AI news archive.
10,659 articles filed under Research, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchPrediction Is Not Calibration: Item Parameter Recovery and Representation Coupling in Knowledge Tracing
arXiv:2610.30211v1 Announce Type: cross Abstract: Knowledge tracing (KT) models can estimate item parameters through an item response decoder trained solely for next-response prediction, yet predictive accuracy does not…
- arXiv cs.AIresearchWhen Reconstruction Is Not Enough: Doubly Robust Counterfactual and Interventional Mediation Analysis with Learned Multimodal Representations
arXiv:2610.30220v1 Announce Type: cross Abstract: Learned representations of high-dimensional multimodal health records are increasingly used to adjust for confounding, yet they are usually trained to reconstruct the dat…
- arXiv cs.AIresearchAutomated screening of privacy risks in medical AI
arXiv:2610.30229v1 Announce Type: cross Abstract: Medical artificial intelligence (AI) models are often shared without their training data, assuming this protects the patients who contributed them. However, a model can r…
- arXiv cs.AIresearchEdit, Don't Imitate: Minimal-Edit On-Policy Distillation for Multimodal Reasoning
arXiv:2610.30231v1 Announce Type: cross Abstract: Visual mathematical reasoning can fail before reasoning begins: when a vision-language model (VLM) misreads a diagram, subsequent reasoning proceeds from false premises.…
- arXiv cs.AIresearchGeneralizing Metropolis-Hastings for DAG Sampling
arXiv:2610.30291v1 Announce Type: cross Abstract: A fundamental challenge in Bayesian network structure learning lies in efficiently approximating the posterior distribution of directed acyclic graphs (DAGs). For large,…
- arXiv cs.AIresearchGender, Sexual Orientation, and the One-Year Refugee Bar: A Computational Study of Bill C-12 and Canadian Refugee Adjudication
arXiv:2610.30297v1 Announce Type: cross Abstract: In March 2026, Bill C-12 amended the Immigration and Refugee Protection Act to make refugee claims ineligible for referral to the Refugee Protection Division where they a…
- arXiv cs.AIresearchMPBRS: Multi-Potential-Based Reward Shaping for Unified Reward Configuration in Humanoid Locomotion
arXiv:2610.30334v1 Announce Type: cross Abstract: Designing and tuning reward functions remains one of the main challenges in building effective reinforcement learning (RL) pipelines for humanoid locomotion. While shapin…
- arXiv cs.AIresearchConsistency Is Not Validity: Self-Rewarded Moral Argumentation Makes Language Models Decisive but Pliable
arXiv:2610.30349v1 Announce Type: cross Abstract: LLMs are increasingly consulted for moral judgment. We aim to improve performance on such tasks by rewarding good arguments, on the premise that arguing well increases th…
- arXiv cs.AIresearchProbing and Steering for Safety-Relevant Behaviours in Large Language Models
arXiv:2610.30363v1 Announce Type: cross Abstract: Activation probes are computed directions in a language model's residual stream, used both to detect safety-relevant behaviours and, by adding their direction back into t…
- arXiv cs.AIresearchAcoustiPrint: Physics-Guided Neural Design of Manufacturable Acoustic Structures
arXiv:2610.30411v1 Announce Type: cross Abstract: Recent work in additive manufacturing and neural inverse design enables the creation of complex three-dimensional structures to manipulate physical fields, yet these desi…
- arXiv cs.AIresearchHigh-Value Training Data from Noisy, Diverse Sources
arXiv:2610.30421v1 Announce Type: cross Abstract: Training state-of-the-art models increasingly requires learning from large, heterogeneous datasets whose examples vary in quality, domain relevance, and source of supervi…
- arXiv cs.AIresearchaggmetrics: Aggregating Classification Performance Measures for Machine Learning
arXiv:2610.30456v1 Announce Type: cross Abstract: aggmetrics is a Python package that extends any binary performance measure expressed in the four confusion-matrix counts to multiclass, multilabel, ordinal, cost-sensitiv…
- arXiv cs.AIresearchShort-to-Long: Detached Features for Long-Horizon Value Learning
arXiv:2610.30461v1 Announce Type: cross Abstract: Learning useful representations from continually changing value targets remains a challenge in deep reinforcement learning. We study the temporal horizon of this supervis…
- arXiv cs.AIresearchRethinking SAE Evaluation: An Atomic Interpretable Unit Framework Reveals Hidden Polysemanticity and Redundancy
arXiv:2610.30474v2 Announce Type: replace-cross Abstract: Sparse autoencoders (SAEs) were originally motivated by discovering monosemantic features, a property that characterizes individual features but does not specify…
- arXiv cs.AIresearchPhysibleMDM: Enforcing Inference-Time Physical Feasibility Constraints on Motion Diffusion Models via Noise Optimization
arXiv:2610.30500v1 Announce Type: cross Abstract: Motion Diffusion Models (MDMs) can generate diverse and visually appealing human motion; yet, the resulting trajectories frequently violate physical constraints, limiting…
- arXiv cs.AIresearchBehind Aggregate Scores: What Systematically Varying Arena-Hard's LLM Judge Reveals
arXiv:2610.30512v1 Announce Type: cross Abstract: LLM judges are used to determine which of two answers is better. Trusting these verdicts requires knowing how repeatable they are and how much they depend on the judge's…
- arXiv cs.AIresearchProtegrity-PII Technical Report
arXiv:2610.30518v2 Announce Type: replace-cross Abstract: We present Protegrity-PII, a new PII detection model for structured and unstructured text. Protegrity-PII achieves a typed recall of 0.910 with a precision of 0.9…
- arXiv cs.AIresearchLLM2Cert: LLM Synthesis of Certificates with SMT/Lean Verification
arXiv:2610.30524v1 Announce Type: cross Abstract: Lyapunov functions and barrier certificates give state-space guarantees of stability and safety, but synthesizing and verifying them---especially for nonlinear, high-dime…
- arXiv cs.AIresearchBridging the Closed-World Gap: Interpretable Anomaly Detection via a Hybrid TSK-FCM Ensemble on the BETH Dataset
arXiv:2610.30576v1 Announce Type: cross Abstract: A fundamental paradox plagues the deployment of Machine Learning in cybersecurity: supervised models generalize poorly to novel, Out-of-Distribution (OoD) attacks, wherea…
- arXiv cs.AIresearchVisual Grounding First, Multimodal In-context Learning Follows
arXiv:2610.30592v1 Announce Type: cross Abstract: LLMs have shown strong in-context learning (ICL) capability, but extending it to Multimodal LLMs (MLLMs) remains challenging. Prior multimodal ICL methods often rely on I…
- arXiv cs.AIresearchImpacts of generative AI skill development on academic adaptation and learning outcomes among university students
arXiv:2610.30599v1 Announce Type: cross Abstract: Understanding how university students perceive the development of their generative artificial intelligence (GenAI) skills over time can clarify how GenAI use relates to l…
- arXiv cs.AIresearchFuture of Time Series Anomaly Detection: From Historical Review to Unified Outlook
arXiv:2610.30628v1 Announce Type: cross Abstract: Time series anomaly detection (TSAD) is a foundational problem in data mining, aiming to identify observations that deviate significantly from nominal temporal patterns.…
- arXiv cs.AIresearchInterpreting Model Reasoning through Behavioral Counterfactuals
arXiv:2610.30630v1 Announce Type: cross Abstract: Faithfully understanding the internal process that occurs as models form their chain of thought is an important problem with the rise in model capabilities. However, this…
- arXiv cs.AIresearchOne-shot federated unsupervised domain adaptation with Smoothed Knowledge Distillation and teacher refinement
arXiv:2610.30646v1 Announce Type: cross Abstract: Federated unsupervised domain adaptation (FUDA) addresses the challenge of adapting models to an unlabeled target domain using decentralized source domains while preservi…
- arXiv cs.AIresearchSpectral Smoothing and Spiking Perturbations Reconfigure Capability Profiles and Selective Task Performance in Large Language Models
arXiv:2610.30676v1 Announce Type: cross Abstract: Singular-value spectra encode important structure in transformer feed-forward projections, yet their causal role in downstream behavior remains underexplored. We study po…
- arXiv cs.AIresearchFrom Clinical Judgment to Checkable Rules: Clinician-Led Guardrails for Mental-Health Chatbots
arXiv:2610.30690v1 Announce Type: cross Abstract: Large language models (LLMs) deployed in mental-health contexts can be evaluated for safety failures, but the resulting judgments are often difficult to inspect or explai…
- arXiv cs.AIresearchLoRA Superposition across Pretrained Models
arXiv:2610.30691v1 Announce Type: cross Abstract: Low-rank adaptation (LoRA) is usually tied to the pretrained backbone on which it is learned. We ask whether LoRAs trained independently for the same task on different pr…
- arXiv cs.AIresearchULME: Predictive Coupling for Mutually Reinforcing Embedding and Language Modeling
arXiv:2610.30705v1 Announce Type: cross Abstract: Text embedding and text generation are two of the most useful capabilities of modern large language models, yet they are typically provided by separate specialized models…
- arXiv cs.AIresearchMeaning Contracts: Local Semantic Geometry in Large Language Models
arXiv:2610.30715v1 Announce Type: cross Abstract: This paper studies the local geometry of semantic meaning in large language models. Current representation analyses ask whether meanings are close in embedding space, or…
- arXiv cs.AIresearchLearning from Next-Frame Prediction: Towards Unified and Scalable Visual World Modeling
arXiv:2610.30724v2 Announce Type: replace-cross Abstract: Video provides a natural source of supervision: what happens next serves as a learning signal for visual world modeling. Yet masked video pretraining focuses on r…
- arXiv cs.AIresearchVLTest: Finding Joint Image-Text Failures in Vision-Language Models
arXiv:2610.30794v1 Announce Type: cross Abstract: Vision-language models (VLMs) are increasingly embedded in software systems. Testing them raises two problems. Mutating either input can change the expected answer, so an…
- arXiv cs.AIresearchNeural Spectral Capacity with Residual Context for Heterogeneous Resource Allocation within Transformers
arXiv:2610.30823v1 Announce Type: cross Abstract: Predicting relative trained performance from architectural specifications can guide design when training costs limit experimentation. Neural Spectral Capacity (NSC) provi…
- arXiv cs.AIresearchOne Evaluation Is Enough: Inversion-Free Image Editing with Trajectory Correction
arXiv:2610.30827v1 Announce Type: cross Abstract: Real-image editing commonly relies on inversion and iterative sampling, while efficient one-step editors often stabilize a large update by estimating and averaging editin…
- arXiv cs.AIresearchBifurcations from Weight Space: JEPAWG on Parametric Dynamical Systems
arXiv:2610.30847v1 Announce Type: cross Abstract: Trained network weights are increasingly treated as data, but there is rarely ground truth about what a population of models should encode, which hampers systematic valid…
- arXiv cs.AIresearchDirect Forcing: Single-Stage Training with Representation-Space Supervision for Few-Step Autoregressive Video Generation
arXiv:2610.30861v2 Announce Type: replace-cross Abstract: Few-step autoregressive video generation enables low-latency streaming, yet prevailing training pipelines separate causal adaptation from distribution matching. R…
- arXiv cs.AIresearchMOER: Mix-Policy Optimization under Expert Prefix Guidance with Selective Rollback
arXiv:2610.30873v1 Announce Type: cross Abstract: Mix-policy optimization incorporates off-policy expert data into the reinforcement learning (RL) loop to transcend the capability boundary of on-policy RL. However, exist…
- arXiv cs.AIresearchQuery-Time Calibration of CLIP Features for Open-Vocabulary 3D Segmentation
arXiv:2610.30908v1 Announce Type: cross Abstract: Lifting vision-language features such as CLIP into 3D Gaussian reconstructions enables open-vocabulary segmentation through natural-language queries. Although CLIP repres…
- arXiv cs.AIresearchMIG-COW: Transferable Adversarial Attacks on Deepfake Detectors via Gradient Decomposition
arXiv:2610.30914v1 Announce Type: cross Abstract: Despite recent advances, deepfake detectors remain vulnerable to adversarial examples, particularly in diverse, real-world settings. We propose MIG-COW, a novel adversari…
- arXiv cs.AIresearchLow-Latency MoE Inference in Space Data Centers: A Wireless-Power-Transfer Perspective
arXiv:2610.30923v1 Announce Type: cross Abstract: Space data centers (SpaceDCs) are emerging as platforms for large language models (LLMs), supported by continuous solar-energy harvesting and high-speed interconnections.…
- arXiv cs.AIresearchVision Transformers for Estimating Irradiance Using Data Scarce Sky Images
arXiv:2610.30940v1 Announce Type: cross Abstract: Accurate estimation of diffuse horizontal irradiance (DHI) is critical for optimising photovoltaic system performance and energy forecasting yet remains challenging in re…
- arXiv cs.AIresearchGateFormer: Forecast-Space Decomposition for Intra-Hour Solar Irradiance Prediction from Sky Images
arXiv:2610.30942v1 Announce Type: cross Abstract: Sub-hourly dispatch, balancing, and storage control increasingly depend on forecasts that anticipate rapid variability in solar generation. Accurate sky-image-based irrad…
- arXiv cs.AIresearchMetacognitive Scaffolds Create Productive Friction for AI-Assisted Knowledge Work
arXiv:2610.30945v1 Announce Type: cross Abstract: Generative AI imposes new metacognitive demands on knowledge workers as their work shifts from production to planning, evaluation, and orchestration. In a randomized, bet…
- arXiv cs.AIresearchRetiJev: Fast and Source-Grounded Ophthalmic Decision Models
arXiv:2610.30947v1 Announce Type: cross Abstract: Ophthalmic clinical decision support requires fast, accurate, and privacy-preserving inference, yet autoregressive large language models (LLMs) incur substantial latency…
- arXiv cs.AIresearchOpenAttention: One Percent Is Enough with Tail Proxies
arXiv:2610.30951v3 Announce Type: replace-cross Abstract: Sparse attention reads only a small subset of the key-value cache, and how to treat the unread tail remains a key challenge. Discarding the tail biases the output…
- arXiv cs.AIresearchLAST-V2X: Language-Driven Adaptive Scenario Synthesis and Testing for Communication-Induced Failures in V2X Safety Applications
arXiv:2610.30979v1 Announce Type: cross Abstract: Vehicle-to-everything (V2X) communication enables connected vehicles to make safety-critical decisions, but delayed, missing, or incorrect information can compromise driv…
- arXiv cs.AIresearchSecLog-Bench: A Scalable Benchmark for Cybersecurity Log Reasoning with Scaffolded Evidence
arXiv:2610.31000v1 Announce Type: cross Abstract: Large language models (LLMs) have shown strong potential for cybersecurity, leading to growing interest in LLM-based automated cybersecurity log analysis. However, curren…
- arXiv cs.AIresearchMulti-Tool Selection for Robotic Systems: Comparing Semantic Retrieval and LLM
arXiv:2610.31013v1 Announce Type: cross Abstract: Natural-language interfaces allow users to command robotic systems without interacting directly with mission planners or robotics middleware. Their reliable use depends o…
- arXiv cs.AIresearchMostly Reading: What Open-Book Scores Measure in Document-Level LoRA Adapters
arXiv:2610.31017v2 Announce Type: replace-cross Abstract: Single-document LoRA adapters have been proposed as units of knowledge to be merged and retrieved; yet open-book scoring, with the document in the prompt, can cre…
- arXiv cs.AIresearchHarm Is Behavioural, Moderation Is Lexical: How Language and Culture Decide Whom Automated Safety Systems Protect and Whom They Silence
arXiv:2610.31047v1 Announce Type: cross Abstract: Content warning: this paper quotes slurs and hateful statements from published test suites; the racial slur among them is masked. Automated systems decide at scale which…
- arXiv cs.AIresearchMQAScore: Fine-Grained Text-Music Alignment Evaluation via Large Audio Language Model
arXiv:2610.31083v1 Announce Type: cross Abstract: Text-to-music alignment is commonly evaluated by the global similarity between text and audio embeddings, which collapses all described attributes into a single score and…