AI news archive.
19,861 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchCan synthetic data reproduce real-world findings in epidemiology? A replication study using adversarial random forests
arXiv:2508.14936v4 Announce Type: replace-cross Abstract: Synthetic data hold substantial potential to address practical challenges in epidemiology due to restricted data access and privacy concerns. However, many curren…
- arXiv cs.AIresearchHyperdimensional Probe: Decoding LLM Representations via Vector Symbolic Architectures
arXiv:2509.25045v4 Announce Type: replace-cross Abstract: Despite their capabilities, Large Language Models (LLMs) remain opaque with limited understanding of their internal representations. Current interpretability meth…
- arXiv cs.AIresearchAFFORD2ACT: How Far Can Sparse Keypoints Go for Robot Manipulation?
arXiv:2510.01433v3 Announce Type: replace-cross Abstract: Vision-based manipulation policies are commonly learned from rich visual observations, typically using dense visual features extracted from full resolution images…
- arXiv cs.AIresearchProtecting De-identified Documents from Search-based Linkage Attacks
arXiv:2510.06383v3 Announce Type: replace-cross Abstract: While de-identification models can help conceal the identity of the individuals mentioned in a document, they fail to address linkage risks, defined as the potent…
- arXiv cs.AIresearchSculpting the Latent Space: Disentanglement with WAE-MMD and Programmable Priors
arXiv:2510.11953v2 Announce Type: replace-cross Abstract: Learning disentangled representations, where semantic features are independently captured in a latent space, is dominated by Variational Auto Encoders (VAE) and A…
- arXiv cs.AIresearchStructured Temporal Causality for Interpretable Multivariate Time Series Anomaly Detection
arXiv:2510.16511v2 Announce Type: replace-cross Abstract: Real-world multivariate time series anomalies are rare and often unlabeled. Additionally, prevailing methods rely on increasingly complex architectures tuned to b…
- arXiv cs.AIresearchAlign, Don't Blend: Orthogonal Supervision Disentanglement As the Key to Generalizable AI-Generated Image Detection
arXiv:2512.06746v3 Announce Type: replace-cross Abstract: Recent advances in AI-Generated Image (AIGI) detection have largely focused on model architectures, loss design, and training strategies, while overlooking a more…
- arXiv cs.AIresearchAlgorithmic Reflectivity in Large Language Models: Methodological Study of Linguistic Structure in Mentalization
arXiv:2512.08945v2 Announce Type: replace-cross Abstract: Mentalization is a core human capacity involving the interpretation of one's own and others' behavior in terms of underlying mental states. Large language models…
- arXiv cs.AIresearchEvolutionary BP+OSD Decoding for Low-Latency Quantum Error Correction
arXiv:2512.18273v3 Announce Type: replace-cross Abstract: Quantum error correction (QEC) for fault-tolerant quantum computing requires a balanced decoding solution that offers high performance, low complexity, and low la…
- arXiv cs.AIresearchRubRIX: Rubric-Driven Risk Mitigation in Caregiver-AI Interactions
arXiv:2601.13235v2 Announce Type: replace-cross Abstract: Caregivers seeking AI-mediated support express complex needs---information-seeking, emotional validation, and distress cues---that warrant careful evaluation of r…
- arXiv cs.AIresearchDisentangling generalization and memorization in large language models using chess
arXiv:2601.16823v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) exhibit remarkable capabilities, yet it remains unclear to what extent these reflect sophisticated recall or genuine reasoning abilit…
- arXiv cs.AIagentsDoes Centralized Learning Help Embodied Agents Coordinate, and When Can a Tabular Study Tell?
arXiv:2601.17454v3 Announce Type: replace-cross Abstract: Tabular studies are a common way to compare independent and centralized multi-agent learners, because they avoid function approximation. A natural expectation is…
- arXiv cs.AIresearchFrom Fuzzy to Exact: The Halo Architecture for Infinite-Depth Reasoning via Rational Arithmetic
arXiv:2601.18702v5 Announce Type: replace-cross Abstract: The prevailing scaling paradigm of Large Language Models (LLMs) rests on a substrate of "Fuzzy" floating-point arithmetic. To mitigate the inherent instability of…
- arXiv cs.AIresearchControlling Output Rankings in LLM-Based Search via Generative Engine Optimization
arXiv:2602.03608v2 Announce Type: replace-cross Abstract: The way customers search for and choose products is changing with the rise of large language models (LLMs). LLM-based search, or generative engines, provides dire…
- arXiv cs.AIresearchHealthMamba: An Uncertainty-aware Spatiotemporal Graph State Space Model for Effective and Reliable Healthcare Facility Visit Prediction
arXiv:2602.05286v4 Announce Type: replace-cross Abstract: Healthcare facility visit prediction is essential for optimizing healthcare resource allocation and informing public health policy. Despite advanced machine learn…
- arXiv cs.AIagentsRuleSmith: Multi-Agent LLMs for Automated Game Balancing
arXiv:2602.06232v2 Announce Type: replace-cross Abstract: Game balancing is a longstanding challenge requiring repeated playtesting, expert intuition, and extensive manual tuning. We introduce RuleSmith, a framework that…
- arXiv cs.AIresearchAnalyzing and Improving Chain-of-Thought Monitorability Through Information Theory
arXiv:2602.18297v2 Announce Type: replace-cross Abstract: Chain-of-thought (CoT) monitors are LLM-based systems that analyze reasoning traces to detect when outputs may exhibit attributes of interest, such as test-hackin…
- arXiv cs.AIresearchData-Free Finite-Volume Convolutional Neural Networks for Steady Compressible Euler Flow around a Circular Cylinder
arXiv:2603.01001v2 Announce Type: replace-cross Abstract: A data-free finite-volume convolutional neural network (FV-CNN) is formulated for steady Euler flow around a cylinder at eight Mach numbers, 2--15. Shared-face fl…
- arXiv cs.AIresearchStructLens: A Structural Lens for Language Models via Maximum Spanning Trees
arXiv:2603.03328v3 Announce Type: replace-cross Abstract: Language exhibits inherent structures, a property that explains both language acquisition and language change. Given this characteristic, we expect language model…
- arXiv cs.AIresearchMICA: Multi-granularity Intertemporal Credit Assignment for Long-Horizon Emotional Support Dialogue
arXiv:2603.06194v4 Announce Type: replace-cross Abstract: Reinforcement learning (RL) for large language models (LLMs) has shown strong performance in single-turn tasks, but extending it to multi-turn interaction remains…
- arXiv cs.AIresearchSYNAPSE: Framework for Neuron Analysis and Perturbation in Sequence Encoding
arXiv:2603.08424v2 Announce Type: replace-cross Abstract: In recent years, Artificial Intelligence has become a powerful partner for complex tasks such as data analysis, prediction, and problem-solving, yet its lack of t…
- arXiv cs.AIresearchMCLR: Improving Conditional Modeling via Inter-Class Likelihood-Ratio Maximization and Unifying Classifier-Free Guidance with Alignment Objectives
arXiv:2603.22364v4 Announce Type: replace-cross Abstract: Diffusion models achieve strong generative performance but often rely on classifier-free guidance (CFG), an inference-time intervention that modifies the sampling…
- arXiv cs.AIresearchThe Stepwise Informativeness Assumption: When Do Entropy Dynamics Track Reasoning Correctness in LLMs?
arXiv:2604.06192v2 Announce Type: replace-cross Abstract: Recent work uses entropy-based signals at multiple representation levels to study reasoning in large language models, but the field remains largely empirical. Fro…
- arXiv cs.AIresearchGeneralization and Scaling Laws for Mixture-of-Experts Transformers
arXiv:2604.09175v2 Announce Type: replace-cross Abstract: We develop a theory of generalization and scaling for Mixture-of-Experts (MoE) Transformers that cleanly separates \emph{active} per-input capacity from routing c…
- arXiv cs.AIresearchIt Takes a Forum: Resources & Stakeholders Sustaining the Online Synthetic Non-Consensual Intimate Image Creation Ecosystem
arXiv:2604.12190v2 Announce Type: replace-cross Abstract: Many malicious actors responsible for disseminating synthetic non-consensual intimate imagery (SNCII) operate within internet forums to exchange resources, strate…
- arXiv cs.AIresearchOn the Expressive Power and Limitations of Multi-Layer SSMs
arXiv:2604.14501v3 Announce Type: replace-cross Abstract: We study how depth, finite precision, state dimension, and chain-of-thought (CoT) affect the expressive power of multi-layer state-space models (SSMs). For the ex…
- arXiv cs.AIresearchFine-Tuning Small Reasoning Models for Quantum Field Theory
arXiv:2604.18936v2 Announce Type: replace-cross Abstract: Despite the growing application of large language models (LLMs) to theoretical physics, there has been little academic exploration of how domain-specific physics…
- arXiv cs.AIresearchOn the Complementarity of Quantum and Classical Features: Adaptive Hybrid Quantum-Classical Feature Fusion for Breast Cancer Classification
arXiv:2604.22903v2 Announce Type: replace-cross Abstract: The integration of quantum machine learning with classical deep learning offers promising avenues for medical image analysis by mapping data into high-dimensional…
- arXiv cs.AIagentsSUDP: Secret-Use Delegation Protocol for Agentic Systems
arXiv:2604.24920v4 Announce Type: replace-cross Abstract: Agentic systems now act with user secrets for APIs, messaging platforms, and cloud services. Today's agent runtimes typically implement authorization by exposure:…
- arXiv cs.AIresearchProMORNA: An End-to-End Generative Framework for Full-Length mRNA Design
arXiv:2605.01513v2 Announce Type: replace-cross Abstract: Designing therapeutic messenger RNA (mRNA) requires generating full-length transcripts that optimally balance intracellular stability and translation efficiency.…
- arXiv cs.AIresearchDooly: Configuration-Agnostic, Redundancy-Aware Profiling for LLM Inference Simulation
arXiv:2605.07985v3 Announce Type: replace-cross Abstract: Selecting the optimal LLM inference configuration requires evaluation across hardware, serving engines, attention backends, and model architectures, since no sing…
- arXiv cs.AIresearchPath-Coupled Bellman Flows for Distributional Reinforcement Learning
arXiv:2605.08253v3 Announce Type: replace-cross Abstract: Distributional reinforcement learning (DRL) models the full return distribution, but existing finite-support or quantile-based methods rely on projections, while…
- arXiv cs.AIagentsDeep Reasoning in General Purpose Agents via Structured Meta-Cognition
arXiv:2605.11388v3 Announce Type: replace-cross Abstract: Humans intuitively solve complex problems by flexibly shifting among reasoning modes: they plan, execute, revise intermediate goals, resolve ambiguity through ass…
- arXiv cs.AIagentsBiological Context Does Not Reliably Improve LLM-Guided Experimental Optimization
arXiv:2605.15341v2 Announce Type: replace-cross Abstract: Autonomous labs increasingly deploy large language models (LLMs) as closedloop biology optimizers that propose a design, read the outcome, then propose again. Thi…
- arXiv cs.AIresearchFeedback World Model Enables Precise Guidance of Diffusion Policy
arXiv:2605.15705v2 Announce Type: replace-cross Abstract: World models aim to improve robotic decision making by predicting the consequences of actions. However, in practice, their predictions often become unreliable onc…
- arXiv cs.AIresearchCAVE: A Structured Credit Assignment Approach for Fragmented Visual Evidence Reasoning
arXiv:2605.16416v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) have achieved strong performance on general multimodal reasoning, yet remain challenged in integrating nonlocal visual information t…
- arXiv cs.AIresearchDualView: Adaptive Local-Global Fusion for Multi-Hop Document Reranking
arXiv:2605.18767v2 Announce Type: replace-cross Abstract: Multi-hop question answering requires aggregating information from multiple documents, a critical capability for knowledge-intensive applications. A fundamental c…
- arXiv cs.AIresearchLearning Altruistic Collaboration in Heterogeneous Multi-Team Systems
arXiv:2605.21723v2 Announce Type: replace-cross Abstract: This paper studies heterogeneous multi-team collaboration through dynamic robot allocation, where the robots themselves are treated as transferable resources. Lev…
- arXiv cs.AIresearchFrom Theory to Decision Rule: Calibrating the Noisy-Label Crossover for Vision-Language Model Weak Supervision Across Three Medical-Imaging Benchmarks
arXiv:2605.24771v2 Announce Type: replace-cross Abstract: In medical imaging, small sets of expert labels are often combined with zero-shot pseudo-labels from a vision-language model (VLM). When the expert-labeled set is…
- arXiv cs.AIresearchMetropolis-Scale Resilient and Trustworthy Traffic Flow Inference Using Multi-Source Data
arXiv:2605.25004v2 Announce Type: replace-cross Abstract: Inferring network-wide traffic states from sparse observations with high accuracy and trustworthy uncertainty quantification is essential for intelligent transpor…
- arXiv cs.AIresearchInfoQuant: Shaping Activation Distributions for Low-Bit LLM Quantization
arXiv:2605.26175v2 Announce Type: replace-cross Abstract: Low-bit activation quantization remains a major bottleneck in efficient large language model (LLM) deployment. The difficulty is not only that activations contain…
- arXiv cs.AIresearchLet It Be Simple: One-Step Action Generation for Vision-Language-Action Models
arXiv:2606.05737v3 Announce Type: replace-cross Abstract: One-step generation from standard diffusion or Flow-Matching training is rarely effective for text-to-image or video generation without distillation or specialize…
- arXiv cs.AIagentsClosing the Sim-to-Real Gap: An Evaluation Framework for Autonomous Cyber Defense Configuration of Commercial EDR
arXiv:2606.08168v2 Announce Type: replace-cross Abstract: Leading commercial endpoint detection and response (EDR) products have shifted from operator-configured rule sets to multi-component systems where autonomous AI c…
- arXiv cs.AIresearchEHRNote-ChatQA: A Benchmark for Evidence-Grounded Multi-Turn Clinical Question Answering over Longitudinal Discharge Summaries
arXiv:2606.15735v4 Announce Type: replace-cross Abstract: Discharge summaries are crucial clinical documents containing the context of a patient's overall hospital stay, and are routinely reviewed by medical experts for…
- arXiv cs.AIresearchLatent Bridges for Multi-Table Question Answering
arXiv:2606.28916v3 Announce Type: replace-cross Abstract: We introduce GRAB, a constructor-encoder-bridge pipeline for table question answering. Our method lifts relational data into an heterogeneous graph, encodes it vi…
- arXiv cs.AIresearchMixture-of-Control: State-Aware Fine-Tuning for Transformer-based Models
arXiv:2606.31397v2 Announce Type: replace-cross Abstract: State-based fine-tuning has emerged as a compelling alternative to weight-based adaptation for transformers, updating lightweight controls into states rather than…
- arXiv cs.AIagentsASPIRE: Agentic /Skills Discovery for Robotics
arXiv:2607.00272v2 Announce Type: replace-cross Abstract: Traditional robot programming is notoriously challenging: it requires orchestrating multimodal perception, managing physical contact dynamics, and handling divers…
- arXiv cs.AIresearchTo Retain or to Adapt? Generalizing Continual Learning
arXiv:2607.05609v2 Announce Type: replace-cross Abstract: The Continual Learning (CL) literature has long been driven by the goal of mitigating catastrophic forgetting. This objective rests on an often unstated assumptio…
- arXiv cs.AIresearchConditional Optimal Bridge for Riemannian Activation Steering
arXiv:2607.10517v2 Announce Type: replace-cross Abstract: Activation steering offers a lightweight alternative to fine-tuning for controlling large language models at inference time. Many existing steering methods implic…
- arXiv cs.AIresearchFlout at Your Own Risk: LLMs Struggle with Pragmatic Cooperativity Under Epistemic Asymmetry
arXiv:2607.11053v2 Announce Type: replace-cross Abstract: Fruitful collaborations require effective communication of privately-held information. The increasing use of LLMs as "collaborators" raises questions about the ex…