id stringlengths 64 64 | published stringlengths 19 25 | title stringlengths 7 262 | description stringlengths 6 54.4k | link stringlengths 31 227 | category stringclasses 6
values | image stringlengths 3 247 |
|---|---|---|---|---|---|---|
b5ea2192f3e995e8f622bd586880d02ef8e9f61134d84b5e68761df9964084a8 | 2026-01-13T00:00:00-05:00 | Foundational Analysis of Safety Engineering Requirements (SAFER) | arXiv:2601.06335v1 Announce Type: new Abstract: We introduce a framework for Foundational Analysis of Safety Engineering Requirements (SAFER), a model-driven methodology supported by Generative AI to improve the generation and analysis of safety requirements for complex safety-critical systems. Safety requirements are ... | https://arxiv.org/abs/2601.06335 | Academic Papers | svg |
bcdb97ab4b308420011f91ef7e26b3ed565b27d16ec581fb7f0d0121e518a8eb | 2026-01-13T00:00:00-05:00 | Future-as-Label: Scalable Supervision from Real-World Outcomes | arXiv:2601.06336v1 Announce Type: new Abstract: Many real-world prediction problems lack labels observable at prediction time, creating a temporal gap between prediction and outcome that yields supervision only after events resolve. To address this setting, we extend reinforcement learning with verifiable rewards to te... | https://arxiv.org/abs/2601.06336 | Academic Papers | svg |
af43f78421a4cb3df82b9aece6555b451346721b0f12715c36a586ed6b160a91 | 2026-01-13T00:00:00-05:00 | Circuit Mechanisms for Spatial Relation Generation in Diffusion Transformers | arXiv:2601.06338v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) have greatly advanced text-to-image generation, but models still struggle to generate the correct spatial relations between objects as specified in the text prompt. In this study, we adopt a mechanistic interpretability approach to investigat... | https://arxiv.org/abs/2601.06338 | Academic Papers | svg |
a2a5cc034344fc958610c85b72ccafdc1a5edc93d5c9f74d85dd1e4987505edd | 2026-01-13T00:00:00-05:00 | Evaluating Robustness of Large Language Models in Enterprise Applications: Benchmarks for Perturbation Consistency Across Formats and Languages | arXiv:2601.06341v1 Announce Type: new Abstract: Enterprise LLM applications require consistently high quality and reliable performance across diverse scenarios, demanding robustness to minor variations. Existing research shows that even small prompt changes can lead to substantial differences in output, but has mainly ... | https://arxiv.org/abs/2601.06341 | Academic Papers | svg |
7b177e5ea7bc557e29b5ad74b6eadf2de7e1c636859f0a9d9999f19ea7e52195 | 2026-01-13T00:00:00-05:00 | BlazeAIoT: A Modular Multi-Layer Platform for Real-Time Distributed Robotics Across Edge, Fog, and Cloud Infrastructures | arXiv:2601.06344v1 Announce Type: new Abstract: The increasing complexity of distributed robotics has driven the need for platforms that seamlessly integrate edge, fog, and cloud computing layers while meeting strict real-time constraints. This paper introduces BlazeAIoT, a modular multi-layer platform designed to unif... | https://arxiv.org/abs/2601.06344 | Academic Papers | svg |
c1619d5dd8ae5907b2e3dfbe6afec327099148d10b149c300401afc3aaa5443a | 2026-01-13T00:00:00-05:00 | What Matters When Building Universal Multilingual Named Entity Recognition Models? | arXiv:2601.06347v1 Announce Type: new Abstract: Recent progress in universal multilingual named entity recognition (NER) has been driven by advances in multilingual transformer models and task-specific architectures, loss functions, and training datasets. Despite substantial prior work, we find that many critical desig... | https://arxiv.org/abs/2601.06347 | Academic Papers | svg |
b7e871908d1737ab329c0a7a1c53620004766414fd4c9c9c27b7309b9c77ed26 | 2026-01-13T00:00:00-05:00 | Federated Learning and Class Imbalances | arXiv:2601.06348v1 Announce Type: new Abstract: Federated Learning (FL) enables collaborative model training across decentralized devices while preserving data privacy. However, real-world FL deployments face critical challenges such as data imbalances, including label noise and non-IID distributions. RHFL+, a state-of... | https://arxiv.org/abs/2601.06348 | Academic Papers | svg |
f4cf9df4aff1af2aee77faee94e28bbac2565b027a00ddd3821b917b4bdbcc7c | 2026-01-13T00:00:00-05:00 | Fixing ill-formed UTF-16 strings with SIMD instructions | arXiv:2601.06349v1 Announce Type: new Abstract: UTF-16 is a widely used Unicode encoding representing characters with one or two 16-bit code units. The format relies on surrogate pairs to encode characters beyond the Basic Multilingual Plane, requiring a high surrogate followed by a low surrogate. Ill-formed UTF-16 str... | https://arxiv.org/abs/2601.06349 | Academic Papers | svg |
7d4910d3bccea0e9ffa0e07a4d53b8bd41fdcc05520908c8602c97a3e53ef179 | 2026-01-13T00:00:00-05:00 | A Fast and Effective Method for Euclidean Anticlustering: The Assignment-Based-Anticlustering Algorithm | arXiv:2601.06351v1 Announce Type: new Abstract: The anticlustering problem is to partition a set of objects into K equal-sized anticlusters such that the sum of distances within anticlusters is maximized. The anticlustering problem is NP-hard. We focus on anticlustering in Euclidean spaces, where the input data is tabu... | https://arxiv.org/abs/2601.06351 | Academic Papers | svg |
4b9557a6245654e6c22e1654503b26a410c4872d2258b3dbd442435781631d69 | 2026-01-13T00:00:00-05:00 | CARD: Cluster-level Adaptation with Reward-guided Decoding for Personalized Text Generation | arXiv:2601.06352v1 Announce Type: new Abstract: Adapting large language models to individual users remains challenging due to the tension between fine-grained personalization and scalable deployment. We present CARD, a hierarchical framework that achieves effective personalization through progressive refinement. CARD f... | https://arxiv.org/abs/2601.06352 | Academic Papers | svg |
ae96f8fa430bad764046298b6d269dea308d0fcd81e2f864ee38fa52c12b136a | 2026-01-13T00:00:00-05:00 | Monkey Jump : MoE-Style PEFT for Efficient Multi-Task Learning | arXiv:2601.06356v1 Announce Type: new Abstract: Mixture-of-experts variants of parameter-efficient fine-tuning enable per-token specialization, but they introduce additional trainable routers and expert parameters, increasing memory usage and training cost. This undermines the core goal of parameter-efficient fine-tuni... | https://arxiv.org/abs/2601.06356 | Academic Papers | svg |
d560b4db121be80a22bc358e6a9173247de111fc9f47a68e54e22c0844fb9061 | 2026-01-13T00:00:00-05:00 | Smart Privacy Policy Assistant: An LLM-Powered System for Transparent and Actionable Privacy Notices | arXiv:2601.06357v1 Announce Type: new Abstract: Most users agree to online privacy policies without reading or understanding them, even though these documents govern how personal data is collected, shared, and monetized. Privacy policies are typically long, legally complex, and difficult for non-experts to interpret. T... | https://arxiv.org/abs/2601.06357 | Academic Papers | svg |
be317c1edc1db72d83f252949da02f5526ab0704abbf8632233adb6adacdc4f9 | 2026-01-13T00:00:00-05:00 | Average shortest-path length in word-adjacency networks: Chinese versus English | arXiv:2601.06361v1 Announce Type: new Abstract: Complex networks provide powerful tools for analyzing and understanding the intricate structures present in various systems, including natural language. Here, we analyze topology of growing word-adjacency networks constructed from Chinese and English literary works writte... | https://arxiv.org/abs/2601.06361 | Academic Papers | svg |
319df01e22dbe6d74ddcca8ebc57d4181e940d1474ca010574e4dce16f4b39ea | 2026-01-13T00:00:00-05:00 | Styles + Persona-plug = Customized LLMs | arXiv:2601.06362v1 Announce Type: new Abstract: We discover a previously overlooked challenge in personalized text generation: personalization methods are increasingly applied under explicit style instructions, yet their behavior under such constraints remains poorly understood. To balance implicit personalization and ... | https://arxiv.org/abs/2601.06362 | Academic Papers | svg |
304b55a376ccce0f3926f3c054d990674bee74cd7dfd8f75ed5fdec45aa6804c | 2026-01-13T00:00:00-05:00 | Human-in-the-Loop Interactive Report Generation for Chronic Disease Adherence | arXiv:2601.06364v1 Announce Type: new Abstract: Chronic disease management requires regular adherence feedback to prevent avoidable hospitalizations, yet clinicians lack time to produce personalized patient communications. Manual authoring preserves clinical accuracy but does not scale; AI generation scales but can und... | https://arxiv.org/abs/2601.06364 | Academic Papers | svg |
468b3d7fbe95b65715018bc9f3315146edd80352ae7a6f9d1524dd335ca6f3b6 | 2026-01-13T00:00:00-05:00 | SafeGPT: Preventing Data Leakage and Unethical Outputs in Enterprise LLM Use | arXiv:2601.06366v1 Announce Type: new Abstract: Large Language Models (LLMs) are transforming enterprise workflows but introduce security and ethics challenges when employees inadvertently share confidential data or generate policy-violating content. This paper proposes SafeGPT, a two-sided guardrail system preventing ... | https://arxiv.org/abs/2601.06366 | Academic Papers | svg |
c3594aef4a7909cded3b450d4678b917ff6e7f40afac97c68c685c8fe2cf0438 | 2026-01-13T00:00:00-05:00 | ReAct: Reflection Attack Mitigation For Asymmetric Routing | arXiv:2601.06367v1 Announce Type: new Abstract: Amplification Reflection Distributed Denial-of-Service (AR-DDoS) attacks remain a formidable threat, exploiting stateless protocols to flood victims with illegitimate traffic. Recent advances have enabled data-plane defenses against such attacks, but existing solutions ty... | https://arxiv.org/abs/2601.06367 | Academic Papers | svg |
841a5472cf616bc64bea38c26b6b1e6eea46bfba6edd5e5c3cbc5b410fe7d37c | 2026-01-13T00:00:00-05:00 | From Easy to Hard++: Promoting Differentially Private Image Synthesis Through Spatial-Frequency Curriculum | arXiv:2601.06368v1 Announce Type: new Abstract: To improve the quality of Differentially private (DP) synthetic images, most studies have focused on improving the core optimization techniques (e.g., DP-SGD). Recently, we have witnessed a paradigm shift that takes these techniques off the shelf and studies how to use th... | https://arxiv.org/abs/2601.06368 | Academic Papers | svg |
eddd075b098a6e20990164063ef726e83e6aa67485af01290f0e5bc69483d5d7 | 2026-01-13T00:00:00-05:00 | Talking to Extraordinary Objects: Folktales Offer Analogies for Interacting with Technology | arXiv:2601.06372v1 Announce Type: new Abstract: Speech and language are valuable for interacting with technology. It would be ideal to be able to decouple their use from anthropomorphization, which has recently met an important moment of reckoning. In the world of folktales, language is everywhere and talking to extrao... | https://arxiv.org/abs/2601.06372 | Academic Papers | svg |
ee337ddcaaf8c73c99af119e417d6f687e31bce9e57fb7936269954f38c48b9f | 2026-01-13T00:00:00-05:00 | DemMA: Dementia Multi-Turn Dialogue Agent with Expert-Guided Reasoning and Action Simulation | arXiv:2601.06373v1 Announce Type: new Abstract: Simulating dementia patients with large language models (LLMs) is challenging due to the need to jointly model cognitive impairment, emotional dynamics, and nonverbal behaviors over long conversations. We present DemMA, an expert-guided dementia dialogue agent for high-fi... | https://arxiv.org/abs/2601.06373 | Academic Papers | svg |
343c642152c2d8ee8756b7bdd178f6ec4b286c882dd712447184e10413e058d3 | 2026-01-13T00:00:00-05:00 | HiMem: Hierarchical Long-Term Memory for LLM Long-Horizon Agents | arXiv:2601.06377v1 Announce Type: new Abstract: Although long-term memory systems have made substantial progress in recent years, they still exhibit clear limitations in adaptability, scalability, and self-evolution under continuous interaction settings. Inspired by cognitive theories, we propose HiMem, a hierarchical ... | https://arxiv.org/abs/2601.06377 | Academic Papers | svg |
c1b495de4843c42aa1c527e38f5b44defa5d2cf0a3611f5a501a127912bba39d | 2026-01-13T00:00:00-05:00 | RigMo: Unifying Rig and Motion Learning for Generative Animation | arXiv:2601.06378v1 Announce Type: new Abstract: Despite significant progress in 4D generation, rig and motion, the core structural and dynamic components of animation are typically modeled as separate problems. Existing pipelines rely on ground-truth skeletons and skinning weights for motion generation and treat auto-r... | https://arxiv.org/abs/2601.06378 | Academic Papers | svg |
05ac02058ca182cfefc0fb99e61b82efefc66e060a882c0f74067a5073e95715 | 2026-01-13T00:00:00-05:00 | Hierarchical Pooling and Explainability in Graph Neural Networks for Tumor and Tissue-of-Origin Classification Using RNA-seq Data | arXiv:2601.06381v1 Announce Type: new Abstract: This study explores the use of graph neural networks (GNNs) with hierarchical pooling and multiple convolution layers for cancer classification based on RNA-seq data. We combine gene expression data from The Cancer Genome Atlas (TCGA) with a precomputed STRING protein-pro... | https://arxiv.org/abs/2601.06381 | Academic Papers | svg |
9870dd85669539ddccf98d4f677bcf531793f1f8d7473ba94ab22b59b461dcdf | 2026-01-13T00:00:00-05:00 | Dynamic Incentivized Cooperation under Changing Rewards | arXiv:2601.06382v1 Announce Type: new Abstract: Peer incentivization (PI) is a popular multi-agent reinforcement learning approach where all agents can reward or penalize each other to achieve cooperation in social dilemmas. Despite their potential for scalable cooperation, current PI methods heavily depend on fixed in... | https://arxiv.org/abs/2601.06382 | Academic Papers | svg |
ae79b5be72e4065068acd68c2045744d0bb8cb747d8d71f9179ba015a99c1816 | 2026-01-13T00:00:00-05:00 | Noise Reduction for Pufferfish Privacy: A Practical Noise Calibration Method | arXiv:2601.06385v1 Announce Type: new Abstract: This paper introduces a relaxed noise calibration method to enhance data utility while attaining pufferfish privacy. This work builds on the existing $1$-Wasserstein (Kantorovich) mechanism by alleviating the existing overly strict condition that leads to excessive noise,... | https://arxiv.org/abs/2601.06385 | Academic Papers | svg |
421f58e99b57e1f5231feecd51976f8c085f3bd5c1d4e72c416a6e70cdeb6509 | 2026-01-13T00:00:00-05:00 | An Efficient Evolutionary Algorithm for Few-for-Many Optimization | arXiv:2601.06387v1 Announce Type: new Abstract: Few-for-many (F4M) optimization, recently introduced as a novel paradigm in multi-objective optimization, aims to find a small set of solutions that effectively handle a large number of conflicting objectives. Unlike traditional many-objective optimization methods, which ... | https://arxiv.org/abs/2601.06387 | Academic Papers | svg |
ce4af1f23291c4070f2ecbbfc1dfcd1423cfae4bba8e8941cba2432a2df616ce | 2026-01-13T00:00:00-05:00 | Supervised and Unsupervised Neural Network Solver for First Order Hyperbolic Nonlinear PDEs | arXiv:2601.06388v1 Announce Type: new Abstract: We present a neural network-based method for learning scalar hyperbolic conservation laws. Our method replaces the traditional numerical flux in finite volume schemes with a trainable neural network while preserving the conservative structure of the scheme. The model can ... | https://arxiv.org/abs/2601.06388 | Academic Papers | svg |
4b1064053ab2e4b6bad6dca073761d6283c3d860a2954594c9de1ffedf37faeb | 2026-01-13T00:00:00-05:00 | Towards Building efficient Routed systems for Retrieval | arXiv:2601.06389v1 Announce Type: new Abstract: Late-interaction retrieval models like ColBERT achieve superior accuracy by enabling token-level interactions, but their computational cost hinders scalability and integration with Approximate Nearest Neighbor Search (ANNS). We introduce FastLane, a novel retrieval framew... | https://arxiv.org/abs/2601.06389 | Academic Papers | svg |
551b23115d571528c962ee417c1729895df69ae7d99ccc9a866a7c35f0594877 | 2026-01-13T00:00:00-05:00 | Object-WIPER : Training-Free Object and Associated Effect Removal in Videos | arXiv:2601.06391v1 Announce Type: new Abstract: In this paper, we introduce Object-WIPER, a training-free framework for removing dynamic objects and their associated visual effects from videos, and inpainting them with semantically consistent and temporally coherent content. Our approach leverages a pre-trained text-to... | https://arxiv.org/abs/2601.06391 | Academic Papers | svg |
6ae0de874262cd8f59e08a3653fe4b7b55e7a53d339c7e11c36ec22da2a0f5c1 | 2026-01-13T00:00:00-05:00 | Context Matters: Peer-Aware Student Behavioral Engagement Measurement via VLM Action Parsing and LLM Sequence Classification | arXiv:2601.06394v1 Announce Type: new Abstract: Understanding student behavior in the classroom is essential to improve both pedagogical quality and student engagement. Existing methods for predicting student engagement typically require substantial annotated data to model the diversity of student behaviors, yet privac... | https://arxiv.org/abs/2601.06394 | Academic Papers | svg |
d78e71577f7632879179a561f9bf756f02a16381e46daba3c612fdd2cfd890c0 | 2026-01-13T00:00:00-05:00 | AfriqueLLM: How Data Mixing and Model Architecture Impact Continued Pre-training for African Languages | arXiv:2601.06395v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly multilingual, yet open models continue to underperform relative to proprietary systems, with the gap most pronounced for African languages. Continued pre-training (CPT) offers a practical route to language adaptation, but impr... | https://arxiv.org/abs/2601.06395 | Academic Papers | svg |
e611e22ac1ef65b666a85f5ebd12f23f5a81c20107f6c35aef0542714c2e3700 | 2026-01-13T00:00:00-05:00 | MITRA: A Large-Scale Parallel Corpus and Multilingual Pretrained Language Model for Machine Translation and Semantic Retrieval for P\=ali, Sanskrit, Buddhist Chinese, and Tibetan | arXiv:2601.06400v1 Announce Type: new Abstract: Ancient Buddhist literature features frequent, yet often unannotated, textual parallels spread across diverse languages: Sanskrit, P\=ali, Buddhist Chinese, Tibetan, and more. The scale of this material makes manual examination prohibitive. We present the MITRA framework,... | https://arxiv.org/abs/2601.06400 | Academic Papers | svg |
411f09e06f62490aae6a8dbc27c498a9f609cf427d4468ca358ac67167f68a13 | 2026-01-13T00:00:00-05:00 | BizFinBench.v2: A Unified Dual-Mode Bilingual Benchmark for Expert-Level Financial Capability Alignment | arXiv:2601.06401v1 Announce Type: new Abstract: Large language models have undergone rapid evolution, emerging as a pivotal technology for intelligence in financial operations. However, existing benchmarks are often constrained by pitfalls such as reliance on simulated or general-purpose samples and a focus on singular... | https://arxiv.org/abs/2601.06401 | Academic Papers | svg |
8128f6b1391da5f830e88825b9c81e68ed75b504293d18cdd899ed697829cf62 | 2026-01-13T00:00:00-05:00 | Spatiotemporal Change-Points in Development Discourse: Insights from Social Media in Low-Resource Contexts | arXiv:2601.06402v1 Announce Type: new Abstract: This study investigates the spatiotemporal evolution of development discourse in low-resource settings. Analyzing more than two years of geotagged X data from Zambia, we introduce a mixed-methods pipeline utilizing topic modeling, change-point detection, and qualitative c... | https://arxiv.org/abs/2601.06402 | Academic Papers | svg |
c4dc783dc7b1a91af84d62f0ced897865758165f152dc4125097401399103076 | 2026-01-13T00:00:00-05:00 | Steer Model beyond Assistant: Controlling System Prompt Strength via Contrastive Decoding | arXiv:2601.06403v1 Announce Type: new Abstract: Large language models excel at complex instructions yet struggle to deviate from their helpful assistant persona, as post-training instills strong priors that resist conflicting instructions. We introduce system prompt strength, a training-free method that treats prompt a... | https://arxiv.org/abs/2601.06403 | Academic Papers | svg |
4dea30f8620a2a8992d9cf78bae96542638ec14413c5251d7c387870f8b3718c | 2026-01-13T00:00:00-05:00 | One-Shot Hierarchical Federated Clustering | arXiv:2601.06404v1 Announce Type: new Abstract: Driven by the growth of Web-scale decentralized services, Federated Clustering (FC) aims to extract knowledge from heterogeneous clients in an unsupervised manner while preserving the clients' privacy, which has emerged as a significant challenge due to the lack of label ... | https://arxiv.org/abs/2601.06404 | Academic Papers | svg |
3575ce7b659cc42d47f6b806d04534007b5b7136061cb624b2b773bcd86e6cc2 | 2026-01-13T00:00:00-05:00 | Representing Sounds as Neural Amplitude Fields: A Benchmark of Coordinate-MLPs and A Fourier Kolmogorov-Arnold Framework | arXiv:2601.06406v1 Announce Type: new Abstract: Although Coordinate-MLP-based implicit neural representations have excelled in representing radiance fields, 3D shapes, and images, their application to audio signals remains underexplored. To fill this gap, we investigate existing implicit neural representations, from wh... | https://arxiv.org/abs/2601.06406 | Academic Papers | svg |
99544ef20b2efec93aca7dbcc600b5ee65e4f3d82f391bbea114928484c8e2f0 | 2026-01-13T00:00:00-05:00 | Value of Information: A Framework for Human-Agent Communication | arXiv:2601.06407v1 Announce Type: new Abstract: Large Language Model (LLM) agents deployed for real-world tasks face a fundamental dilemma: user requests are underspecified, yet agents must decide whether to act on incomplete information or interrupt users for clarification. Existing approaches either rely on brittle c... | https://arxiv.org/abs/2601.06407 | Academic Papers | svg |
d2cb5a559f371768b2b463e5647128bc36f6f29f3a254630adc2a06a7cfec7e2 | 2026-01-13T00:00:00-05:00 | An NPDo Approach for Principal Joint Block Diagonalization | arXiv:2601.06410v1 Announce Type: new Abstract: Matrix joint block-diagonalization (JBD) frequently arises from diverse applications such as independent component analysis, blind source separation, and common principal component analysis (CPCA), among others. Particularly, CPCA aims at joint diagonalization, i.e., each... | https://arxiv.org/abs/2601.06410 | Academic Papers | svg |
7317e29c1f76dddee1dd601fab5bd3b3db9dc633cdb99837a5953ac173728530 | 2026-01-13T00:00:00-05:00 | Structured Episodic Event Memory | arXiv:2601.06411v1 Announce Type: new Abstract: Current approaches to memory in Large Language Models (LLMs) predominantly rely on static Retrieval-Augmented Generation (RAG), which often results in scattered retrieval and fails to capture the structural dependencies required for complex reasoning. For autonomous agent... | https://arxiv.org/abs/2601.06411 | Academic Papers | svg |
c32e0675a8486b769caccee0d8ffc9b98a0795176dc35046d9200865ec1071af | 2026-01-13T00:00:00-05:00 | Brokerage in the Black Box: Swing States, Strategic Ambiguity, and the Global Politics of AI Governance | arXiv:2601.06412v1 Announce Type: new Abstract: The U.S. - China rivalry has placed frontier dual-use technologies, particularly Artificial Intelligence (AI), at the center of global power dynamics, as techno-nationalism, supply chain securitization, and competing standards deepen bifurcation within a weaponized interd... | https://arxiv.org/abs/2601.06412 | Academic Papers | svg |
aaf0ddbbb368478d61293c3008403939a7cb6054550c1a4559962e2835e6f9ed | 2026-01-13T00:00:00-05:00 | GlobalPaint: Spatiotemporal Coherent Video Outpainting with Global Feature Guidance | arXiv:2601.06413v1 Announce Type: new Abstract: Video outpainting extends a video beyond its original boundaries by synthesizing missing border content. Compared with image outpainting, it requires not only per-frame spatial plausibility but also long-range temporal coherence, especially when outpainted content becomes... | https://arxiv.org/abs/2601.06413 | Academic Papers | svg |
ece5c320df92cf0d32f828baf874f017cf2fadc0c97660119026b6b18d923015 | 2026-01-13T00:00:00-05:00 | Semantic Enrichment of CAD-Based Industrial Environments via Scene Graphs for Simulation and Reasoning | arXiv:2601.06415v1 Announce Type: new Abstract: Utilizing functional elements in an industrial environment, such as displays and interactive valves, provide effective possibilities for robot training. When preparing simulations for robots or applications that involve high-level scene understanding, the simulation envir... | https://arxiv.org/abs/2601.06415 | Academic Papers | svg |
10f6d49fc714603c198fceab809f81869b01dee26ad4f3b5058cc67875455658 | 2026-01-13T00:00:00-05:00 | Lightweight Yet Secure: Secure Scripting Language Generation via Lightweight LLMs | arXiv:2601.06419v1 Announce Type: new Abstract: The security of scripting languages such as PowerShell is critical given their powerful automation and administration capabilities, often exercised with elevated privileges. Today, securing these languages still demands substantial human effort to craft and enforce rules,... | https://arxiv.org/abs/2601.06419 | Academic Papers | svg |
839be3b0692074b62b8aa283ae746962be1b9f24846eeeecc7ab3424723ca4f9 | 2026-01-13T00:00:00-05:00 | Does Inference Scaling Improve Reasoning Faithfulness? A Multi-Model Analysis of Self-Consistency Tradeoffs | arXiv:2601.06423v1 Announce Type: new Abstract: Self-consistency has emerged as a popular technique for improving large language model accuracy on reasoning tasks. The approach is straightforward: generate multiple reasoning paths and select the most common answer through majority voting. While this reliably boosts acc... | https://arxiv.org/abs/2601.06423 | Academic Papers | svg |
3bf79a5cf45fba040e40178d6d52c0a8b8d3d729dd35d565347870cd45701f48 | 2026-01-13T00:00:00-05:00 | Can a Unimodal Language Agent Provide Preferences to Tune a Multimodal Vision-Language Model? | arXiv:2601.06424v1 Announce Type: new Abstract: To explore a more scalable path for adding multimodal capabilities to existing LLMs, this paper addresses a fundamental question: Can a unimodal LLM, relying solely on text, reason about its own informational needs and provide effective feedback to optimize a multimodal m... | https://arxiv.org/abs/2601.06424 | Academic Papers | svg |
f48afab9c2754a67fd5b01bcd0c47a7e19bbc97fd968fced444dbda9e2c8c495 | 2026-01-13T00:00:00-05:00 | HiDVFS: A Hierarchical Multi-Agent DVFS Scheduler for OpenMP DAG Workloads | arXiv:2601.06425v1 Announce Type: new Abstract: With advancements in multicore embedded systems, leakage power, exponentially tied to chip temperature, has surpassed dynamic power consumption. Energy-aware solutions use dynamic voltage and frequency scaling (DVFS) to mitigate overheating in performance-intensive scenar... | https://arxiv.org/abs/2601.06425 | Academic Papers | svg |
18b9919b9c5e2b1d9fd2328a558610a6d24d08997140267e8b1b0a14e2cff504 | 2026-01-13T00:00:00-05:00 | NC-Bench: An LLM Benchmark for Evaluating Conversational Competence | arXiv:2601.06426v1 Announce Type: new Abstract: The Natural Conversation Benchmark (NC-Bench) introduce a new approach to evaluating the general conversational competence of large language models (LLMs). Unlike prior benchmarks that focus on the content of model behavior, NC-Bench focuses on the form and structure of n... | https://arxiv.org/abs/2601.06426 | Academic Papers | svg |
28b1c1f55990c3daa06610a3bf360bd19bafc9f818e849c19a997e35c531cac7 | 2026-01-13T00:00:00-05:00 | Teach Diffusion Language Models to Learn from Their Own Mistakes | arXiv:2601.06428v1 Announce Type: new Abstract: Masked Diffusion Language Models (DLMs) achieve significant speed by generating multiple tokens in parallel. However, this parallel sampling approach, especially when using fewer inference steps, will introduce strong dependency errors and cause quality to deteriorate rap... | https://arxiv.org/abs/2601.06428 | Academic Papers | svg |
822b862a20e3ac01d3958f91a799ee1d39af804d255c333fc3b3237759a4e535 | 2026-01-13T00:00:00-05:00 | A Unified Shape-Aware Foundation Model for Time Series Classification | arXiv:2601.06429v1 Announce Type: new Abstract: Foundation models pre-trained on large-scale source datasets are reshaping the traditional training paradigm for time series classification. However, existing time series foundation models primarily focus on forecasting tasks and often overlook classification-specific cha... | https://arxiv.org/abs/2601.06429 | Academic Papers | svg |
9950130b46d34db8e04affed6653dcd426afdcc8930d02507abf1b3b0579a12b | 2026-01-13T00:00:00-05:00 | Robust and Secure Blockage-Aware Pinching Antenna-assisted Wireless Communication | arXiv:2601.06430v1 Announce Type: new Abstract: In this work, we investigate a blockage-aware pinching antenna (PA) system designed for secure and robust wireless communication. The considered system comprises a base station equipped with multiple waveguides, each hosting multiple PAs, and serves multiple single-antenn... | https://arxiv.org/abs/2601.06430 | Academic Papers | svg |
e25891169c5e17d56cfdd540cc2a9918a914c4cf64502a3fdca95e2e11e28c43 | 2026-01-13T00:00:00-05:00 | LSRIF: Logic-Structured Reinforcement Learning for Instruction Following | arXiv:2601.06431v1 Announce Type: new Abstract: Instruction-following is critical for large language models, but real-world instructions often contain logical structures such as sequential dependencies and conditional branching. Existing methods typically construct datasets with parallel constraints and optimize averag... | https://arxiv.org/abs/2601.06431 | Academic Papers | svg |
1371fc2eee11258dca2ca2464683d5747ac82b3847c602e786534841bf8393e5 | 2026-01-13T00:00:00-05:00 | Certified Unlearning in Decentralized Federated Learning | arXiv:2601.06436v1 Announce Type: new Abstract: Driven by the right to be forgotten (RTBF), machine unlearning has become an essential requirement for privacy-preserving machine learning. However, its realization in decentralized federated learning (DFL) remains largely unexplored. In DFL, clients exchange local update... | https://arxiv.org/abs/2601.06436 | Academic Papers | svg |
93cd992a79898278ff20578ecb4f8375ae62f7f4476afd1132a389674512ee48 | 2026-01-13T00:00:00-05:00 | Time Travel Engine: A Shared Latent Chronological Manifold Enables Historical Navigation in Large Language Models | arXiv:2601.06437v1 Announce Type: new Abstract: Time functions as a fundamental dimension of human cognition, yet the mechanisms by which Large Language Models (LLMs) encode chronological progression remain opaque. We demonstrate that temporal information in their latent space is organized not as discrete clusters but ... | https://arxiv.org/abs/2601.06437 | Academic Papers | svg |
3f0a8e7bbc35148bb32a2394e869bbed6f9ace713db284b947e380832f7dfa3e | 2026-01-13T00:00:00-05:00 | Deep Reinforcement Learning based Control Design for Aircraft Recovery from Loss-of-Control Scenario | arXiv:2601.06439v1 Announce Type: new Abstract: Loss-of-control (LOC) remains a leading cause of fixed-wing aircraft accidents, especially in post-stall and flat-spin regimes where conventional gain-scheduled or logic-based recovery laws may fail. This study formulates spin-recovery as a continuous-state, continuous-ac... | https://arxiv.org/abs/2601.06439 | Academic Papers | svg |
d2f5d36ab49a0b806372ee62040577f098261f2bf7672403550a6c999a37c800 | 2026-01-13T00:00:00-05:00 | FlexAct: Why Learn when you can Pick? | arXiv:2601.06441v1 Announce Type: new Abstract: Learning activation functions has emerged as a promising direction in deep learning, allowing networks to adapt activation mechanisms to task-specific demands. In this work, we introduce a novel framework that employs the Gumbel-Softmax trick to enable discrete yet differ... | https://arxiv.org/abs/2601.06441 | Academic Papers | svg |
551d06379d97182a188a81315e3679fef3a20a013e46e8494fbbe932eb268868 | 2026-01-13T00:00:00-05:00 | WHU-PCPR: A cross-platform heterogeneous point cloud dataset for place recognition in complex urban scenes | arXiv:2601.06442v1 Announce Type: new Abstract: Point Cloud-based Place Recognition (PCPR) demonstrates considerable potential in applications such as autonomous driving, robot localization and navigation, and map update. In practical applications, point clouds used for place recognition are often acquired from differe... | https://arxiv.org/abs/2601.06442 | Academic Papers | svg |
4234388bc03c4cc8b5b97987581419fe6e2acf80174c37dba57a6d63f43f8bc9 | 2026-01-13T00:00:00-05:00 | How to Build Robust, Scalable Models for GSV-Based Indicators in Neighborhood Research | arXiv:2601.06443v1 Announce Type: new Abstract: A substantial body of health research demonstrates a strong link between neighborhood environments and health outcomes. Recently, there has been increasing interest in leveraging advances in computer vision to enable large-scale, systematic characterization of neighborhoo... | https://arxiv.org/abs/2601.06443 | Academic Papers | svg |
b0c717c16256a0df9a91a4648bdaf51b1acf1b4bca10545145231291ba703190 | 2026-01-13T00:00:00-05:00 | Physics-Informed Tree Search for High-Dimensional Computational Design | arXiv:2601.06444v1 Announce Type: new Abstract: High-dimensional design spaces underpin a wide range of physics-based modeling and computational design tasks in science and engineering. These problems are commonly formulated as constrained black-box searches over rugged objective landscapes, where function evaluations ... | https://arxiv.org/abs/2601.06444 | Academic Papers | svg |
7481112176ae51e7a74473d36d876ac4f638ddd3e02ae3d94d211e080cc81af6 | 2026-01-13T00:00:00-05:00 | LitVISTA: A Benchmark for Narrative Orchestration in Literary Text | arXiv:2601.06445v1 Announce Type: new Abstract: Computational narrative analysis aims to capture rhythm, tension, and emotional dynamics in literary texts. Existing large language models can generate long stories but overly focus on causal coherence, neglecting the complex story arcs and orchestration inherent in human... | https://arxiv.org/abs/2601.06445 | Academic Papers | svg |
e90cacb3d3d2cd8608bf1f88c650259faac1148f3a7f6c40021786092e0bdcc4 | 2026-01-13T00:00:00-05:00 | Error correction methods based on two-faced processes | arXiv:2601.06447v1 Announce Type: new Abstract: A new approach to the problem of error correction in communication channels is proposed, in which the input sequence is transformed in such a way that the interdependence of symbols is significantly increased. Then, after the sequence is transmitted over the channel, this... | https://arxiv.org/abs/2601.06447 | Academic Papers | svg |
df4526c3d69fa427c185c345b0319f61df7426a5b38de481992cf01f91285761 | 2026-01-13T00:00:00-05:00 | Function-Correcting Partition codes | arXiv:2601.06450v1 Announce Type: new Abstract: We introduce function-correcting partition codes (FCPCs) that are a natural generalization of function-correcting codes (FCCs). A $t$-error function-correcting partition code is an $(\mathcal{P},t)$-encoding defined directly on a partition $\mathcal{P}$ of $\mathbb{F}_q^k... | https://arxiv.org/abs/2601.06450 | Academic Papers | svg |
dfe76016a0b8bd090e302c9f1fd3a86aad890d2bc69c4258cafab08ef882f069 | 2026-01-13T00:00:00-05:00 | CulinaryCut-VLAP: A Vision-Language-Action-Physics Framework for Food Cutting via a Force-Aware Material Point Method | arXiv:2601.06451v1 Announce Type: new Abstract: Food cutting is a highly practical yet underexplored application at the intersection of vision and robotic manipulation. The task remains challenging because interactions between the knife and deformable materials are highly nonlinear and often entail large deformations, ... | https://arxiv.org/abs/2601.06451 | Academic Papers | svg |
bdf13557787cfe97c5a9586d353008ea45feb53332106c6ba884cd5d50482c5f | 2026-01-13T00:00:00-05:00 | ConSensus: Multi-Agent Collaboration for Multimodal Sensing | arXiv:2601.06453v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly grounded in sensor data to perceive and reason about human physiology and the physical world. However, accurately interpreting heterogeneous multimodal sensor data remains a fundamental challenge. We show that a single monolit... | https://arxiv.org/abs/2601.06453 | Academic Papers | svg |
fd16ede28d85582b715739e644e5865fa26a54f4917e280de95abe18bb385796 | 2026-01-13T00:00:00-05:00 | Architecting AgentOps Needs CHANGE | arXiv:2601.06456v1 Announce Type: new Abstract: The emergence of Agentic AI systems has outpaced the architectural thinking required to operate them effectively. These agents differ fundamentally from traditional software: their behavior is not fixed at deployment but continuously shaped by experience, feedback, and co... | https://arxiv.org/abs/2601.06456 | Academic Papers | svg |
6d9f1e66ed75f26e033f9274b7354092f1e4b3d19f931097f1792cfe3f47a327 | 2026-01-13T00:00:00-05:00 | PixRec: Leveraging Visual Context for Next-Item Prediction in Sequential Recommendation | arXiv:2601.06458v1 Announce Type: new Abstract: Large Language Models (LLMs) have recently shown strong potential for usage in sequential recommendation tasks through text-only models, which combine advanced prompt design, contrastive alignment, and fine-tuning on downstream domain-specific data. While effective, these... | https://arxiv.org/abs/2601.06458 | Academic Papers | svg |
f4957f4b4b4e34b427fe78335fa983ecae7838e77bf0b8d5b2dc7768301d322c | 2026-01-13T00:00:00-05:00 | Tone Matters: The Impact of Linguistic Tone on Hallucination in VLMs | arXiv:2601.06460v1 Announce Type: new Abstract: Vision-Language Models (VLMs) are increasingly used in safety-critical applications that require reliable visual grounding. However, these models often hallucinate details that are not present in the image to satisfy user prompts. While recent datasets and benchmarks have... | https://arxiv.org/abs/2601.06460 | Academic Papers | svg |
74963ba95d0131e930d376fa85c7077315cfc4428b6648d0e92c74f1ba58bb64 | 2026-01-13T00:00:00-05:00 | VIPER Strike: Defeating Visual Reasoning CAPTCHAs via Structured Vision-Language Inference | arXiv:2601.06461v1 Announce Type: new Abstract: Visual Reasoning CAPTCHAs (VRCs) combine visual scenes with natural-language queries that demand compositional inference over objects, attributes, and spatial relations. They are increasingly deployed as a primary defense against automated bots. Existing solvers fall into... | https://arxiv.org/abs/2601.06461 | Academic Papers | svg |
ae3849b62dcd7ea6837d62a0aef891c54639a92a0487205733f7f8a027bd4f60 | 2026-01-13T00:00:00-05:00 | Gecko: An Efficient Neural Architecture Inherently Processing Sequences with Arbitrary Lengths | arXiv:2601.06463v1 Announce Type: new Abstract: Designing a unified neural network to efficiently and inherently process sequential data with arbitrary lengths is a central and challenging problem in sequence modeling. The design choices in Transformer, including quadratic complexity and weak length extrapolation, have... | https://arxiv.org/abs/2601.06463 | Academic Papers | svg |
7f854b94b15e9a352be77b20d5799959e7b3f9cd88f8f6343b68f3e831ec30d4 | 2026-01-13T00:00:00-05:00 | On the Adversarial Robustness of 3D Large Vision-Language Models | arXiv:2601.06464v1 Announce Type: new Abstract: 3D Vision-Language Models (VLMs), such as PointLLM and GPT4Point, have shown strong reasoning and generalization abilities in 3D understanding tasks. However, their adversarial robustness remains largely unexplored. Prior work in 2D VLMs has shown that the integration of ... | https://arxiv.org/abs/2601.06464 | Academic Papers | svg |
d9d7c1db13d0008a5f6554baa84c054c1771fae91f6dda131380cac280e1bc90 | 2026-01-13T00:00:00-05:00 | SecureDyn-FL: A Robust Privacy-Preserving Federated Learning Framework for Intrusion Detection in IoT Networks | arXiv:2601.06466v1 Announce Type: new Abstract: The rapid proliferation of Internet of Things (IoT) devices across domains such as smart homes, industrial control systems, and healthcare networks has significantly expanded the attack surface for cyber threats, including botnet-driven distributed denial-of-service (DDoS... | https://arxiv.org/abs/2601.06466 | Academic Papers | svg |
456653ecc907c7257a1393eff25bc3a7a75b66660ef330de34eac1f5ec08b0bc | 2026-01-13T00:00:00-05:00 | Style-constrained inverse design of microstructures with tailored mechanical properties using unconditional diffusion models | arXiv:2601.06469v1 Announce Type: new Abstract: Deep generative models, particularly denoising diffusion models, have achieved remarkable success in high-fidelity generation of architected microstructures with desired properties and styles. Nevertheless, these recent methods typically rely on conditional training mecha... | https://arxiv.org/abs/2601.06469 | Academic Papers | svg |
e91a0d54ab7735062e8d2192118ec1ce62a27564b5d1643db064b431656b21ff | 2026-01-13T00:00:00-05:00 | PRISP: Privacy-Safe Few-Shot Personalization via Lightweight Adaptation | arXiv:2601.06471v1 Announce Type: new Abstract: Large language model (LLM) personalization aims to adapt general-purpose models to individual users. Most existing methods, however, are developed under data-rich and resource-abundant settings, often incurring privacy risks. In contrast, realistic personalization typical... | https://arxiv.org/abs/2601.06471 | Academic Papers | svg |
67aa1ab544eac22dfbc6153f0661ae9d8dbc13a5605dc8bd7b158ba53b3489ba | 2026-01-13T00:00:00-05:00 | StablePDENet: Enhancing Stability of Operator Learning for Solving Differential Equations | arXiv:2601.06472v1 Announce Type: new Abstract: Learning solution operators for differential equations with neural networks has shown great potential in scientific computing, but ensuring their stability under input perturbations remains a critical challenge. This paper presents a robust self-supervised neural operator... | https://arxiv.org/abs/2601.06472 | Academic Papers | svg |
6f2db3a578685fa47a6a40120eaeb7b22ffe6c4c811ad543a9bc55dc93b2437d | 2026-01-13T00:00:00-05:00 | Hybrid LSTM-UKF Framework: Ankle Angle and Ground Reaction Force Estimation | arXiv:2601.06473v1 Announce Type: new Abstract: Accurate prediction of joint kinematics and kinetics is essential for advancing gait analysis and developing intelligent assistive systems such as prosthetics and exoskeletons. This study presents a hybrid LSTM-UKF framework for estimating ankle angle and ground reaction ... | https://arxiv.org/abs/2601.06473 | Academic Papers | svg |
4ffd32b8e48fc983dd8adf5c353184f3feb336aa2401738273a444d860fead80 | 2026-01-13T00:00:00-05:00 | SparseOccVLA: Bridging Occupancy and Vision-Language Models via Sparse Queries for Unified 4D Scene Understanding and Planning | arXiv:2601.06474v1 Announce Type: new Abstract: In autonomous driving, Vision Language Models (VLMs) excel at high-level reasoning , whereas semantic occupancy provides fine-grained details. Despite significant progress in individual fields, there is still no method that can effectively integrate both paradigms. Conven... | https://arxiv.org/abs/2601.06474 | Academic Papers | svg |
1116d4daf0fbf73ebe601c8bd2cc72557ca3f568dafc027c3d6adddeec5e74d5 | 2026-01-13T00:00:00-05:00 | VVTRec: Radio Interferometric Reconstruction through Visual and Textual Modality Enrichment | arXiv:2601.06475v1 Announce Type: new Abstract: Radio astronomy is an indispensable discipline for observing distant celestial objects. Measurements of wave signals from radio telescopes, called visibility, need to be transformed into images for astronomical observations. These dirty images blend information from real ... | https://arxiv.org/abs/2601.06475 | Academic Papers | svg |
d06fca3af8cab92fa12b18fd0d36469692ae9bf38ba5b3952cb2d01fbeb51fb9 | 2026-01-13T00:00:00-05:00 | IndRegBias: A Dataset for Studying Indian Regional Biases in English and Code-Mixed Social Media Comments | arXiv:2601.06477v1 Announce Type: new Abstract: Warning: This paper consists of examples representing regional biases in Indian regions that might be offensive towards a particular region. While social biases corresponding to gender, race, socio-economic conditions, etc., have been extensively studied in the major appl... | https://arxiv.org/abs/2601.06477 | Academic Papers | svg |
0358f3c8a3bbaf446302d7e3e739b2ad566099ddbeb69305cf115eb8325e025d | 2026-01-13T00:00:00-05:00 | Deriving Decoder-Free Sparse Autoencoders from First Principles | arXiv:2601.06478v1 Announce Type: new Abstract: Gradient descent on log-sum-exp (LSE) objectives performs implicit expectation--maximization (EM): the gradient with respect to each component output equals its responsibility. The same theory predicts collapse without volume control analogous to the log-determinant in Ga... | https://arxiv.org/abs/2601.06478 | Academic Papers | svg |
e6a5c145f57ca025c0712c9e9800abbfefe5011576844ba333c412a9d68084b5 | 2026-01-13T00:00:00-05:00 | SRFlow: A Dataset and Regularization Model for High-Resolution Facial Optical Flow via Splatting Rasterization | arXiv:2601.06479v1 Announce Type: new Abstract: Facial optical flow supports a wide range of tasks in facial motion analysis. However, the lack of high-resolution facial optical flow datasets has hindered progress in this area. In this paper, we introduce Splatting Rasterization Flow (SRFlow), a high-resolution facial ... | https://arxiv.org/abs/2601.06479 | Academic Papers | svg |
52e3d728575461552e5e2d20d12197e679fe734917be6329cccdc1da4f08dc70 | 2026-01-13T00:00:00-05:00 | Learning Domain Agnostic Latent Embeddings of 3D Faces for Zero-shot Animal Expression Transfer | arXiv:2601.06484v1 Announce Type: new Abstract: We present a zero-shot framework for transferring human facial expressions to 3D animal face meshes. Our method combines intrinsic geometric descriptors (HKS/WKS) with a mesh-agnostic latent embedding that disentangles facial identity and expression. The ID latent space c... | https://arxiv.org/abs/2601.06484 | Academic Papers | svg |
7e3f5e41593a93ac58c26cd963cf712ce6d7c6ecd6f5fd14aa3d64f35853e8b4 | 2026-01-13T00:00:00-05:00 | Coupling Smoothed Particle Hydrodynamics with Multi-Agent Deep Reinforcement Learning for Cooperative Control of Point Absorbers | arXiv:2601.06485v1 Announce Type: new Abstract: Wave Energy Converters, particularly point absorbers, have emerged as one of the most promising technologies for harvesting ocean wave energy. Nevertheless, achieving high conversion efficiency remains challenging due to the inherently complex and nonlinear interactions b... | https://arxiv.org/abs/2601.06485 | Academic Papers | svg |
229f3ad755ae0a90dcb92579da88bee47a7fd4042564f681013706102b672c6a | 2026-01-13T00:00:00-05:00 | ArenaRL: Scaling RL for Open-Ended Agents via Tournament-based Relative Ranking | arXiv:2601.06487v1 Announce Type: new Abstract: Reinforcement learning has substantially improved the performance of LLM agents on tasks with verifiable outcomes, but it still struggles on open-ended agent tasks with vast solution spaces (e.g., complex travel planning). Due to the absence of objective ground-truth for ... | https://arxiv.org/abs/2601.06487 | Academic Papers | svg |
ca23fea03bdab78995a14f8745519c3723fe6b23721aed1b8a5f2c5dbdd07fd8 | 2026-01-13T00:00:00-05:00 | Bi-Mem: Bidirectional Construction of Hierarchical Memory for Personalized LLMs via Inductive-Reflective Agents | arXiv:2601.06490v1 Announce Type: new Abstract: Constructing memory from users' long-term conversations overcomes LLMs' contextual limitations and enables personalized interactions. Recent studies focus on hierarchical memory to model users' multi-granular behavioral patterns via clustering and aggregating historical c... | https://arxiv.org/abs/2601.06490 | Academic Papers | svg |
51c28a1c142baee3d5cd934159496c106a15f7946c1839776b6f5a1a86895576 | 2026-01-13T00:00:00-05:00 | Algorithms for Computing the Petz-Augustin Capacity | arXiv:2601.06492v1 Announce Type: new Abstract: We propose the first algorithms with non-asymptotic convergence guarantees for computing the Petz-Augustin capacity, which generalizes the channel capacity and characterizes the optimal error exponent in classical-quantum channel coding. This capacity can be equivalently ... | https://arxiv.org/abs/2601.06492 | Academic Papers | svg |
146eb287027464dc60276095bdb453221d2a641262523f3f2cd23c04359af534 | 2026-01-13T00:00:00-05:00 | On the Number of Subsequences in the Nonbinary Deletion Channel | arXiv:2601.06493v1 Announce Type: new Abstract: In the deletion channel, an important problem is to determine the number of subsequences derived from a string $U$ of length $n$ when subjected to $t$ deletions. It is well-known that the number of subsequences in the setting exhibits a strong dependence on the number of ... | https://arxiv.org/abs/2601.06493 | Academic Papers | svg |
0b59aa4fb12c24ab98b8c3dfba234fecddfa1a64ed949e80f0ff9072b32a4134 | 2026-01-13T00:00:00-05:00 | 3D CoCa v2: Contrastive Learners with Test-Time Search for Generalizable Spatial Intelligence | arXiv:2601.06496v1 Announce Type: new Abstract: Spatial intelligence refers to the ability to perceive, reason about, and describe objects and their relationships within three-dimensional environments, forming a foundation for embodied perception and scene understanding. 3D captioning aims to describe 3D scenes in natu... | https://arxiv.org/abs/2601.06496 | Academic Papers | svg |
669da0dfab078d92f41468c796e522b42bbf1dc8798ad49114e594b392ad94ff | 2026-01-13T00:00:00-05:00 | Coding in a Bubble? Evaluating LLMs in Resolving Context Adaptation Bugs During Code Adaptation | arXiv:2601.06497v1 Announce Type: new Abstract: Code adaptation is a fundamental but challenging task in software development, requiring developers to modify existing code for new contexts. A key challenge is to resolve Context Adaptation Bugs (CtxBugs), which occurs when code correct in its original context violates c... | https://arxiv.org/abs/2601.06497 | Academic Papers | svg |
34ca377093e9742f8e9d133d904372d77f02fd3cd0edb19b2d8f7641db69d2b6 | 2026-01-13T00:00:00-05:00 | Spec-o3: A Tool-Augmented Vision-Language Agent for Rare Celestial Object Candidate Vetting via Automated Spectral Inspection | arXiv:2601.06498v1 Announce Type: new Abstract: Due to the limited generalization and interpretability of deep learning classifiers, The final vetting of rare celestial object candidates still relies on expert visual inspection--a manually intensive process. In this process, astronomers leverage specialized tools to an... | https://arxiv.org/abs/2601.06498 | Academic Papers | svg |
46a0d82b8b02331d5d0f5d9b765e0c4c2f7ed06b2e273237fccb4346c1bedd0e | 2026-01-13T00:00:00-05:00 | The AI Pyramid A Conceptual Framework for Workforce Capability in the Age of AI | arXiv:2601.06500v1 Announce Type: new Abstract: Artificial intelligence (AI) represents a qualitative shift in technological change by extending cognitive labor itself rather than merely automating routine tasks. Recent evidence shows that generative AI disproportionately affects highly educated, white collar work, cha... | https://arxiv.org/abs/2601.06500 | Academic Papers | svg |
9edd211a68bcc33a8850823736bc48ecd4fe632046f9013813d18a18fcfc5e4c | 2026-01-13T00:00:00-05:00 | Coding for Fading Channels with Imperfect CSI at the Transmitter and Quantized Feedback | arXiv:2601.06501v1 Announce Type: new Abstract: The classical Schalkwijk-Kailath (SK) scheme for the additive Gaussian noise channel with noiseless feedback is highly efficient since its coding complexity is extremely low and the decoding error doubly exponentially decays as the coding blocklength tends to infinity. Ho... | https://arxiv.org/abs/2601.06501 | Academic Papers | svg |
c9aa2d9e2705bc878288ee571bb9c27c19f04a3551b02a4d71c1eabbb63bfeab | 2026-01-13T00:00:00-05:00 | DRAGON: LLM-Driven Decomposition and Reconstruction Agents for Large-Scale Combinatorial Optimization | arXiv:2601.06502v1 Announce Type: new Abstract: Large Language Models (LLMs) have recently shown promise in addressing combinatorial optimization problems (COPs) through prompt-based strategies. However, their scalability and generalization remain limited, and their effectiveness diminishes as problem size increases, p... | https://arxiv.org/abs/2601.06502 | Academic Papers | svg |
8cf1727222a955c8ad53e245c47f0fbecd730a66aca66f9584d9f7a025886ff8 | 2026-01-13T00:00:00-05:00 | Some New Results on Sequence Reconstruction Problem for Deletion Channels | arXiv:2601.06503v1 Announce Type: new Abstract: Levenshtein first introduced the sequence reconstruction problem in $2001$. In the realm of combinatorics, the sequence reconstruction problem is equivalent to determining the value of $N(n,d,t)$, which represents the maximum size of the intersection of two metric balls o... | https://arxiv.org/abs/2601.06503 | Academic Papers | svg |
cdcc06daee324b9f68525d647ffbf1aa411c2955d39147fc3ec8ca7b35812008 | 2026-01-13T00:00:00-05:00 | Neural Nonmyopic Bayesian Optimization in Dynamic Cost Settings | arXiv:2601.06505v1 Announce Type: new Abstract: Bayesian optimization (BO) is a common framework for optimizing black-box functions, yet most existing methods assume static query costs and rely on myopic acquisition strategies. We introduce LookaHES, a nonmyopic BO framework designed for dynamic, history-dependent cost... | https://arxiv.org/abs/2601.06505 | Academic Papers | svg |
9f9448af963e363284e492c4fc648573fe1bc953b5b0288201d33400bb601434 | 2026-01-13T00:00:00-05:00 | Precision Meets Art: Autonomous Multi-UAV System for Large Scale Mural Drawing | arXiv:2601.06508v1 Announce Type: new Abstract: The integration of autonomous unmanned aerial vehicles (UAVs) into large-scale artistic projects has emerged as a new application in robotics. This paper presents the design, deployment, and testing of a novel multi-drone system for automated mural painting in outdoor set... | https://arxiv.org/abs/2601.06508 | Academic Papers | svg |
77b372e7a57ec8593b15ccf5d7cb43bbbe916784157e9b3e47d33a967a15a83a | 2026-01-13T00:00:00-05:00 | A novel RF-enabled Non-Destructive Inspection Method through Machine Learning and Programmable Wireless Environments | arXiv:2601.06512v1 Announce Type: new Abstract: Contemporary industrial Non-Destructive Inspection (NDI) methods require sensing capabilities that operate in occluded, hazardous, or access restricted environments. Yet, the current visual inspection based on optical cameras offers limited quality of service to that resp... | https://arxiv.org/abs/2601.06512 | Academic Papers | svg |
0f98c833d92b7bb236f0a26e782e8051d65ce6d34f06d6bb518cdb2aefb8564d | 2026-01-13T00:00:00-05:00 | Convergence Analysis of Weighted Median Opinion Dynamics with Higher-Order Effects | arXiv:2601.06515v1 Announce Type: new Abstract: The weighted median mechanism provides a robust alternative to weighted averaging in opinion dynamics. Existing models, however, are predominantly formulated on pairwise interaction graphs, which limits their ability to represent higher-order environmental effects. In thi... | https://arxiv.org/abs/2601.06515 | Academic Papers | svg |
66709d3630701030ee73f93e3569d6861952638de29de62ec46b1af65ba68228 | 2026-01-13T00:00:00-05:00 | Pareto-Optimal Model Selection for Low-Cost, Single-Lead EMG Control in Embedded Systems | arXiv:2601.06516v1 Announce Type: new Abstract: Consumer-grade biosensors offer a cost-effective alternative to medical-grade electromyography (EMG) systems, reducing hardware costs from thousands of dollars to approximately $13. However, these low-cost sensors introduce significant signal instability and motion artifa... | https://arxiv.org/abs/2601.06516 | Academic Papers | svg |
2f44fffa9bbb21dc6bef937231e4d55416d09529eb71dc10751a9d0d8de0f480 | 2026-01-13T00:00:00-05:00 | Bridging Robustness and Efficiency: Real-Time Low-Light Enhancement via Attention U-Net GAN | arXiv:2601.06518v1 Announce Type: new Abstract: Recent advancements in Low-Light Image Enhancement (LLIE) have focused heavily on Diffusion Probabilistic Models, which achieve high perceptual quality but suffer from significant computational latency (often exceeding 2-4 seconds per image). Conversely, traditional CNN-b... | https://arxiv.org/abs/2601.06518 | Academic Papers | svg |
78896be96972779ff1f71eb87c3532e253e7f01597cb9c3e02550893971bc851 | 2026-01-13T00:00:00-05:00 | MedRAGChecker: Claim-Level Verification for Biomedical Retrieval-Augmented Generation | arXiv:2601.06519v1 Announce Type: new Abstract: Biomedical retrieval-augmented generation (RAG) can ground LLM answers in medical literature, yet long-form outputs often contain isolated unsupported or contradictory claims with safety implications. We introduce MedRAGChecker, a claim-level verification and diagnostic f... | https://arxiv.org/abs/2601.06519 | Academic Papers | svg |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.