalizes the Hamming metric by assigning different weights to blocks of coordinates. It is well-suited for applications such as coding over independent parallel channels, each of which has a different level of importance or noise. From a cod... | https://arxiv.org/abs/2601.12998 | Academic Papers | svg |
47cefe685b21b95474b8fa99d0c3478106f06e32595a1d4f0cf2d1b5c26672d1 | 2026-01-21T00:00:00-05:00 | PrivFly: A Privacy-Preserving Self-Supervised Framework for Rare Attack Detection in IoFT | arXiv:2601.13003v1 Announce Type: new Abstract: The Internet of Flying Things (IoFT) plays a vital role in modern applications such as aerial surveillance and smart mobility. However, it remains highly vulnerable to cyberattacks that threaten the confidentiality, integrity, and availability of sensitive data. Developin... | https://arxiv.org/abs/2601.13003 | Academic Papers | svg |
feaf49fb4eb2b2c3359f58a3b9c0510b5ce4e7d58c4977b1c46b55879c8647d9 | 2026-01-21T00:00:00-05:00 | An iterative approach to a fluid-rigid body interaction problem | arXiv:2601.13004v1 Announce Type: new Abstract: We study a novel approach for the existence of solutions to an incompressible fluid-rigid body interaction problem in three dimensions. Our approach introduces an iteration based on a sequence of related problems posed on domains with prescribed evolution. In particular w... | https://arxiv.org/abs/2601.13004 | Academic Papers | svg |
e040b0d1be2694edb3133587e7f071cb5d169b850806164cbd36ee0ce9ffeb3c | 2026-01-21T00:00:00-05:00 | ArchAgent: Scalable Legacy Software Architecture Recovery with LLMs | arXiv:2601.13007v1 Announce Type: new Abstract: Recovering accurate architecture from large-scale legacy software is hindered by architectural drift, missing relations, and the limited context of Large Language Models (LLMs). We present ArchAgent, a scalable agent-based framework that combines static analysis, adaptive... | https://arxiv.org/abs/2601.13007 | Academic Papers | svg |
29938fe09b7fef81d7ee6232271a38fc856b16a98e85f5b4883bfa989f5deaa3 | 2026-01-21T00:00:00-05:00 | HT-GNN: Hyper-Temporal Graph Neural Network for Customer Lifetime Value Prediction in Baidu Ads | arXiv:2601.13013v1 Announce Type: new Abstract: Lifetime value (LTV) prediction is crucial for news feed advertising, enabling platforms to optimize bidding and budget allocation for long-term revenue growth. However, it faces two major challenges: (1) demographic-based targeting creates segment-specific LTV distributi... | https://arxiv.org/abs/2601.13013 | Academic Papers | svg |
633029a3f1a3e37e9d12eaa26dff403cde14ae3741833efebcbf8ca3bc3b9177 | 2026-01-21T00:00:00-05:00 | MeltRTL: Multi-Expert LLMs with Inference-time Intervention for RTL Code Generation | arXiv:2601.13015v1 Announce Type: new Abstract: The automated generation of hardware register-transfer level (RTL) code with large language models (LLMs) shows promise, yet current solutions struggle to produce syntactically and functionally correct code for complex digital designs. This paper introduces MeltRTL, a nov... | https://arxiv.org/abs/2601.13015 | Academic Papers | svg |
17f893e2a3298f6be8c2dbc23c483eece61d7edfcc85e8760ea228a5f66f6248 | 2026-01-21T00:00:00-05:00 | Bi-Attention HateXplain : Taking into account the sequential aspect of data during explainability in a multi-task context | arXiv:2601.13018v1 Announce Type: new Abstract: Technological advances in the Internet and online social networks have brought many benefits to humanity. At the same time, this growth has led to an increase in hate speech, the main global threat. To improve the reliability of black-box models used for hate speech detec... | https://arxiv.org/abs/2601.13018 | Academic Papers | svg |
97dac88272d0d24e033417448cb8ad0f5b35b563325ae82e43b08c8a219d4418 | 2026-01-21T00:00:00-05:00 | PASs-MoE: Mitigating Misaligned Co-drift among Router and Experts via Pathway Activation Subspaces for Continual Learning | arXiv:2601.13020v1 Announce Type: new Abstract: Continual instruction tuning (CIT) requires multimodal large language models (MLLMs) to adapt to a stream of tasks without forgetting prior capabilities. A common strategy is to isolate updates by routing inputs to different LoRA experts. However, existing LoRA-based Mixt... | https://arxiv.org/abs/2601.13020 | Academic Papers | svg |
7f5544673d1ec7ed01810f5eb97234028e7c5ed2e035374fb556e0e61b185eea | 2026-01-21T00:00:00-05:00 | Enhancing Generalization in Sickle Cell Disease Diagnosis through Ensemble Methods and Feature Importance Analysis | arXiv:2601.13021v1 Announce Type: new Abstract: This work presents a novel approach for selecting the optimal ensemble-based classification method and features with a primarly focus on achieving generalization, based on the state-of-the-art, to provide diagnostic support for Sickle Cell Disease using peripheral blood s... | https://arxiv.org/abs/2601.13021 | Academic Papers | svg |
ab8507d1208dc8c881f66f17b7e2877631d30734acdb594f51e21bcdb484680e | 2026-01-21T00:00:00-05:00 | Tears or Cheers? Benchmarking LLMs via Culturally Elicited Distinct Affective Responses | arXiv:2601.13024v1 Announce Type: new Abstract: Culture serves as a fundamental determinant of human affective processing and profoundly shapes how individuals perceive and interpret emotional stimuli. Despite this intrinsic link extant evaluations regarding cultural alignment within Large Language Models primarily pri... | https://arxiv.org/abs/2601.13024 | Academic Papers | svg |
57dcedc75fdedd9f2ceb2a8ad45001724dc4b27255655328dac69a0c5490d7cc | 2026-01-21T00:00:00-05:00 | Think3D: Thinking with Space for Spatial Reasoning | arXiv:2601.13029v1 Announce Type: new Abstract: Understanding and reasoning about the physical world requires spatial intelligence: the ability to interpret geometry, perspective, and spatial relations beyond 2D perception. While recent vision large models (VLMs) excel at visual understanding, they remain fundamentally... | https://arxiv.org/abs/2601.13029 | Academic Papers | svg |
585cad05bcddf49553fe25a30a3ce6bbcb3af3debe26ebe3c96a88eb84de49fb | 2026-01-21T00:00:00-05:00 | Post-Quantum Secure Aggregation via Code-Based Homomorphic Encryption | arXiv:2601.13031v1 Announce Type: new Abstract: Secure aggregation enables aggregation of inputs from multiple parties without revealing individual contributions to the server or other clients. Existing post-quantum approaches based on homomorphic encryption offer practical efficiency but predominantly rely on lattice-... | https://arxiv.org/abs/2601.13031 | Academic Papers | svg |
bf9f0956f378c7f1bb92f35fd17046c97122e898cb75168578623a4df2e02533 | 2026-01-21T00:00:00-05:00 | SASA: Semantic-Aware Contrastive Learning Framework with Separated Attention for Triple Classification | arXiv:2601.13035v1 Announce Type: new Abstract: Knowledge Graphs~(KGs) often suffer from unreliable knowledge, which restricts their utility. Triple Classification~(TC) aims to determine the validity of triples from KGs. Recently, text-based methods learn entity and relation representations from natural language descri... | https://arxiv.org/abs/2601.13035 | Academic Papers | svg |
3ca100a8bdf493d2f7d23f99e3e3f8f0a7b4aa6548999df3c61a9dd8f6cdd6c0 | 2026-01-21T00:00:00-05:00 | Feedforward-Feedback Integration in Flight Control: Reinforcement Learning with Sliding Mode Control | arXiv:2601.13037v1 Announce Type: new Abstract: Learning-based controllers leverage nonlinear couplings and enhance transients but seldom offer guarantees under tight input constraints. Robust feedback like sliding-mode control (SMC) provides these guarantees but is conservative in isolation. This paper creates a learn... | https://arxiv.org/abs/2601.13037 | Academic Papers | svg |
0cbc58d8e1fd684dcb308a41d92f4f3893b0f38d9638f445442eaaac92b33515 | 2026-01-21T00:00:00-05:00 | Solving Generalized Lyapunov Equations with guarantees: application to the Model Reduction of Switched Linear Systems | arXiv:2601.13039v1 Announce Type: new Abstract: We present an efficient strategy to approximate the solutions of large-scale generalized Lyapunov equations (GLEs) with rigorous, computable error guarantees. This work is motivated by applications in model order reduction (MOR) of switched linear systems (SLS) in control... | https://arxiv.org/abs/2601.13039 | Academic Papers | svg |
5f8da8d7e9b44dbc91f254d500ea58eba954204a92d75d7347eab6ca41a332c4 | 2026-01-21T00:00:00-05:00 | CPU-less parallel execution of lambda calculus in digital logic | arXiv:2601.13040v1 Announce Type: new Abstract: While transistor density is still increasing, clock speeds are not, motivating the search for new parallel architectures. One approach is to completely abandon the concept of CPU -- and thus serial imperative programming -- and instead to specify and execute tasks in para... | https://arxiv.org/abs/2601.13040 | Academic Papers | svg |
8707719c9c0497964a1955f6f217a84beb1dad93cacbb1e730e575a84b9aa804 | 2026-01-21T00:00:00-05:00 | High-Throughput and Scalable Secure Inference Protocols for Deep Learning with Packed Secret Sharing | arXiv:2601.13041v1 Announce Type: new Abstract: Most existing secure neural network inference protocols based on secure multi-party computation (MPC) typically support at most four participants, demonstrating severely limited scalability. Liu et al. (USENIX Security'24) presented the first relatively practical approach... | https://arxiv.org/abs/2601.13041 | Academic Papers | svg |
bd9aaab012f805eaeafb7abc98c70062a86c6113e5c64a08b35db327d8741b13 | 2026-01-21T00:00:00-05:00 | Static Is Not Enough: A Comparative Study of VR and SpaceMouse in Static and Dynamic Teleoperation Tasks | arXiv:2601.13042v1 Announce Type: new Abstract: Imitation learning relies on high-quality demonstrations, and teleoperation is a primary way to collect them, making teleoperation interface choice crucial for the data. Prior work mainly focused on static tasks, i.e., discrete, segmented motions, yet demonstrations also ... | https://arxiv.org/abs/2601.13042 | Academic Papers | svg |
207a8986786747834f8f34d9bacefdeffe45c5dae30b90eba18100bf96e93af7 | 2026-01-21T00:00:00-05:00 | Typhoon ASR Real-time: FastConformer-Transducer for Thai Automatic Speech Recognition | arXiv:2601.13044v1 Announce Type: new Abstract: Large encoder-decoder models like Whisper achieve strong offline transcription but remain impractical for streaming applications due to high latency. However, due to the accessibility of pre-trained checkpoints, the open Thai ASR landscape remains dominated by these offli... | https://arxiv.org/abs/2601.13044 | Academic Papers | svg |
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