AI news archive
997 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIagentsREVERSAL-BENCH: A Reversibility Axis and Reset Oracle for Measuring the Reset-Free RL Cliff
arXiv:2609.17745v1 Announce Type: cross Abstract: A central goal of autonomous reinforcement learning is continuous policy training without external resets. However, existing paradigms largely depend on underlying enviro…
- arXiv cs.AIresearchEvolution of US Oral Political Language
arXiv:2609.17755v1 Announce Type: cross Abstract: The analysis of US political language is usually based on the written form (e.g. presidential addresses) or posts broadcasted on various social networks. Oral production,…
- arXiv cs.AIresearchCALOS: Control-Affine Lyapunov On-manifold Safety Layer for Safe Deep Reinforcement Learning for Quadrotors
arXiv:2609.17758v1 Announce Type: cross Abstract: Deep Reinforcement Learning has demonstrated remarkable capability in quadrotor control, yet learned policies offer no guarantee of respecting safety constraints during t…
- arXiv cs.AIresearchIs Luke the Author of a Gospel and the Acts of the Apostles?
arXiv:2609.17762v1 Announce Type: cross Abstract: According to Christian tradition, Luke is credited with authoring a Gospel and the Acts of the Apostles, even if his name does not appear in either book, both originally…
- arXiv cs.AIresearchHINT-Plan: Human Intention-Aware Robot Task Planning in Context-Rich Environments using Vision Language Models
arXiv:2609.17771v1 Announce Type: cross Abstract: Approaches to incorporating human awareness into mobile robot decision-making mainly focus on collision avoidance in low-level motion planning, often overlooking the chal…
- arXiv cs.AIresearchWhen AI Generates Covariates: Causal Typing and Estimand Drift in Sequential Experiments
arXiv:2609.17772v1 Announce Type: cross Abstract: AI-generated covariates from notes, conversations, images, and wearable streams can change the causal question when their roles are left unspecified. A generated feature…
- arXiv cs.AIresearchInformation Set Emulation: Causal Certificates for AI Derived EHR Features
arXiv:2609.17777v1 Announce Type: cross Abstract: AI and large language models can recover clinically meaningful features from electronic health records (EHRs), but predictive usefulness does not establish admissibility…
- arXiv cs.AIresearchAI and Human Approaches to Mathematical Problem Solving
arXiv:2609.17779v1 Announce Type: cross Abstract: AI systems have begun to report solutions, disproofs, and substantive advances on long-standing mathematical problems, raising questions about whether they approach resea…
- arXiv cs.AIresearchSAiFE-gym: Model-based Environments for Automated Market Making with Concentrated Liquidity
arXiv:2609.17788v1 Announce Type: cross Abstract: We present SAiFE_gym, a Python module that provides a collection of simulation environments for studying trading problems in Constant Product Markets (CPMs) with Concentr…
- arXiv cs.AIresearchQiT: Quantum-Inspired Transformer for Visual Recognition Task
arXiv:2609.17789v1 Announce Type: cross Abstract: Quantum machine learning offers a compelling representational perspective: angle-encoded states inhabit Hilbert spaces in which periodic similarities and interactions can…
- arXiv cs.AIresearchPrincipled Koopman Representations with Kalman Inference for Efficient Time-Series Prediction
arXiv:2609.17815v1 Announce Type: cross Abstract: The Koopman operator has been widely used for time-series prediction in dynamical systems. However, prior work that learns latent ``Koopman spaces'' using neural networks…
- arXiv cs.AIresearchThe Free Inference Dimension: Complexity Measure for Zero-Collision Navigation under Hypothesis Mixtures
arXiv:2609.17816v1 Announce Type: cross Abstract: Solomonoff induction frames prediction as a mixture over computable hypotheses, typically leading to identification of the true environment. In a finite meta-reinforcemen…
- arXiv cs.AIagentsReflections on Trusting Trust, Revisited: Contaminating Self-Modifying AI Coding Agents with Poisoned Benchmarks
arXiv:2609.17817v1 Announce Type: cross Abstract: Thompson's "Reflections on Trusting Trust" showed that a compiler can be poisoned to reinsert its own backdoor, so that even recompiling clean source reproduces the Troja…
- arXiv cs.AIresearchLearning Multi-Humanoid Pickup and Transport via Decentralized Object-Centric Control
arXiv:2609.17824v1 Announce Type: cross Abstract: We study cooperative multi-humanoid pickup and transport of objects with varying size, weight, and geometry, requiring robot teams of different sizes. Our approach uses d…
- arXiv cs.AIresearchProcedural Pretraining for Molecular Property Prediction
arXiv:2609.17831v1 Announce Type: cross Abstract: Molecular property prediction is often limited by the small size of labeled downstream datasets, motivating pretraining on large corpora of unlabeled molecules. In this w…
- arXiv cs.AIresearchAdaptive hybrid coupling with operator inference, the overlapping Schwarz alternating method and reinforcement learning
arXiv:2609.17837v1 Announce Type: cross Abstract: Hybrid domain decomposition methods provide a flexible framework for coupling full order models (FOMs) and reduced order models (ROMs), but typically assume the model ass…
- arXiv cs.AIresearchLearning Nuclear Structure with AI: Radii and Collectivity
arXiv:2609.17838v1 Announce Type: cross Abstract: Low-energy nuclear structure is encoded in a broad body of experimental information across the chart of nuclides. Learning how this information is organized across observ…
- arXiv cs.AIagentsLexara-RF: Reference-Free Metrics for Evaluating Conversational Visual Analytics Agents
arXiv:2609.17842v1 Announce Type: cross Abstract: Conversational visual analytics (CVA) agents powered by large language models generate visualizations and natural-language explanations from open-ended queries. Evaluatin…
- arXiv cs.AIresearchRoboVAD: A Large Cross-Domain Evaluation Benchmark for Anomaly Detection in Robotic Arm Manipulation Videos
arXiv:2609.17843v1 Announce Type: cross Abstract: Video anomaly detection (VAD) is an actively studied task, having wide applications in typical scenarios such as public surveillance and road traffic safety. The task is…
- arXiv cs.AIagentsPrimeScientist: Strategic Allocation of Research Effort in Autonomous Research
arXiv:2609.17846v1 Announce Type: cross Abstract: Autonomous research agents aim to automate scientific workflows, from proposing ideas to conducting experiments and analyzing results. Yet current AI and research agents…
- arXiv cs.AIresearchAfriSyCo: Measuring Assertive Framing, Verification, and Wording Sensitivity Around African-Language Content
arXiv:2609.17853v1 Announce Type: cross Abstract: AfriSyCo studies answer switching around African-language factual content with two complementary layers: native-language follow-ups and a controlled cross-language factor…
- arXiv cs.AIresearchWho Judges Matters: Measuring Family-Conditioned Preference in LLM-as-Judge Panels
arXiv:2609.17857v1 Announce Type: cross Abstract: Who the judge is can affect an LLM-as-judge result, but measuring that effect without confusing it with candidate quality is difficult. We study four open-weight families…
- arXiv cs.AIresearchDoes AI Assistance Leave a Temporal Fingerprint? Detecting Overreliance in AI-Assisted Writing and Programming
arXiv:2609.17883v1 Announce Type: cross Abstract: The rapid adoption of generative AI has made final artifacts unreliable evidence of student learning, and AI detectors that examine only the finished product are inaccura…
- arXiv cs.AIresearchWalking the Score Manifold: Continuous-time Generative Dynamics on Learned Data Manifolds
arXiv:2609.17901v1 Announce Type: cross Abstract: Generative modeling of time-dependent data is typically formulated on a discrete temporal grid, restricting supervision to the observed timestamps in the training data. W…
- arXiv cs.AIresearchEDCT-Bench: Uncovering Faithfulness Gaps in VLMs via Explanation-Driven Counterfactual Testing
arXiv:2609.17953v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) can produce Natural Language Explanations (NLEs) that sound plausible yet remain inconsistent with the visual evidence they cite. We present…
- arXiv cs.AIagentsWhom Do AI Agents Work For? Role Assignment Induces Sponsorship Bias in LLM Recommenders
arXiv:2609.17989v1 Announce Type: cross Abstract: Large language models (LLMs) now serve as conversational shopping assistants on platforms that also sell advertising. These AI agents face a conflict of duty. They advise…
- arXiv cs.AIresearchThe Attention Within: Consensus Dynamics in Selective State Space Models
arXiv:2609.17997v1 Announce Type: cross Abstract: Selective state space models (SSMs) have recently emerged as a compelling alternative to transformers, combining competitive performance with substantially improved infer…
- arXiv cs.AIresearchNewer Is Not Fairer: Gender Stereotyping in Text-to-Image AI Across Model Generations
arXiv:2609.18007v1 Announce Type: cross Abstract: Text-to-image generative models are widely used in professional and creative settings, yet how they represent gender across occupations -- and whether newer models are fa…
- arXiv cs.AIresearchPhysics-Informed Neural Networks for Fast Multilayer Spectral Inversion of H{\alpha} 6562.8 A and Ca II 8542.1 A Spectra
arXiv:2609.18025v1 Announce Type: cross Abstract: Strong chromospheric absorption lines such as H$\alpha$ 6562.8 A and Ca II 8542.1 A provide vital diagnostics of plasma dynamics and thermal structure in the solar chromo…
- arXiv cs.AIresearchAn Empirical Evaluation of Cost-Efficient Large Language Models on Algorithmic Programming Tasks
arXiv:2609.18052v1 Announce Type: cross Abstract: This study empirically evaluates whether cost-efficient Large Language Models (LLMs) can be trusted to generate enterprise code to a written specification. Three models (…
- arXiv cs.AIresearchFrom a River in Gilead to the Inference Distributions of Large Language Models: Covert Dialect Bias and Linguistic Profiling at Scale
arXiv:2609.18068v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in high-stakes domains such as housing screening. While alignment techniques mitigate explicit racial bias in gener…
- arXiv cs.AIresearchMask 2D-3D: Adaptive Dual-Masked Autoencoder Network for Image-to-Point Cloud Registration
arXiv:2609.18088v1 Announce Type: cross Abstract: Detection-free methods for image-to-point cloud registration are prone to erroneous correspondences caused by domain and modality discrepancies, limited sensitivity of fe…
- arXiv cs.AIagentsAgora: Git as Shared Memory for Collective AutoResearch
arXiv:2609.18094v1 Announce Type: cross Abstract: Autonomous research loops such as AutoResearch show that one coding agent can improve a training setup unattended. Run several of them and each session starts from scratc…
- arXiv cs.AIresearchLinguistic Triggers of Gender and Racial Bias in Open-Weight LLMs Applied to Recruitment
arXiv:2609.18106v1 Announce Type: cross Abstract: Open-weight large language models are rapidly entering hiring pipelines, yet their discriminatory failure modes -- and the regulatory exposure these create under the EU A…
- arXiv cs.AIagentsA Comprehensive Review of Generative Physical Artificial Intelligence
arXiv:2609.18111v1 Announce Type: cross Abstract: The integration of large-scale foundation models with physical embodiments has led to significant advancements in robotics known as Generative Physical Artificial Intelli…
- arXiv cs.AIagentsPentestChain: A Cost-Aware, MCP-Orchestrated Framework for Automated Penetration Testing with Free-Tier LLMs
arXiv:2609.18120v1 Announce Type: cross Abstract: AI-driven penetration testing has been demonstrated with premium frontier models such as GPT-4, but the per-engagement token cost makes continuous, automated testing unaf…
- arXiv cs.AIresearchRethinking How We Evaluate Methodological Progress in Health AI
arXiv:2609.18134v1 Announce Type: cross Abstract: Methodological progress in artificial intelligence (AI) for electronic health records (EHRs) depends on our ability to determine which algorithms work better, and under w…
- arXiv cs.AIagentsDualSQL: Text-to-SQL with Multi-Agent Reinforcement Learning
arXiv:2609.18135v1 Announce Type: cross Abstract: State-of-the-art Text-to-SQL systems are typically multi-agent pipelines centered around two fundamental tasks: schema linking and SQL generation. However, existing work…
- arXiv cs.AIresearchMoRE: Mixture of Reused Experts
arXiv:2609.18176v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) architectures decouple model capacity from computational cost, yet incur high memory footprints as parameters grow linearly with the number of ex…
- arXiv cs.AIresearchBeyond Accuracy: How Procedural Traces Shift the Decision Criterion of LLM Overseers
arXiv:2609.18204v1 Announce Type: cross Abstract: Organizations increasingly use oversight loops where one large language model (LLM) audits another's outputs alongside procedural traces of claimed steps. A common concer…
- arXiv cs.AIresearchCapMap-MS-TTA: 3rd Place Solution for the MUMU Track of the 8th LSVOS Challenge at ECCV 2026
arXiv:2609.18206v1 Announce Type: cross Abstract: The MUMU track of the 8th Large-scale Video Object Segmentation (LSVOS) Challenge requires a single unified multimodal model to jointly solve image tagging (Task A), open…
- arXiv cs.AIresearchA Lightweight CNN Integrated Compact Convolutional Transformer for Multi-Scale Feature Learning and reducing computational complexity for breast cancer mammography image detection and classification
arXiv:2609.18212v1 Announce Type: cross Abstract: Over the years, Convolutional Neural Networks (CNNs) have demonstrated strong capability in cancer detection and classification using medical images. However, CNN-based m…
- arXiv cs.AIresearchCPR: Combining global composing, local performing and full-sequence refining in piano rendering with continuous autoregressive modelling
arXiv:2609.18216v1 Announce Type: cross Abstract: Prompt-conditioned piano MIDI-to-Music rendering aims to faithfully render target notes while reproducing the timbre of a reference recording. Existing approaches primari…
- arXiv cs.AIresearchAPGEM: Adaptive Policy-Guided Error Mitigation for Quantum Reinforcement Learning on a Real-World CVRP Case Study
arXiv:2609.18219v1 Announce Type: cross Abstract: Quantum Reinforcement Learning (QRL) represents policies as variational quantum circuits (VQCs), making it attractive for combinatorial optimization such as the Capacitat…
- arXiv cs.AIresearchRemembering Solomon Marcus
arXiv:2609.18224v1 Announce Type: cross Abstract: From the manifest of Andre Breton, through the transdisciplinary understanding, we arrive at a post-modern manifest. A talk by Laura De Marco (Harvard) will provide scien…
- arXiv cs.AIresearchQuanta: A Self-Contained Python Library for Hybrid Retrieval over Quantised Embeddings, Lexical Indexes, and Knowledge Graphs
arXiv:2609.18248v1 Announce Type: cross Abstract: An advanced retrieval-augmented generation pipeline is typically assembled from three or four independently operated systems: an approximate nearest-neighbour index, a fu…
- arXiv cs.AIresearch${M}^2$Tok: Multi-head Multi-codebook Discrete Action Tokenization for Vision-Language-Action Models
arXiv:2609.18259v1 Announce Type: cross Abstract: Recent advancements have successfully adapted autoregressive language models to process multimodal signals, such as images and actions. Since raw action signals are conti…
- arXiv cs.AIresearchI code or AI code: A comparative evaluation of AI-rated scores in classroom observations
arXiv:2609.18274v1 Announce Type: cross Abstract: Classroom observations are widely recognized as a key tool for establishing benchmarks of education quality and guiding pedagogical improvement, yet they remain resource-…
- arXiv cs.AIagentsA Study of the Reliability of Agentic AI-Generated Programs
arXiv:2609.18298v1 Announce Type: cross Abstract: Agentic-AI based software development offers the promise of faster completion of the software, greater programmer efficiency, and more reliable code. The question is how…
- arXiv cs.AIresearchKnowledge-Graph Based Augmentation versus Retrieval Augmented Generation for Cultural-Related Question Answering
arXiv:2609.18317v1 Announce Type: cross Abstract: Large language models (LLMs) suffer from a long-tail deficit: culturally specific facts, particularly those concerning underrepresented regions such as Latin America, app…