AI news archive.
10,659 articles filed under Research, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchRisk-Calibrated Proposal Transport for Finite-Particle Diffusion Steering
arXiv:2610.04171v1 Announce Type: cross Abstract: Inference-time steering combines pretrained diffusion experts or rewards without retraining by changing the dynamics that transport noise to data. Feynman-Kac correction…
- arXiv cs.AIresearchClean: Second-order LLM Training at Linear Memory Cost via Nystr{\"o}m Sketching
arXiv:2610.04204v3 Announce Type: replace-cross Abstract: Training large language models (LLMs) entails a fundamental trade-off: memory-efficient optimizers such as Adam discard cross-parameter curvature, whereas full-cu…
- arXiv cs.AIresearchCurveCodec 2: Skeleton-agnostic animation compression with a learned entropy model
arXiv:2610.04211v1 Announce Type: cross Abstract: Skeletal motion is stored as every joint's transform at every frame, yet most of it is implied by the body rather than by what the motion is about. Compression is one way…
- arXiv cs.AIresearchFTD-GNO: Memory-Efficient Graph Neural Operators through Functional Tensor Decomposition of the Kernel
arXiv:2610.04212v1 Announce Type: cross Abstract: Graph Neural Operators (GNOs) provide flexible surrogate models for learning solution operators of partial differential equations (PDEs). However, standard GNOs typically…
- arXiv cs.AIresearchAttention-Based Surface Representation Learning for Robot State Prediction and Open-Ended Surface Classification
arXiv:2610.04240v1 Announce Type: cross Abstract: For ground robots operating in outdoor environments, understanding the properties of the underlying terrain is essential for ensuring reliable operation. In most percepti…
- arXiv cs.AIresearchAI-Enabled Quality Assurance for Multiple-Choice Assessment Items
arXiv:2610.04267v1 Announce Type: cross Abstract: Generating multiple-choice questions is increasingly scalable, but establishing their assessment quality remains difficult. We present a focused narrative review of autom…
- arXiv cs.AIresearchRethinking Self-Distillation for Multi-Teacher Capability Merging
arXiv:2610.04272v1 Announce Type: cross Abstract: Combining capabilities of multiple expert models trained starting from the same base checkpoint has become increasingly common in frontier language-model post-training. R…
- arXiv cs.AIresearchFirst-Order Steering: Translating Weight Adaptation into Activation Steering
arXiv:2610.04283v1 Announce Type: cross Abstract: Activation steering exploits interpretable directions in the residual stream to enable inference-time manipulation of model behavior. Composing steering vectors to apply…
- arXiv cs.AIresearchCyTReX: Explainable AI-Based Cybersecurity Threat Reasoning Framework for DER Networks
arXiv:2610.04286v1 Announce Type: cross Abstract: Distributed Energy Resource (DER) environments rely on network communication protocols to coordinate control commands, measurements, and device states across edge assets…
- arXiv cs.AIresearchScaling of Wireless Foundation Models via Representation Diversity and Multi-Branch Architectures
arXiv:2610.04289v1 Announce Type: cross Abstract: Wireless foundation models learn representations from unlabeled radio signals for reuse across downstream tasks. Scaling model capacity is a common strategy for learning…
- arXiv cs.AIresearchRRM-GPT: A Framework and Vision for Radio Resource Management Foundation Models
arXiv:2610.04296v2 Announce Type: replace-cross Abstract: Learning-based models for radio resource management (RRM) are typically built for a single function and deployment, so each new setting repeats the development pi…
- arXiv cs.AIresearchQuestioning the Questions: Sustaining Self-Evolution in Reasoning Models
arXiv:2610.04299v2 Announce Type: replace-cross Abstract: Self-evolving reasoning models learn from their own generated questions, yet repeated self-training can lead to performance collapse. In this paper, we investigat…
- arXiv cs.AIresearchWhat to Preserve in Recursive Computation: A Local Predictive Sufficiency Principle
arXiv:2610.04303v1 Announce Type: cross Abstract: Recursive computation repeatedly compresses or reuses intermediate states, creating a simple tension: information that must remain useful across longer recursive paths is…
- arXiv cs.AIresearchGrayShield: Bit-Level Sanitization for Transformer Model Supply-Chain Security
arXiv:2610.04319v1 Announce Type: cross Abstract: Transformer models such as BERT and Vision Transformer~(ViT) achieve strong performance via densely parameterized attention backbones. However, the least significant bits…
- arXiv cs.AIresearchSystem One Models for Wireless Decision-Making:Applications and Performance Evaluation
arXiv:2610.04345v1 Announce Type: cross Abstract: Many wireless control tasks require repeated selection of a single action from a finite feasible set under stringent latency and reliability constraints. While large lang…
- arXiv cs.AIresearchA Bird's-Eye View of Iterative Reward Design
arXiv:2610.04364v1 Announce Type: cross Abstract: Designing effective reward functions in RL typically requires substantial expertise and trial and error. Recent work automates this process with LLM-based systems that ge…
- arXiv cs.AIresearchGlitchPatch: Repairing Glitch Tokens in Frozen Language Models via Local Retokenization
arXiv:2610.04399v1 Announce Type: cross Abstract: Glitch tokens are anomalous vocabulary entries that can cause large language models (LLMs) to produce outputs inconsistent with their inputs. Existing repair methods requ…
- arXiv cs.AIresearchXTurnix: Large-Scale Self-Supervised Turn Control through Two-State Binary Decisions
arXiv:2610.04400v1 Announce Type: cross Abstract: General turn-taking behavior in real-time dialogue systems requires deciding whether to keep listening or start responding while listening, and whether to continue or sto…
- arXiv cs.AIresearchSpecific Algorithmic Interpretability of Neural Networks: A Case Study on Textures
arXiv:2610.04413v1 Announce Type: cross Abstract: We develop a principled framework for constructing neural networks whose specific parameter realizations admit an explicit algorithmic interpretation. Existing algorithm-…
- arXiv cs.AIresearchMaDeL: Manifold-Decomposed Feature Losses for Generative Modeling
arXiv:2610.04419v1 Announce Type: cross Abstract: Generative models are often trained with isotropic objectives such as mean-squared error. For data concentrated near a low-dimensional manifold, however, such losses conf…
- arXiv cs.AIresearchAgroGround: Multi-Granularity Grounded Recognition in Agriculture
arXiv:2610.04425v2 Announce Type: replace-cross Abstract: Agricultural visual models are typically evaluated for either recognition or localization, but reliable diagnosis requires identifying what is present and localiz…
- arXiv cs.AIresearchCOSMOS: Soft Mechanism Mixtures with Verifiable Routing for Long-Horizon PDE Forecasting
arXiv:2610.04427v1 Announce Type: cross Abstract: Neural operators offer an efficient alternative to classical PDE solvers, but most learn a monolithic map per equation family and discretization. Real systems are composi…
- arXiv cs.AIresearchGuess My Weight: Profiled Side-Channel Recovery of Floating-Point Neural-Network Weights
arXiv:2610.04436v1 Announce Type: cross Abstract: Neural-network parameters deployed on embedded devices may be exposed through physical side-channel leakage during inference. Existing side-channel attacks on floating-po…
- arXiv cs.AIresearchTarget-free Latent Safety Alignment
arXiv:2610.04467v1 Announce Type: cross Abstract: Large language models (LLMs) remain highly vulnerable to jailbreak attacks that induce harmful behaviors and circumvent safety alignment. To defend against such attacks,…
- arXiv cs.AIresearchUnderstanding Clustering in Slot Attention via Particle Dynamics
arXiv:2610.04493v1 Announce Type: cross Abstract: Studying attention through the lens of interacting particle dynamics has shown how token clustering can emerge from the underlying dynamics. We extend this perspective to…
- arXiv cs.AIresearchLocalization Lens for Improving Medical Vision-Language Models
arXiv:2610.04502v1 Announce Type: cross Abstract: Medical Vision-Language Models (Med-VLMs) have demonstrated strong capabilities in clinical tasks. However, they often struggle to understand anatomical structures and sp…
- arXiv cs.AIresearchEgoExo-Next:Benchmarking Vision-Language Models on Visual-Option Next-State and Cross-View Reasoning
arXiv:2610.04506v1 Announce Type: cross Abstract: Vision-language models (VLMs) are increasingly evaluated for egocentric and cross-view video reasoning, yet existing benchmarks largely focus on semantic event understand…
- arXiv cs.AIresearchDiffusion-Based Stress Testing of Overload Monitoring for Resilient Emergency Cellular Networks Using Internet CDR Proxies
arXiv:2610.04526v1 Announce Type: cross Abstract: Disasters can overload cellular control-plane signaling within minutes, yet fine-grained Radio Resource Control (RRC) or Next Generation (NG) Application Protocol (NGAP)…
- arXiv cs.AIresearchWeight Decay and Neuron Condensation: A Three-Stage Analysis of Two-Layer ReLU Networks
arXiv:2610.04533v1 Announce Type: cross Abstract: Weight decay is widely used as a regularization technique in neural network training, yet its role in neuron condensation (parameter direction alignment) remains unclear.…
- arXiv cs.AIresearchCross-Modal Solar Image Synthesis: Adapting the Surya Foundation Model from He I 10830 {\AA} to EUV Translation and Coronal Hole Segmentation
arXiv:2610.04553v1 Announce Type: cross Abstract: The long observational record of He I 10830 {\AA} offers a means to investigate solar morphology before modern extreme-ultraviolet (EUV) imaging. We adapt the Surya solar…
- arXiv cs.AIresearchCoupling Noisy Pairwise Knowledge to the DAG Posterior for Causal Discovery
arXiv:2610.04559v1 Announce Type: cross Abstract: External causal reports can improve structure learning from limited observations, but their reliability varies across sources and variable pairs. We introduce HB-NoisyKG,…
- arXiv cs.AIresearchOnly Project Once: Projection-Adaptive Loss for Exact Constraint Satisfaction
arXiv:2610.04572v1 Announce Type: cross Abstract: Precise constraint satisfaction is a prerequisite to deploying learned models in many areas, motivating methods that repair raw neural predictions with a repair procedure…
- arXiv cs.AIresearchVariational Quantum Attention for Molecular Graph Learning
arXiv:2610.04588v1 Announce Type: cross Abstract: Molecular property prediction is central to computational drug discovery, where graph neural networks learn to weight neighboring atomic environments during message passi…
- arXiv cs.AIresearchConEx: Human-Interpretable Saliency Maps via Concept-Aware Attribution
arXiv:2610.04605v1 Announce Type: cross Abstract: Many visual explanation methods in computer vision highlight pixel importance but struggle to link these low-level cues to semantically meaningful concepts, limiting thei…
- arXiv cs.AIresearchPolicy as Data: Replay-Based Policy Dual Averaging via Advantage Regression
arXiv:2610.04638v1 Announce Type: cross Abstract: Actor-critic methods reuse past experience to improve sample efficiency. However, historical data are typically regarded as off-policy samples for the current policy-impr…
- arXiv cs.AIresearchGS-Codec: A Gaussian-Splatting Bottleneck for Neural Audio Coding
arXiv:2610.04651v1 Announce Type: cross Abstract: Neural audio codecs compress waveforms into compact discrete tokens that underpin speech language models, real-time communication, and large-scale audio storage. Almost e…
- arXiv cs.AIresearchExtracting Persona Subspaces Through Iterative Nullspace Projection For Modulation
arXiv:2610.04676v1 Announce Type: cross Abstract: Large Language Models (LLMs) can adopt distinct personas to tune their semantics, expertise, and perspective to different users and tasks. Precise control over these trai…
- arXiv cs.AIresearchNeurodiversity-Aware Multimodal Affective Computing for Neurodevelopmental Assessment: From Norm-Referenced Classification to Context-Sensitive Decision Support
arXiv:2610.04705v1 Announce Type: cross Abstract: Automated neurodevelopmental assessment increasingly combines computer vision, speech, eye tracking, physiology, and machine learning, yet multimodality and discriminatio…
- arXiv cs.AIresearchKnossos and Ariadne: Benchmarking and Learning Complete Diagram Topology Extraction with Vision-Language Models
arXiv:2610.04721v1 Announce Type: cross Abstract: Structural diagrams are widely used to represent complex systems and relational information across scientific, engineering, procedural, and spatial domains. Recent vision…
- arXiv cs.AIresearchRobot Learning with Visual Predicted Force
arXiv:2610.04741v2 Announce Type: replace-cross Abstract: Force-aware manipulation typically relies on specialized force or tactile sensors. We show that force-aware manipulation can instead be achieved through visual fo…
- arXiv cs.AIresearchMore Value per Key: Asymmetric Sparse Attention for Faster LLM Decoding
arXiv:2610.04753v2 Announce Type: replace-cross Abstract: Autoregressive generation in Large Language Models (LLMs) is constrained by the memory and computational demands of attention mechanisms. Sparse attention methods…
- arXiv cs.AIresearchEasyClassifier: Honest, Reproducible Machine-Learning Classification for Researchers Who Do Not Program
arXiv:2610.04758v1 Announce Type: cross Abstract: Machine-learning classification is now used across medicine, the social sciences, economics, education and engineering, very often by researchers who do not program. Two…
- arXiv cs.AIresearchActive-DiNTS: Active Differentiable Network Topology Search
arXiv:2610.04787v1 Announce Type: cross Abstract: Neural Architecture Search (NAS) has proved to be a strong alternative to manual network design, but applying it to 3D medical image segmentation is limited by two well-k…
- arXiv cs.AIresearchCluster Validation Indices as Self-Supervised Objectives for Text Representation Learning
arXiv:2610.04830v1 Announce Type: cross Abstract: Self-supervised fine-tuning refines the embedding space of a pretrained language encoder without labels. However, the commonly used approaches are computationally expensi…
- arXiv cs.AIresearchPIT-GCL: Protein Interaction using Topological Graph Contrastive Learning
arXiv:2610.04850v3 Announce Type: replace-cross Abstract: Protein binding prediction is central to target identification, therapeutic binder design, and large scale screening, yet remains challenging because binding depe…
- arXiv cs.AIresearchInvisible Ink, Visible Lies: How Production Watermarking Causes LLMs to Hallucinate
arXiv:2610.04860v1 Announce Type: cross Abstract: Text watermarking helps identify AI-generated content, but its effect on factual reliability remains underexplored. In this paper, we study watermarking hallucination: fa…
- arXiv cs.AIresearchEnhancing Long-Video VLM Embeddings with Query-Aware Streaming Latent Reasoning
arXiv:2610.04864v1 Announce Type: cross Abstract: Long-video embedding requires capturing sparse query-relevant evidence under a limited visual-token budget. Uniform sampling can miss brief events in videos spanning minu…
- arXiv cs.AIresearchGreedy Local Learning for Language Model Pretraining: Gaps and Objective Design
arXiv:2610.04867v2 Announce Type: replace-cross Abstract: Greedy block-wise local learning splits a network into gradient-isolated blocks trained by local auxiliary losses, deleting the backward pass between blocks: inte…
- arXiv cs.AIresearchResOPD: Tail Residualization for Sparse On-Policy Distillation
arXiv:2610.04882v1 Announce Type: cross Abstract: On-policy distillation (OPD) trains a student model on self-generated trajectories, but transmitting dense teacher distributions across long reasoning traces creates proh…
- arXiv cs.AIresearchSFlexRCA: Lightweight, Scalable, and Flexible Root Cause Analysis for IIoT Edge Systems
arXiv:2610.04893v1 Announce Type: cross Abstract: Industrial Internet of Things (IIoT) systems generate high-dimensional sensor telemetry from interconnected components, where faults can propagate across the system. To a…