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cc509bd4d785c041d3700252d4591182c638f1e2a93492f38eaff8c35cf15a0c | 2026-01-01T00:00:00-05:00 | ReSPIRe: Informative and Reusable Belief Tree Search for Robot Probabilistic Search and Tracking in Unknown Environments | arXiv:2512.24680v1 Announce Type: new Abstract: Target search and tracking (SAT) is a fundamental problem for various robotic applications such as search and rescue and environmental exploration. This paper proposes an informative trajectory planning approach, namely ReSPIRe, for SAT in unknown cluttered environments u... | https://arxiv.org/abs/2512.24680 | Academic Papers | svg |
d4459e97e3d19a25efaff108ae2bf18e1941ceba9dbda43883e365992d5fb406 | 2026-01-01T00:00:00-05:00 | CellSecInspector: Safeguarding Cellular Networks via Automated Security Analysis on Specifications | arXiv:2512.24682v1 Announce Type: new Abstract: The complexity, interdependence, and rapid evolution of 3GPP specifications present fundamental challenges for ensuring the security of modern cellular networks. Manual reviews and existing automated approaches, which often depend on rule-based parsing or small sets of ma... | https://arxiv.org/abs/2512.24682 | Academic Papers | svg |
7c266ebb8025af83eace4390b8ce83df7d8a8819e8fa791572c5e327a08e562c | 2026-01-01T00:00:00-05:00 | Waste-to-Energy-Coupled AI Data Centers: Cooling Efficiency and Grid Resilience | arXiv:2512.24683v1 Announce Type: new Abstract: AI data-center expansion is increasingly constrained by the coupled availability of deliverable electricity and heat-rejection (cooling) capacity. We propose and evaluate an integrated Waste-to-Energy-AI Data Center configuration that treats cooling as a first-class energ... | https://arxiv.org/abs/2512.24683 | Academic Papers | svg |
39eb09c40aab42010496b94aa24ff3d43dc06b8109bf8a1ef2952e5fb1959c49 | 2026-01-01T00:00:00-05:00 | R-Debater: Retrieval-Augmented Debate Generation through Argumentative Memory | arXiv:2512.24684v1 Announce Type: new Abstract: We present R-Debater, an agentic framework for generating multi-turn debates built on argumentative memory. Grounded in rhetoric and memory studies, the system views debate as a process of recalling and adapting prior arguments to maintain stance consistency, respond to o... | https://arxiv.org/abs/2512.24684 | Academic Papers | svg |
ce32a0d015f0d3a3cf5f5b70302f79bd428af6d2b8a08bac64ce48548fdb8a9f | 2026-01-01T00:00:00-05:00 | BatteryAgent: Synergizing Physics-Informed Interpretation with LLM Reasoning for Intelligent Battery Fault Diagnosis | arXiv:2512.24686v1 Announce Type: new Abstract: Fault diagnosis of lithium-ion batteries is critical for system safety. While existing deep learning methods exhibit superior detection accuracy, their "black-box" nature hinders interpretability. Furthermore, restricted by binary classification paradigms, they struggle t... | https://arxiv.org/abs/2512.24686 | Academic Papers | svg |
295a6f6a7f61af590b35d0d95e1bcd929e4f985457bcb2d579ee6dbc83daaa82 | 2026-01-01T00:00:00-05:00 | CREPES-X: Hierarchical Bearing-Distance-Inertial Direct Cooperative Relative Pose Estimation System | arXiv:2512.24688v1 Announce Type: new Abstract: Relative localization is critical for cooperation in autonomous multi-robot systems. Existing approaches either rely on shared environmental features or inertial assumptions or suffer from non-line-of-sight degradation and outliers in complex environments. Robust and effi... | https://arxiv.org/abs/2512.24688 | Academic Papers | svg |
45c195979f06dbc6d53ad6d953410228a1e9b086682b2f94ebd3eceab74c9fed | 2026-01-01T00:00:00-05:00 | MUSIC: MUlti-Step Instruction Contrast for Multi-Turn Reward Models | arXiv:2512.24693v1 Announce Type: new Abstract: Evaluating the quality of multi-turn conversations is crucial for developing capable Large Language Models (LLMs), yet remains a significant challenge, often requiring costly human evaluation. Multi-turn reward models (RMs) offer a scalable alternative and can provide val... | https://arxiv.org/abs/2512.24693 | Academic Papers | svg |
9ddc0af596ea1204860552db24620ac55b04f80335d1fd5cd1f1cd58e863d0f3 | 2026-01-01T00:00:00-05:00 | Mobility-Assisted Decentralized Federated Learning: Convergence Analysis and A Data-Driven Approach | arXiv:2512.24694v1 Announce Type: new Abstract: Decentralized Federated Learning (DFL) has emerged as a privacy-preserving machine learning paradigm that enables collaborative training among users without relying on a central server. However, its performance often degrades significantly due to limited connectivity and ... | https://arxiv.org/abs/2512.24694 | Academic Papers | svg |
838a4ca8795fb4794f4cf696c69bcf9083e8ba0d93cb13eb418ee0997097b4f6 | 2026-01-01T00:00:00-05:00 | Nested Learning: The Illusion of Deep Learning Architectures | arXiv:2512.24695v1 Announce Type: new Abstract: Despite the recent progresses, particularly in developing Language Models, there are fundamental challenges and unanswered questions about how such models can continually learn/memorize, self-improve, and find effective solutions. In this paper, we present a new learning ... | https://arxiv.org/abs/2512.24695 | Academic Papers | svg |
e3ddb96ecf90581ae006e0bb77f54443eb382e0b22dd0ca71deda8f1463bc566 | 2026-01-01T00:00:00-05:00 | Causal Discovery with Mixed Latent Confounding via Precision Decomposition | arXiv:2512.24696v1 Announce Type: new Abstract: We study causal discovery from observational data in linear Gaussian systems affected by \emph{mixed latent confounding}, where some unobserved factors act broadly across many variables while others influence only small subsets. This setting is common in practice and pose... | https://arxiv.org/abs/2512.24696 | Academic Papers | svg |
cbe768037c2c82d4c4e34cf0531410707cbd0b69792df26b65d32a469ddce834 | 2026-01-01T00:00:00-05:00 | Dynamic Policy Learning for Legged Robot with Simplified Model Pretraining and Model Homotopy Transfer | arXiv:2512.24698v1 Announce Type: new Abstract: Generating dynamic motions for legged robots remains a challenging problem. While reinforcement learning has achieved notable success in various legged locomotion tasks, producing highly dynamic behaviors often requires extensive reward tuning or high-quality demonstratio... | https://arxiv.org/abs/2512.24698 | Academic Papers | svg |
770da85a59021c0910c56d162dc4c982512182cb7a16d92f5fa09bc1ac88771c | 2026-01-01T00:00:00-05:00 | Average Consensus with Dynamic Quantization Framing and Finite-Time Termination over Limited-Bandwidth Directed Networks | arXiv:2512.24700v1 Announce Type: new Abstract: This paper proposes a deterministic distributed algorithm, referred to as PP-ACDC, that achieves exact average consensus over possibly unbalanced directed graphs using only a fixed and a priori specified number of quantization bits. The method integrates Push-Pull (surplu... | https://arxiv.org/abs/2512.24700 | Academic Papers | svg |
274b1620dd2d5b20aa1cfe6b1aa2ce6a4438bad7107344bf879a1868dd5d16ce | 2026-01-01T00:00:00-05:00 | Evolving, Not Training: Zero-Shot Reasoning Segmentation via Evolutionary Prompting | arXiv:2512.24702v1 Announce Type: new Abstract: Reasoning Segmentation requires models to interpret complex, context-dependent linguistic queries to achieve pixel-level localization. Current dominant approaches rely heavily on Supervised Fine-Tuning (SFT) or Reinforcement Learning (RL). However, SFT suffers from catast... | https://arxiv.org/abs/2512.24702 | Academic Papers | svg |
5b614086237782247d9bcdc1cb55c2319cd7a70cc5919fc30dbec0be4b4837bf | 2026-01-01T00:00:00-05:00 | BandiK: Efficient Multi-Task Decomposition Using a Multi-Bandit Framework | arXiv:2512.24708v1 Announce Type: new Abstract: The challenge of effectively transferring knowledge across multiple tasks is of critical importance and is also present in downstream tasks with foundation models. However, the nature of transfer, its transitive-intransitive nature, is still an open problem, and negative ... | https://arxiv.org/abs/2512.24708 | Academic Papers | svg |
4523ff20eb181b73fa4e67a176e054bb6cb12693b7a3afdce30e7ed7f0900946 | 2026-01-01T00:00:00-05:00 | MEIC-DT: Memory-Efficient Incremental Clustering for Long-Text Coreference Resolution with Dual-Threshold Constraints | arXiv:2512.24711v1 Announce Type: new Abstract: In the era of large language models (LLMs), supervised neural methods remain the state-of-the-art (SOTA) for Coreference Resolution. Yet, their full potential is underexplored, particularly in incremental clustering, which faces the critical challenge of balancing efficie... | https://arxiv.org/abs/2512.24711 | Academic Papers | svg |
f4ef1df6b88c0b36254db7c4be37c09ebc5b8b0026b587cdb8054e8706f7d80d | 2026-01-01T00:00:00-05:00 | LSRE: Latent Semantic Rule Encoding for Real-Time Semantic Risk Detection in Autonomous Driving | arXiv:2512.24712v1 Announce Type: new Abstract: Real-world autonomous driving must adhere to complex human social rules that extend beyond legally codified traffic regulations. Many of these semantic constraints, such as yielding to emergency vehicles, complying with traffic officers' gestures, or stopping for school b... | https://arxiv.org/abs/2512.24712 | Academic Papers | svg |
fcf9c770656c30ac48893107473bc52527862419082c0749170ea69dace2ad4d | 2026-01-01T00:00:00-05:00 | FPGA Co-Design for Efficient N:M Sparse and Quantized Model Inference | arXiv:2512.24713v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated remarkable performance across a wide range of language processing tasks. However, this success comes at the cost of substantial computation and memory requirements, which significantly impedes their deployment in resource-con... | https://arxiv.org/abs/2512.24713 | Academic Papers | svg |
3174d34f93056b94997214d87061cb03603b4d74252b037f5932465e754e527c | 2026-01-01T00:00:00-05:00 | Boundary error control for numerical solution of BSDEs by the convolution-FFT method | arXiv:2512.24714v1 Announce Type: new Abstract: We first review the convolution fast-Fourier-transform (CFFT) approach for the numerical solution of backward stochastic differential equations (BSDEs) introduced in (Hyndman and Oyono Ngou, 2017). We then propose a method for improving the boundary errors obtained when v... | https://arxiv.org/abs/2512.24714 | Academic Papers | svg |
6d54a92c0c56d13266b66bd94f956b59235367f73ec39b614caca18d30410176 | 2026-01-01T00:00:00-05:00 | MDiffFR: Modality-Guided Diffusion Generation for Cold-start Items in Federated Recommendation | arXiv:2512.24715v1 Announce Type: new Abstract: Federated recommendations (FRs) provide personalized services while preserving user privacy by keeping user data on local clients, which has attracted significant attention in recent years. However, due to the strict privacy constraints inherent in FRs, access to user-ite... | https://arxiv.org/abs/2512.24715 | Academic Papers | svg |
d76fa73442defec754befe31729b2cafcfa4f3701cc2c1ceabb65af8bf6b1774 | 2026-01-01T00:00:00-05:00 | Equivalence of Personalized PageRank and Successor Representations | arXiv:2512.24722v1 Announce Type: new Abstract: The hippocampus appears to implement two core but highly distinct functions in the brain: long term memory retrieval and planning and spatial navigation. Naively, these functions appear very different algorithmically. In this short note, we demonstrate that two powerful a... | https://arxiv.org/abs/2512.24722 | Academic Papers | svg |
5761f08ab78ade00798a4db9d507a0440cd7edbef5d6aedc95e914f573c9782e | 2026-01-01T00:00:00-05:00 | FlowBlending: Stage-Aware Multi-Model Sampling for Fast and High-Fidelity Video Generation | arXiv:2512.24724v1 Announce Type: new Abstract: In this work, we show that the impact of model capacity varies across timesteps: it is crucial for the early and late stages but largely negligible during the intermediate stage. Accordingly, we propose FlowBlending, a stage-aware multi-model sampling strategy that employ... | https://arxiv.org/abs/2512.24724 | Academic Papers | svg |
f1ac5a869526d761c548c2f69bf7a039fef5dd947a0a17fb7b5463c84507e945 | 2026-01-01T00:00:00-05:00 | EchoFoley: Event-Centric Hierarchical Control for Video Grounded Creative Sound Generation | arXiv:2512.24731v1 Announce Type: new Abstract: Sound effects build an essential layer of multimodal storytelling, shaping the emotional atmosphere and the narrative semantics of videos. Despite recent advancement in video-text-to-audio (VT2A), the current formulation faces three key limitations: First, an imbalance be... | https://arxiv.org/abs/2512.24731 | Academic Papers | svg |
85521d5a94f90010091ddf379912eb87960d480250b8e98681a9c7a790a9ed26 | 2026-01-01T00:00:00-05:00 | BIOME-Bench: A Benchmark for Biomolecular Interaction Inference and Multi-Omics Pathway Mechanism Elucidation from Scientific Literature | arXiv:2512.24733v1 Announce Type: new Abstract: Multi-omics studies often rely on pathway enrichment to interpret heterogeneous molecular changes, but pathway enrichment (PE)-based workflows inherit structural limitations of pathway resources, including curation lag, functional redundancy, and limited sensitivity to mo... | https://arxiv.org/abs/2512.24733 | Academic Papers | svg |
2616e8d5b3d3f0a679c7c4a4f2834ffeffcb8329193d0d757739590387c124a8 | 2026-01-01T00:00:00-05:00 | Exact compensation of communication delays for discrete-time heterogeneous multi-agent linear systems with applications to SIR epidemic model | arXiv:2512.24735v1 Announce Type: new Abstract: This paper investigates the output synchronization problem for discrete-time heterogeneous multi-agent systems (MASs) subject to distinct communication delays. The presence of such delays prevents the instantaneous delivery of information from neighboring nodes, thereby s... | https://arxiv.org/abs/2512.24735 | Academic Papers | svg |
f725ba468a351f0b36080669106fac2ef5241672a4fbd7bffa4a4139fedadb9b | 2026-01-01T00:00:00-05:00 | SLM-TTA: A Framework for Test-Time Adaptation of Generative Spoken Language Models | arXiv:2512.24739v1 Announce Type: new Abstract: Spoken Language Models (SLMs) are increasingly central to modern speech-driven applications, but performance degrades under acoustic shift - real-world noise, reverberation, and microphone variation. Prior solutions rely on offline domain adaptation, which is post-hoc, da... | https://arxiv.org/abs/2512.24739 | Academic Papers | svg |
53bf5208647156cd45fd94d44369833e00ab7ebba3a31afca29a440bc829e9a3 | 2026-01-01T00:00:00-05:00 | Control of Microrobots with Reinforcement Learning under On-Device Compute Constraints | arXiv:2512.24740v1 Announce Type: new Abstract: An important function of autonomous microrobots is the ability to perform robust movement over terrain. This paper explores an edge ML approach to microrobot locomotion, allowing for on-device, lower latency control under compute, memory, and power constraints. This paper... | https://arxiv.org/abs/2512.24740 | Academic Papers | svg |
c4961bed0b9d8b9ea0610ec12cffec17d97cf1d1d59890ac6e8c8763e3c8760a | 2026-01-01T00:00:00-05:00 | Splatwizard: A Benchmark Toolkit for 3D Gaussian Splatting Compression | arXiv:2512.24742v1 Announce Type: new Abstract: The recent advent of 3D Gaussian Splatting (3DGS) has marked a significant breakthrough in real-time novel view synthesis. However, the rapid proliferation of 3DGS-based algorithms has created a pressing need for standardized and comprehensive evaluation tools, especially... | https://arxiv.org/abs/2512.24742 | Academic Papers | svg |
e49955b822461c5e4c426cc79143caa0ae12afb53c245ba21db2beb86c134a3f | 2026-01-01T00:00:00-05:00 | Analyzing Communication Predictability in LLM Training | arXiv:2512.24750v1 Announce Type: new Abstract: Effective communication is essential in distributed training, with predictability being one of its most significant characteristics. However, existing studies primarily focus on exploiting predictability through online profiling for runtime optimization, without a systema... | https://arxiv.org/abs/2512.24750 | Academic Papers | svg |
c92a515711b2e2b8eb49409ba8afbdec1a23e7e641ca8eb848b9ea5ec9640e17 | 2026-01-01T00:00:00-05:00 | Trustworthy Equipment Monitoring via Cascaded Anomaly Detection and Thermal Localization | arXiv:2512.24755v1 Announce Type: new Abstract: Predictive maintenance demands accurate anomaly detection and trustable explanations. Although multimodal fusion of sensor time-series and thermal imagery shows promise, we demonstrate that naive fusion strategies can paradoxically degrade performance. This paper introduc... | https://arxiv.org/abs/2512.24755 | Academic Papers | svg |
d8069ad61141100799e6a654ceea4da386dc576c19efdf907ba9af67726316bc | 2026-01-01T00:00:00-05:00 | OpenOneRec Technical Report | arXiv:2512.24762v1 Announce Type: new Abstract: While the OneRec series has successfully unified the fragmented recommendation pipeline into an end-to-end generative framework, a significant gap remains between recommendation systems and general intelligence. Constrained by isolated data, they operate as domain special... | https://arxiv.org/abs/2512.24762 | Academic Papers | svg |
cc320f1528d8229d273c885d8cba714647b7746b31791d3e0abb41f20973e0e0 | 2026-01-01T00:00:00-05:00 | UniC-Lift: Unified 3D Instance Segmentation via Contrastive Learning | arXiv:2512.24763v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) and Neural Radiance Fields (NeRF) have advanced novel-view synthesis. Recent methods extend multi-view 2D segmentation to 3D, enabling instance/semantic segmentation for better scene understanding. A key challenge is the inconsistency of 2D in... | https://arxiv.org/abs/2512.24763 | Academic Papers | svg |
9b2a142cad569b2446f20a65826f66918ce3ad96d294926a7d45b51789ff061c | 2026-01-01T00:00:00-05:00 | Dream2Flow: Bridging Video Generation and Open-World Manipulation with 3D Object Flow | arXiv:2512.24766v1 Announce Type: new Abstract: Generative video modeling has emerged as a compelling tool to zero-shot reason about plausible physical interactions for open-world manipulation. Yet, it remains a challenge to translate such human-led motions into the low-level actions demanded by robotic systems. We obs... | https://arxiv.org/abs/2512.24766 | Academic Papers | svg |
dab4e6d5c0d6f4d656c2e1cbfc94a4e8699ae91b8e9bff32c9cc4df2a30f6a5a | 2026-01-01T00:00:00-05:00 | From Trial to Deployment: A SEM Analysis of Traveler Adoptions to Fully Operational Autonomous Taxis | arXiv:2512.24767v1 Announce Type: new Abstract: Autonomous taxi services represent a transformative advancement in urban mobility, offering safety, efficiency, and round-the-clock operations. While existing literature has explored user acceptance of autonomous taxis through stated preference experiments and hypothetica... | https://arxiv.org/abs/2512.24767 | Academic Papers | svg |
44b109bdae1d4caa3e3dd5d94ce92b28d9567e359fa5154bab6fa66d1339bcff | 2026-01-01T00:00:00-05:00 | Uncertainty-aware Semi-supervised Ensemble Teacher Framework for Multilingual Depression Detection | arXiv:2512.24772v1 Announce Type: new Abstract: Detecting depression from social media text is still a challenging task. This is due to different language styles, informal expression, and the lack of annotated data in many languages. To tackle these issues, we propose, Semi-SMDNet, a strong Semi-Supervised Multilingual... | https://arxiv.org/abs/2512.24772 | Academic Papers | svg |
23e235317cda7cb0674ac89dc41815345ad19748c6884fa9a5bc50dd2025817c | 2026-01-01T00:00:00-05:00 | Throughput Optimization in UAV-Mounted RIS under Jittering and Imperfect CSI via DRL | arXiv:2512.24773v1 Announce Type: new Abstract: Reconfigurable intelligent surfaces (RISs) mounted on unmanned aerial vehicles (UAVs) can reshape wireless propagation on-demand. However, their performance is sensitive to UAV jitter and cascaded channel uncertainty. This paper investigates a downlink multiple-input sing... | https://arxiv.org/abs/2512.24773 | Academic Papers | svg |
aefcd52e61076fd8f6f91af660f1966938bc16311a7a1d37d65d5fdb71f7a61d | 2026-01-01T00:00:00-05:00 | Compute-Accuracy Pareto Frontiers for Open-Source Reasoning Large Language Models | arXiv:2512.24776v1 Announce Type: new Abstract: Large Language Models (LLMs) are demonstrating rapid improvements on complex reasoning benchmarks, particularly when allowed to utilize intermediate reasoning steps before converging on a final solution. However, current literature often overlooks the significant computat... | https://arxiv.org/abs/2512.24776 | Academic Papers | svg |
c60f9ec5eb04ca39b120a1f514dca1f3c101d1e0a402a0830a72ed006fc87c16 | 2026-01-01T00:00:00-05:00 | Gradient Descent as Implicit EM in Distance-Based Neural Models | arXiv:2512.24780v1 Announce Type: new Abstract: Neural networks trained with standard objectives exhibit behaviors characteristic of probabilistic inference: soft clustering, prototype specialization, and Bayesian uncertainty tracking. These phenomena appear across architectures -- in attention mechanisms, classificati... | https://arxiv.org/abs/2512.24780 | Academic Papers | svg |
4e27503cf820e89ba3920db2ed120f5872ebb05ae7dc27674e8bdcc09c781b60 | 2026-01-01T00:00:00-05:00 | HiGR: Efficient Generative Slate Recommendation via Hierarchical Planning and Multi-Objective Preference Alignment | arXiv:2512.24787v1 Announce Type: new Abstract: Slate recommendation, where users are presented with a ranked list of items simultaneously, is widely adopted in online platforms. Recent advances in generative models have shown promise in slate recommendation by modeling sequences of discrete semantic IDs autoregressive... | https://arxiv.org/abs/2512.24787 | Academic Papers | svg |
27735d5aa2d9dc2ae60345c73cb356ca3ee1e8087714a5e54abc68452e9d98de | 2026-01-01T00:00:00-05:00 | Projection-based Adversarial Attack using Physics-in-the-Loop Optimization for Monocular Depth Estimation | arXiv:2512.24792v1 Announce Type: new Abstract: Deep neural networks (DNNs) remain vulnerable to adversarial attacks that cause misclassification when specific perturbations are added to input images. This vulnerability also threatens the reliability of DNN-based monocular depth estimation (MDE) models, making robustne... | https://arxiv.org/abs/2512.24792 | Academic Papers | svg |
35dd3c31bbb85dac193f8c58c1048c3f96ecb4c68de262fc5f691ca63f8feac3 | 2026-01-01T00:00:00-05:00 | Self-Supervised Neural Architecture Search for Multimodal Deep Neural Networks | arXiv:2512.24793v1 Announce Type: new Abstract: Neural architecture search (NAS), which automates the architectural design process of deep neural networks (DNN), has attracted increasing attention. Multimodal DNNs that necessitate feature fusion from multiple modalities benefit from NAS due to their structural complexi... | https://arxiv.org/abs/2512.24793 | Academic Papers | svg |
2a6f8f774ac709822512b75a1e26d9df116f470f0038fe8c04639a97fbc4d870 | 2026-01-01T00:00:00-05:00 | Nonlinear Noise2Noise for Efficient Monte Carlo Denoiser Training | arXiv:2512.24794v1 Announce Type: new Abstract: The Noise2Noise method allows for training machine learning-based denoisers with pairs of input and target images where both the input and target can be noisy. This removes the need for training with clean target images, which can be difficult to obtain. However, Noise2No... | https://arxiv.org/abs/2512.24794 | Academic Papers | svg |
391d2efc6e5fca00892be66a3dcb1d6aa8340350557291eeab72542bb380fe5a | 2026-01-01T00:00:00-05:00 | LeanCat: A Benchmark Suite for Formal Category Theory in Lean (Part I: 1-Categories) | arXiv:2512.24796v1 Announce Type: new Abstract: Large language models (LLMs) have made rapid progress in formal theorem proving, yet current benchmarks under-measure the kind of abstraction and library-mediated reasoning that organizes modern mathematics. In parallel with FATE's emphasis on frontier algebra, we introdu... | https://arxiv.org/abs/2512.24796 | Academic Papers | svg |
c5e4997c1b285bdec82fb0751ec729f0cd635ee2502b9dc64b8d1b0c58290cca | 2026-01-01T00:00:00-05:00 | Sidelink Positioning: Standardization Advancements, Challenges and Opportunities | arXiv:2512.24803v1 Announce Type: new Abstract: With the integration of cellular networks in vertical industries that demand precise location information, such as vehicle-to-everything (V2X), public safety, and Industrial Internet of Things (IIoT), positioning has become an imperative component for future wireless netw... | https://arxiv.org/abs/2512.24803 | Academic Papers | svg |
0812dfe02c58e1803c8773ea57df676acef209b4354db41996cdbf3e7876b33f | 2026-01-01T00:00:00-05:00 | DTI-GP: Bayesian operations for drug-target interactions using deep kernel Gaussian processes | arXiv:2512.24810v1 Announce Type: new Abstract: Precise probabilistic information about drug-target interaction (DTI) predictions is vital for understanding limitations and boosting predictive performance. Gaussian processes (GP) offer a scalable framework to integrate state-of-the-art DTI representations and Bayesian ... | https://arxiv.org/abs/2512.24810 | Academic Papers | svg |
3cb214c5c96e49744ce045cf22056fc1bc6bae9015798b050f37c0fa560709c2 | 2026-01-01T00:00:00-05:00 | Unregularized Linear Convergence in Zero-Sum Game from Preference Feedback | arXiv:2512.24818v1 Announce Type: new Abstract: Aligning large language models (LLMs) with human preferences has proven effective for enhancing model capabilities, yet standard preference modeling using the Bradley-Terry model assumes transitivity, overlooking the inherent complexity of human population preferences. Na... | https://arxiv.org/abs/2512.24818 | Academic Papers | svg |
c3a3cb3900e72ea3484a07ff72fe0846114400ffda28557f79e3ec65d60b0030 | 2026-01-01T00:00:00-05:00 | LMG Index: A Robust Learned Index for Multi-Dimensional Performance Balance | arXiv:2512.24824v1 Announce Type: new Abstract: Index structures are fundamental for efficient query processing on large-scale datasets. Learned indexes model the indexing process as a prediction problem to overcome the inherent trade-offs of traditional indexes. However, most existing learned indexes optimize only for... | https://arxiv.org/abs/2512.24824 | Academic Papers | svg |
2ee13ea42e6ebdc1276f146203550e2586d4adf1fbabcc491df9ea563add6787 | 2026-01-01T00:00:00-05:00 | Practising responsibility: Ethics in NLP as a hands-on course | arXiv:2512.24825v1 Announce Type: new Abstract: As Natural Language Processing (NLP) systems become more pervasive, integrating ethical considerations into NLP education has become essential. However, this presents inherent challenges in curriculum development: the field's rapid evolution from both academia and industr... | https://arxiv.org/abs/2512.24825 | Academic Papers | svg |
305ff843b3917333072cf5b1bbfa47ba408aac8bb7fee90d8668a9662cb385b9 | 2026-01-01T00:00:00-05:00 | Video and Language Alignment in 2D Systems for 3D Multi-object Scenes with Multi-Information Derivative-Free Control | arXiv:2512.24826v1 Announce Type: new Abstract: Cross-modal systems trained on 2D visual inputs are presented with a dimensional shift when processing 3D scenes. An in-scene camera bridges the dimensionality gap but requires learning a control module. We introduce a new method that improves multivariate mutual informat... | https://arxiv.org/abs/2512.24826 | Academic Papers | svg |
a2a9c405fdd50ff6438a2547c4caf69cb8e55b67b16e714cf6d0890d51aeddb5 | 2026-01-01T00:00:00-05:00 | Discovering Coordinated Joint Options via Inter-Agent Relative Dynamics | arXiv:2512.24827v1 Announce Type: new Abstract: Temporally extended actions improve the ability to explore and plan in single-agent settings. In multi-agent settings, the exponential growth of the joint state space with the number of agents makes coordinated behaviours even more valuable. Yet, this same exponential gro... | https://arxiv.org/abs/2512.24827 | Academic Papers | svg |
5016c64057d10d36d291dd99327ccb86af677e626cb3c12ab733147e1f6db56c | 2026-01-01T00:00:00-05:00 | Explaining Why Things Go Where They Go: Interpretable Constructs of Human Organizational Preferences | arXiv:2512.24829v1 Announce Type: new Abstract: Robotic systems for household object rearrangement often rely on latent preference models inferred from human demonstrations. While effective at prediction, these models offer limited insight into the interpretable factors that guide human decisions. We introduce an expli... | https://arxiv.org/abs/2512.24829 | Academic Papers | svg |
75cb0244abc53ec9105743f7cffc6504889bb7fb57a1cb59bbec6b75535f53c4 | 2026-01-01T00:00:00-05:00 | GenZ: Foundational models as latent variable generators within traditional statistical models | arXiv:2512.24834v1 Announce Type: new Abstract: We present GenZ, a hybrid model that bridges foundational models and statistical modeling through interpretable semantic features. While large language models possess broad domain knowledge, they often fail to capture dataset-specific patterns critical for prediction task... | https://arxiv.org/abs/2512.24834 | Academic Papers | svg |
1784fc7f3158d6005d858ea07b99588ea9e019b9737bbb07c8008ec3a4132cbd | 2026-01-01T00:00:00-05:00 | CropTrack: A Tracking with Re-Identification Framework for Precision Agriculture | arXiv:2512.24838v1 Announce Type: new Abstract: Multiple-object tracking (MOT) in agricultural environments presents major challenges due to repetitive patterns, similar object appearances, sudden illumination changes, and frequent occlusions. Contemporary trackers in this domain rely on the motion of objects rather th... | https://arxiv.org/abs/2512.24838 | Academic Papers | svg |
8b8a06b81edc10f6936d476860c8684c5e8bf936958cf0db7bdc12b59dafbe63 | 2026-01-01T00:00:00-05:00 | When Does the Silhouette Score Work? A Comprehensive Study in Network Clustering | arXiv:2512.24841v1 Announce Type: new Abstract: Selecting the number of communities is a fundamental challenge in network clustering. The silhouette score offers an intuitive, model-free criterion that balances within-cluster cohesion and between-cluster separation. Albeit its widespread use in clustering analysis, its... | https://arxiv.org/abs/2512.24841 | Academic Papers | svg |
bb13c0aa75e98a571b7f34bb3cd4db2dcc5eef1d988bdff2bbe2386730abca14 | 2026-01-01T00:00:00-05:00 | Triangulation as an Acceptance Rule for Multilingual Mechanistic Interpretability | arXiv:2512.24842v1 Announce Type: new Abstract: Multilingual language models achieve strong aggregate performance yet often behave unpredictably across languages, scripts, and cultures. We argue that mechanistic explanations for such models should satisfy a \emph{causal} standard: claims must survive causal interventio... | https://arxiv.org/abs/2512.24842 | Academic Papers | svg |
274229029c7d122e4fd05bab61dd00211b77e587ac9e63344f853c0476ae8079 | 2026-01-01T00:00:00-05:00 | ArtiSG: Functional 3D Scene Graph Construction via Human-demonstrated Articulated Objects Manipulation | arXiv:2512.24845v1 Announce Type: new Abstract: 3D scene graphs have empowered robots with semantic understanding for navigation and planning, yet they often lack the functional information required for physical manipulation, particularly regarding articulated objects. Existing approaches for inferring articulation mec... | https://arxiv.org/abs/2512.24845 | Academic Papers | svg |
8347658146fcfe00dc00e0b552bef80a96b1813b38cde1059bbcf40f90c2be26 | 2026-01-01T00:00:00-05:00 | AODDiff: Probabilistic Reconstruction of Aerosol Optical Depth via Diffusion-based Bayesian Inference | arXiv:2512.24847v1 Announce Type: new Abstract: High-quality reconstruction of Aerosol Optical Depth (AOD) fields is critical for Atmosphere monitoring, yet current models remain constrained by the scarcity of complete training data and a lack of uncertainty quantification.To address these limitations, we propose AODDi... | https://arxiv.org/abs/2512.24847 | Academic Papers | svg |
33cc0849b97e1748cadf7d218b3180f475205ed9ba478cdaa7bfa4343555e5de | 2026-01-01T00:00:00-05:00 | PrivacyBench: A Conversational Benchmark for Evaluating Privacy in Personalized AI | arXiv:2512.24848v1 Announce Type: new Abstract: Personalized AI agents rely on access to a user's digital footprint, which often includes sensitive data from private emails, chats and purchase histories. Yet this access creates a fundamental societal and privacy risk: systems lacking social-context awareness can uninte... | https://arxiv.org/abs/2512.24848 | Academic Papers | svg |
a70faf7221b1b04bfdcec1ec0daec210a5ee188a92b6fd033447fad666ff5e04 | 2026-01-01T00:00:00-05:00 | On an Erd\H{o}s--Lov'asz problem: 3-critical 3-graphs of minimum degree 7 | arXiv:2512.24850v1 Announce Type: new Abstract: Erd\H{o}s and Lov'asz asked whether there exists a "3-critical" 3-uniform hypergraph in which every vertex has degree at least 7. The original formulation does not specify what 3-critical means, and two non-equivalent notions have appeared in the literature and in later d... | https://arxiv.org/abs/2512.24850 | Academic Papers | svg |
2eb262165c0a558062d2f11c9fd476737c2dfecad7208b9c4e81e86bd63d0ce1 | 2026-01-01T00:00:00-05:00 | VLN-MME: Diagnosing MLLMs as Language-guided Visual Navigation agents | arXiv:2512.24851v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities across a wide range of vision-language tasks. However, their performance as embodied agents, which requires multi-round dialogue spatial reasoning and sequential action prediction, needs fu... | https://arxiv.org/abs/2512.24851 | Academic Papers | svg |
25224fe29573d6bfb424369c80e164804ddfbc082f089b6d884c5dc7d7195f66 | 2026-01-01T00:00:00-05:00 | A study on constraint extraction and exception exclusion in care worker scheduling | arXiv:2512.24853v1 Announce Type: new Abstract: Technologies for automatically generating work schedules have been extensively studied; however, in long-term care facilities, the conditions vary between facilities, making it essential to interview the managers who create shift schedules to design facility-specific cons... | https://arxiv.org/abs/2512.24853 | Academic Papers | svg |
597a112699ff72f65024585978080b4c151e2a5c950f888ce9c6a39de4a15b33 | 2026-01-01T00:00:00-05:00 | Feature Slice Matching for Precise Bug Detection | arXiv:2512.24858v1 Announce Type: new Abstract: Measuring the function similarity to detect bugs is effective, but the statements unrelated to the bugs can impede the performance due to the noise interference. Suppressing the noise interference in existing works does not manage the tough job, i.e., eliminating the nois... | https://arxiv.org/abs/2512.24858 | Academic Papers | svg |
4fc4f50552a1267794ef276d708f5b9bf01ba45592273836b865763ade8776ef | 2026-01-01T00:00:00-05:00 | OFL-SAM2: Prompt SAM2 with Online Few-shot Learner for Efficient Medical Image Segmentation | arXiv:2512.24861v1 Announce Type: new Abstract: The Segment Anything Model 2 (SAM2) has demonstrated remarkable promptable visual segmentation capabilities in video data, showing potential for extension to medical image segmentation (MIS) tasks involving 3D volumes and temporally correlated 2D image sequences. However,... | https://arxiv.org/abs/2512.24861 | Academic Papers | svg |
d3766801932ac91d51cfd9d914afb1ace8c99c94f2d4f2fef116a046d8e2d0c1 | 2026-01-01T00:00:00-05:00 | Big AI is accelerating the metacrisis: What can we do? | arXiv:2512.24863v1 Announce Type: new Abstract: The world is in the grip of ecological, meaning, and language crises which are converging into a metacrisis. Big AI is accelerating them all. Language engineers are playing a central role, persisting with a scalability story that is failing humanity, supplying critical ta... | https://arxiv.org/abs/2512.24863 | Academic Papers | svg |
1cbbb38f5ce29adb062bee892d048f12bd1de0dee168e76420c9f67c1e09a89b | 2026-01-01T00:00:00-05:00 | Characterization of Transfer Using Multi-task Learning Curves | arXiv:2512.24866v1 Announce Type: new Abstract: Transfer effects manifest themselves both during training using a fixed data set and in inductive inference using accumulating data. We hypothesize that perturbing the data set by including more samples, instead of perturbing the model by gradient updates, provides a comp... | https://arxiv.org/abs/2512.24866 | Academic Papers | svg |
901366c52f370c3f3139ab840ec5bc00231cccc6468404e920ab41f75b21c5ae | 2026-01-01T00:00:00-05:00 | Encyclo-K: Evaluating LLMs with Dynamically Composed Knowledge Statements | arXiv:2512.24867v1 Announce Type: new Abstract: Benchmarks play a crucial role in tracking the rapid advancement of large language models (LLMs) and identifying their capability boundaries. However, existing benchmarks predominantly curate questions at the question level, suffering from three fundamental limitations: v... | https://arxiv.org/abs/2512.24867 | Academic Papers | svg |
0ba2993d849de2650dd33c4b6a9051e6a419b7f0f72dc6be2c8e376e8627a0ac | 2026-01-01T00:00:00-05:00 | Let It Flow: Agentic Crafting on Rock and Roll, Building the ROME Model within an Open Agentic Learning Ecosystem | arXiv:2512.24873v1 Announce Type: new Abstract: Agentic crafting requires LLMs to operate in real-world environments over multiple turns by taking actions, observing outcomes, and iteratively refining artifacts. Despite its importance, the open-source community lacks a principled, end-to-end ecosystem to streamline age... | https://arxiv.org/abs/2512.24873 | Academic Papers | svg |
6ced47211c37c02a44efc83743609bd624570f08f84bbc873c4e7bfcac168675 | 2026-01-01T00:00:00-05:00 | A structure-preserving parametric approximation for anisotropic geometric flows via an $\alpha$-surface energy matrix | arXiv:2512.24875v1 Announce Type: new Abstract: We propose a structure-preserving parametric approximation for geometric flows with general anisotropic effects. By introducing a hyperparameter $\alpha$, we construct a unified surface energy matrix $\hat{\boldsymbol{G}}_k^\alpha(\theta)$ that encompasses all existing fo... | https://arxiv.org/abs/2512.24875 | Academic Papers | svg |
dc32503d2fd0b5e2c298f081621ff62c49103a8f9ebc7c13bd41b75510b75888 | 2026-01-01T00:00:00-05:00 | Random compressible Euler flows | arXiv:2512.24879v1 Announce Type: new Abstract: We propose a finite volume stochastic collocation method for the random Euler system. We rigorously prove the convergence of random finite volume solutions under the assumption that the discrete differential quotients remain bounded in probability. Convergence analysis co... | https://arxiv.org/abs/2512.24879 | Academic Papers | svg |
9067e9760b6a98182a564f6730d5d91a62d8e5f416db79d375e4970c2a395e88 | 2026-01-01T00:00:00-05:00 | mHC: Manifold-Constrained Hyper-Connections | arXiv:2512.24880v1 Announce Type: new Abstract: Recently, studies exemplified by Hyper-Connections (HC) have extended the ubiquitous residual connection paradigm established over the past decade by expanding the residual stream width and diversifying connectivity patterns. While yielding substantial performance gains, ... | https://arxiv.org/abs/2512.24880 | Academic Papers | svg |
bbd32c38c8398b3cd7fb5ef7fc92851be6a28efb7747ed01b0a418d13b252e4e | 2026-01-01T00:00:00-05:00 | BEDA: Belief Estimation as Probabilistic Constraints for Performing Strategic Dialogue Acts | arXiv:2512.24885v1 Announce Type: new Abstract: Strategic dialogue requires agents to execute distinct dialogue acts, for which belief estimation is essential. While prior work often estimates beliefs accurately, it lacks a principled mechanism to use those beliefs during generation. We bridge this gap by first formali... | https://arxiv.org/abs/2512.24885 | Academic Papers | svg |
1f74ad0393dd9263f2ed1bc34c4445d5a8fc6724035ec32c07035885c940ddd6 | 2026-01-01T00:00:00-05:00 | Heterogeneous Multi-Agent Multi-Target Tracking using Cellular Sheaves | arXiv:2512.24886v1 Announce Type: new Abstract: Multi-agent target tracking in the presence of nonlinear dynamics and agent heterogeneity, where state-space dimensions may differ, is a challenging problem that traditional graph Laplacian methods cannot easily address. This work leverages the framework of cellular sheav... | https://arxiv.org/abs/2512.24886 | Academic Papers | svg |
d73b9cc26dcf060df80cafb251c839db4cdcc8a80b779d2a0e6f29fe6c466298 | 2026-01-01T00:00:00-05:00 | SoK: Web3 RegTech for Cryptocurrency VASP AML/CFT Compliance | arXiv:2512.24888v1 Announce Type: new Abstract: The decentralized architecture of Web3 technologies creates fundamental challenges for Anti-Money Laundering and Counter-Financing of Terrorism compliance. Traditional regulatory technology solutions designed for centralized financial systems prove inadequate for blockcha... | https://arxiv.org/abs/2512.24888 | Academic Papers | svg |
f24754432d4202db806610df94d19219218e32d6f61ec6dac480d21184b9f3df | 2026-01-01T00:00:00-05:00 | Semi-Automated Data Annotation in Multisensor Datasets for Autonomous Vehicle Testing | arXiv:2512.24896v1 Announce Type: new Abstract: This report presents the design and implementation of a semi-automated data annotation pipeline developed within the DARTS project, whose goal is to create a large-scale, multimodal dataset of driving scenarios recorded in Polish conditions. Manual annotation of such hete... | https://arxiv.org/abs/2512.24896 | Academic Papers | svg |
26acd566c1f0a4095a536b3c9d6ecd9fe2683e140a046919538a452b1b3fd1bf | 2026-01-01T00:00:00-05:00 | PRISM: A hierarchical multiscale approach for time series forecasting | arXiv:2512.24898v1 Announce Type: new Abstract: Forecasting is critical in areas such as finance, biology, and healthcare. Despite the progress in the field, making accurate forecasts remains challenging because real-world time series contain both global trends, local fine-grained structure, and features on multiple sc... | https://arxiv.org/abs/2512.24898 | Academic Papers | svg |
95acf6b04cf8eb5eb141dc3adb678b12a9c16cf375d55a78660c52d88171b7e0 | 2026-01-01T00:00:00-05:00 | MTSP-LDP: A Framework for Multi-Task Streaming Data Publication under Local Differential Privacy | arXiv:2512.24899v1 Announce Type: new Abstract: The proliferation of streaming data analytics in data-driven applications raises critical privacy concerns, as directly collecting user data may compromise personal privacy. Although existing $w$-event local differential privacy (LDP) mechanisms provide formal guarantees ... | https://arxiv.org/abs/2512.24899 | Academic Papers | svg |
28c0641c2f04fe3a451c22c72d26a93f089fa69c8a6af55232491bdf884d9283 | 2026-01-01T00:00:00-05:00 | Spectral Graph Neural Networks for Cognitive Task Classification in fMRI Connectomes | arXiv:2512.24901v1 Announce Type: new Abstract: Cognitive task classification using machine learning plays a central role in decoding brain states from neuroimaging data. By integrating machine learning with brain network analysis, complex connectivity patterns can be extracted from functional magnetic resonance imagin... | https://arxiv.org/abs/2512.24901 | Academic Papers | svg |
b72f175d68e96b40737aca4a857eec056e573e33e5f01c60b76d37e28727b7df | 2026-01-01T00:00:00-05:00 | FinMMDocR: Benchmarking Financial Multimodal Reasoning with Scenario Awareness, Document Understanding, and Multi-Step Computation | arXiv:2512.24903v1 Announce Type: new Abstract: We introduce FinMMDocR, a novel bilingual multimodal benchmark for evaluating multimodal large language models (MLLMs) on real-world financial numerical reasoning. Compared to existing benchmarks, our work delivers three major advancements. (1) Scenario Awareness: 57.9% o... | https://arxiv.org/abs/2512.24903 | Academic Papers | svg |
b80bc2bffe6259c6353d116baa7010b4554887474f9a5739323ca14576230338 | 2026-01-01T00:00:00-05:00 | One-Shot Camera-Based Extrusion Optimization for High Speed Fused Filament Fabrication | arXiv:2512.24905v1 Announce Type: new Abstract: Off-the-shelf fused filament fabrication 3D printers are widely accessible and convenient, yet they exhibit quality loss at high speeds due to dynamic mis-synchronization between printhead motion and material extrusion systems, notably corner over-extrusion. Existing meth... | https://arxiv.org/abs/2512.24905 | Academic Papers | svg |
e6abda0e1b249b25910e457def91f7219f7e4f6fb0141e84417edb836af9ed34 | 2026-01-01T00:00:00-05:00 | AI-Driven Cloud Resource Optimization for Multi-Cluster Environments | arXiv:2512.24914v1 Announce Type: new Abstract: Modern cloud-native systems increasingly rely on multi-cluster deployments to support scalability, resilience, and geographic distribution. However, existing resource management approaches remain largely reactive and cluster-centric, limiting their ability to optimize sys... | https://arxiv.org/abs/2512.24914 | Academic Papers | svg |
8414880e661e186c188a8b12e4f26fabd005e5a7059fb76eb69cb55d189fff86 | 2026-01-01T00:00:00-05:00 | Frequent subgraph-based persistent homology for graph classification | arXiv:2512.24917v1 Announce Type: new Abstract: Persistent homology (PH) has recently emerged as a powerful tool for extracting topological features. Integrating PH into machine learning and deep learning models enhances topology awareness and interpretability. However, most PH methods on graphs rely on a limited set o... | https://arxiv.org/abs/2512.24917 | Academic Papers | svg |
e27be2b666b43d6ffe9f38bd5191e214cbf3137e85062ab12e36af6fc580c290 | 2026-01-01T00:00:00-05:00 | Semi-Supervised Diversity-Aware Domain Adaptation for 3D Object detection | arXiv:2512.24922v1 Announce Type: new Abstract: 3D object detectors are fundamental components of perception systems in autonomous vehicles. While these detectors achieve remarkable performance on standard autonomous driving benchmarks, they often struggle to generalize across different domains - for instance, a model ... | https://arxiv.org/abs/2512.24922 | Academic Papers | svg |
0e0923cf595784eabdb3dce01400d4874feafb352f8a07ad2df447189d61322b | 2026-01-01T00:00:00-05:00 | Towards Provably Secure Generative AI: Reliable Consensus Sampling | arXiv:2512.24925v1 Announce Type: new Abstract: Existing research on generative AI security is primarily driven by mutually reinforcing attack and defense methodologies grounded in empirical experience. This dynamic frequently gives rise to previously unknown attacks that can circumvent current detection and prevention... | https://arxiv.org/abs/2512.24925 | Academic Papers | svg |
fea19b205444af5951f0d474b48edc7466ed001f1bdce94d01a4bc1eed72021c | 2026-01-01T00:00:00-05:00 | A finite element approach for minimizing line and surface energies arising in the study of singularities in liquid crystals | arXiv:2512.24928v1 Announce Type: new Abstract: Motivated by a problem originating in the study of defect structures in nematic liquid crystals, we describe and study a numerical algorithm for the resolution of a Plateau-like problem. The energy contains the area of a two-dimensional surface $T$ and the length of its b... | https://arxiv.org/abs/2512.24928 | Academic Papers | svg |
95999ee478ab26886652115e5669ea7826e76293098523e0ff7a9f27da2a0653 | 2026-01-01T00:00:00-05:00 | Adaptive Dependency-aware Prompt Optimization Framework for Multi-Step LLM Pipeline | arXiv:2512.24933v1 Announce Type: new Abstract: Multi-step LLM pipelines invoke large language models multiple times in a structured sequence and can effectively solve complex tasks, but their performance heavily depends on the prompts used at each step. Jointly optimizing these prompts is difficult due to missing step... | https://arxiv.org/abs/2512.24933 | Academic Papers | svg |
825f59513692c90ba5b3aa4065b00b4061e170452c1669d2d4fb28f4dc393ddc | 2026-01-01T00:00:00-05:00 | Fair Committee Selection under Ordinal Preferences and Limited Cardinal Information | arXiv:2512.24934v1 Announce Type: new Abstract: We study the problem of fair $k$-committee selection under an egalitarian objective. Given $n$ agents partitioned into $m$ groups (\eg, demographic quotas), the goal is to aggregate their preferences to form a committee of size $k$ that guarantees minimum representation f... | https://arxiv.org/abs/2512.24934 | Academic Papers | svg |
598283c75482571cc2d7d9cb0c8f9321ff499d174094cd6d883b88509831caa9 | 2026-01-01T00:00:00-05:00 | Vibe Coding, Interface Flattening | arXiv:2512.24939v1 Announce Type: new Abstract: Large language models are reshaping programming by enabling 'vibe coding': the development of softwares through natural-language interaction with model-driven toolchains. This article argues that vibe coding is best understood as interface flattening, a reconfiguration in... | https://arxiv.org/abs/2512.24939 | Academic Papers | svg |
0e223049330029239743fe675e2b4686435e14be0eea0ee156054ed2ce043765 | 2026-01-01T00:00:00-05:00 | Iterative Deployment Improves Planning Skills in LLMs | arXiv:2512.24940v1 Announce Type: new Abstract: We show that iterative deployment of large language models (LLMs), each fine-tuned on data carefully curated by users from the previous models' deployment, can significantly change the properties of the resultant models. By testing this mechanism on various planning domai... | https://arxiv.org/abs/2512.24940 | Academic Papers | svg |
c4bcccdc53c3d990b2b76da914312763bc2d3d0386c270e5a9e395b7f98c696f | 2026-01-01T00:00:00-05:00 | Securing High-Concurrency Ticket Sales: A Framework Based on Microservice | arXiv:2512.24941v1 Announce Type: new Abstract: The railway ticketing system is one of the most important public service infrastructure. In peak periods such as holidays, it is often faced with the challenge of high concurrency scenarios because of a large number of users accessing at the same time. The traditional agg... | https://arxiv.org/abs/2512.24941 | Academic Papers | svg |
35d771e2333e87409658bf8f116b56c3996a76a874bc4de05cb6249a3431c9af | 2026-01-01T00:00:00-05:00 | RAIR: A Rule-Aware Benchmark Uniting Challenging Long-Tail and Visual Salience Subset for E-commerce Relevance Assessment | arXiv:2512.24943v1 Announce Type: new Abstract: Search relevance plays a central role in web e-commerce. While large language models (LLMs) have shown significant results on relevance task, existing benchmarks lack sufficient complexity for comprehensive model assessment, resulting in an absence of standardized relevan... | https://arxiv.org/abs/2512.24943 | Academic Papers | svg |
64c0eca0ea4e864a87369686e86c5b40e0bf1df3e4b272725ca716789c40e6ea | 2026-01-01T00:00:00-05:00 | HaineiFRDM: Explore Diffusion to Restore Defects in Fast-Movement Films | arXiv:2512.24946v1 Announce Type: new Abstract: Existing open-source film restoration methods show limited performance compared to commercial methods due to training with low-quality synthetic data and employing noisy optical flows. In addition, high-resolution films have not been explored by the open-source methods.We... | https://arxiv.org/abs/2512.24946 | Academic Papers | svg |
4f403f05e66b3eb17787c16a392d1ad03c69310e5fa9990a7d65491125e6882c | 2026-01-01T00:00:00-05:00 | CPJ: Explainable Agricultural Pest Diagnosis via Caption-Prompt-Judge with LLM-Judged Refinement | arXiv:2512.24947v1 Announce Type: new Abstract: Accurate and interpretable crop disease diagnosis is essential for agricultural decision-making, yet existing methods often rely on costly supervised fine-tuning and perform poorly under domain shifts. We propose Caption--Prompt--Judge (CPJ), a training-free few-shot fram... | https://arxiv.org/abs/2512.24947 | Academic Papers | svg |
d5f81c219af3678e3c72423ccb9b78b1b5597d52e7ab97411d6c9c3db697c032 | 2026-01-01T00:00:00-05:00 | ProDM: Synthetic Reality-driven Property-aware Progressive Diffusion Model for Coronary Calcium Motion Correction in Non-gated Chest CT | arXiv:2512.24948v1 Announce Type: new Abstract: Coronary artery calcium (CAC) scoring from chest CT is a well-established tool to stratify and refine clinical cardiovascular disease risk estimation. CAC quantification relies on the accurate delineation of calcified lesions, but is oftentimes affected by artifacts intro... | https://arxiv.org/abs/2512.24948 | Academic Papers | svg |
1ec2670fcb346076a92d962ffac79d3611ff0619c4416deca2d4567c8dab55d0 | 2026-01-01T00:00:00-05:00 | VIPER: Process-aware Evaluation for Generative Video Reasoning | arXiv:2512.24952v1 Announce Type: new Abstract: Recent breakthroughs in video generation have demonstrated an emerging capability termed Chain-of-Frames (CoF) reasoning, where models resolve complex tasks through the generation of continuous frames. While these models show promise for Generative Video Reasoning (GVR), ... | https://arxiv.org/abs/2512.24952 | Academic Papers | svg |
84708dae6fdc1ac3c9af4e7150dc258a5e141b24beeea01377225918eaf5fb87 | 2026-01-01T00:00:00-05:00 | MSACL: Multi-Step Actor-Critic Learning with Lyapunov Certificates for Exponentially Stabilizing Control | arXiv:2512.24955v1 Announce Type: new Abstract: Achieving provable stability in model-free reinforcement learning (RL) remains a challenge, particularly in balancing exploration with rigorous safety. This article introduces MSACL, a framework that integrates exponential stability theory with maximum entropy RL through ... | https://arxiv.org/abs/2512.24955 | Academic Papers | svg |
0ec3d4faa1becffe128993afff16f96d3afab7ca160588f8f1ee9b254e12e484 | 2026-01-01T00:00:00-05:00 | AMAP Agentic Planning Technical Report | arXiv:2512.24957v1 Announce Type: new Abstract: We present STAgent, an agentic large language model tailored for spatio-temporal understanding, designed to solve complex tasks such as constrained point-of-interest discovery and itinerary planning. STAgent is a specialized model capable of interacting with ten distinct ... | https://arxiv.org/abs/2512.24957 | Academic Papers | svg |
7dac6f19001f70b9b4d0789ae8de63aa17ef7e539557b77b90377273837bbdb1 | 2026-01-01T00:00:00-05:00 | Semi-overlapping Multi-bandit Best Arm Identification for Sequential Support Network Learning | arXiv:2512.24959v1 Announce Type: new Abstract: Many modern AI and ML problems require evaluating partners' contributions through shared yet asymmetric, computationally intensive processes and the simultaneous selection of the most beneficial candidates. Sequential approaches to these problems can be unified under a ne... | https://arxiv.org/abs/2512.24959 | Academic Papers | svg |
b8a8f7ab569889837f23917f6cdc04258d1c135fa1207ddc0e0777d432419475 | 2026-01-01T00:00:00-05:00 | Approximating evolution operators of linear delay equations: a general framework for the convergence analysis | arXiv:2512.24964v1 Announce Type: new Abstract: We consider the problem of discretizing evolution operators of linear delay equations with the aim of approximating their spectra, which is useful in investigating the stability properties of (nonlinear) equations via the principle of linearized stability. We develop a ge... | https://arxiv.org/abs/2512.24964 | Academic Papers | svg |
0ad45719eb6292f873af628cd84dc0db7e2f5912ee4f5e716398abcb5b7721cd | 2026-01-01T00:00:00-05:00 | ShowUI-$\pi$: Flow-based Generative Models as GUI Dexterous Hands | arXiv:2512.24965v1 Announce Type: new Abstract: Building intelligent agents capable of dexterous manipulation is essential for achieving human-like automation in both robotics and digital environments. However, existing GUI agents rely on discrete click predictions (x,y), which prohibits free-form, closed-loop trajecto... | https://arxiv.org/abs/2512.24965 | Academic Papers | svg |
0dcd6c4b84b408dea67a1366ef0344fc8b71e4c1087e1df3c774000d16a0c5a4 | 2026-01-01T00:00:00-05:00 | Evaluating the Impact of Compression Techniques on the Robustness of CNNs under Natural Corruptions | arXiv:2512.24971v1 Announce Type: new Abstract: Compressed deep learning models are crucial for deploying computer vision systems on resource-constrained devices. However, model compression may affect robustness, especially under natural corruption. Therefore, it is important to consider robustness evaluation while val... | https://arxiv.org/abs/2512.24971 | Academic Papers | svg |
61fdcc405e21e864b226fb65df5b82461bcf3f34740d94526f902bdad0beed69 | 2026-01-01T00:00:00-05:00 | Hierarchical Deformation Planning and Neural Tracking for DLOs in Constrained Environments | arXiv:2512.24974v1 Announce Type: new Abstract: Deformable linear objects (DLOs) manipulation presents significant challenges due to DLOs' inherent high-dimensional state space and complex deformation dynamics. The wide-populated obstacles in realistic workspaces further complicate DLO manipulation, necessitating effic... | https://arxiv.org/abs/2512.24974 | Academic Papers | svg |
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