AI news archive.
19,861 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchA Hybrid AI Framework for Academic Advising: Integrating Ensemble-Based Grade Prediction and a Rule-Based Expert System
arXiv:2609.26243v1 Announce Type: new Abstract: The rapidly increasing student population has posed serious challenges to the traditional academic advising process. This study designs and implements a multi-purpose intel…
- arXiv cs.AIresearchA Multi-Timestep LSTM Ensemble regressor for Enhanced Short-Term Runoff Prediction
arXiv:2609.26244v1 Announce Type: new Abstract: Accurately forecasting river runoff is key to managing water resources, controlling floods, and planning agriculture. This study examines the Ajichay River in northwest Ira…
- arXiv cs.AIagentsCoding Agents are Strong Prompt Optimizers
arXiv:2609.26261v1 Announce Type: new Abstract: Search-based prompt optimizers improve prompts through iterative search: they propose edits, execute fresh rollouts, score the resulting trajectories, and retain only edits…
- arXiv cs.AIresearchDecoupling Is Not Identification: Supervised Evidential Learning in Next-Token Prediction
arXiv:2609.26268v1 Announce Type: new Abstract: A next-token probability says what a model predicts, not how much training support lies behind it. A Dirichlet head can represent this distinction by separating mean $m$ fr…
- arXiv cs.AIresearchFISSION: Label Augmentation for Bot Detection
arXiv:2609.26279v1 Announce Type: new Abstract: Bot accounts and coordinated influence operations are often discovered via heuristic methods, leaving a dearth of reliable ground-truth labels for training detection system…
- arXiv cs.AIagentsDual-Frontier: When Can an Agent Trust Its World Model?
arXiv:2609.26293v2 Announce Type: replace Abstract: Learned world models are becoming essential to general-purpose agents: by predicting action consequences, they support planning and decision-making while reducing relia…
- arXiv cs.AIresearchReliability Theory for AI Control
arXiv:2609.26419v1 Announce Type: new Abstract: Reliability theory gives a mature language for layered systems, but its formal tools are not yet standard in frontier AI control. We apply them to Google DeepMind's defense…
- arXiv cs.AIagentsThe Source of Disturbance Matters: External, Internal, and Control-Generated Noise in Adaptive Regulation
arXiv:2609.26428v1 Announce Type: new Abstract: Adaptive regulation can itself perturb the state it is intended to stabilize. In replicated simulations of an adaptive agent, we compare external disturbance, persistent in…
- arXiv cs.AIagentsRecursive self-improvement of AI research agents
arXiv:2609.26457v1 Announce Type: new Abstract: AI agents are beginning to automate research and development across the AI stack, from improving training efficiency to optimizing inference. A natural next step is to impr…
- arXiv cs.AIresearchReproducible AI Requires Reproducible Randomness
arXiv:2609.26461v1 Announce Type: new Abstract: Pseudorandom number generators (PRNGs) constitute indispensable computational tools across multiple scientific domains, including Monte Carlo simulations, stochastic comput…
- arXiv cs.AIagentsREFLEX with Jev for Efficient Selective Control in LLM Agents
arXiv:2609.26532v1 Announce Type: new Abstract: LLM agents often use generative models for bounded decisions, raising the question of when these decisions can be handled more efficiently without reducing task success. We…
- arXiv cs.AIresearchJEV-as-a-Judge: Accept When Confident, Escalate When Unsure
arXiv:2609.26550v5 Announce Type: replace Abstract: LLM-as-a-judge scales evaluation, but reasoning judges are slow and costly. We study JEV-as-a-Judge: evaluation with JEV, a decision-only judge that returns label proba…
- arXiv cs.AIresearchNeutral-Atom-based Quantum Optimization for Resource Allocation in NOMA Networks
arXiv:2609.26556v1 Announce Type: new Abstract: In wireless communication networks, many resource optimization problems are nondeterministic polynomial-time hard (NP-hard) due to their combinatorial nature and high compu…
- arXiv cs.AIresearchQuantum-Aided Active Device Detection in Energy-Harvesting Symbiotic Radio Networks
arXiv:2609.26565v1 Announce Type: new Abstract: Massive connectivity in next-generation networks demands energy- and spectrum-efficient solutions for large-scale Internet of Things (IoT) deployments. Symbiotic radio (SR)…
- arXiv cs.AIagentsThe Delegation Blind Spot: Auditing Product Decisions from Agent Choices
arXiv:2609.26642v1 Announce Type: new Abstract: Successful agent execution need not identify which future product improvement its user would value. We present a decision-specific audit that maps a declared observation ch…
- arXiv cs.AIresearchType-Safe Is Not Error-Free: Typed Decision Models Follow the Option Name, Not the Definition Bound to It
arXiv:2609.26758v3 Announce Type: replace Abstract: Typed decision models return structured results, but output-type correctness alone does not ensure that decisions follow explicit option definitions. Each option pairs…
- arXiv cs.AIagentsGrow the Harness, Not the Context: From Strategy-Free Scaffolds to Reusable Specialist Agents
arXiv:2609.26760v2 Announce Type: replace Abstract: Large language model (LLM) agents often handle streams of related tasks, yet standard harnesses repeatedly ask the model to reconstruct the same control decisions insid…
- arXiv cs.AIagentsSWE-Serve: Benchmarking Agentic Engineering For Production Inference Serving
arXiv:2609.26777v1 Announce Type: new Abstract: We introduce SWE-Serve, a benchmark for evaluating agents on production inference engineering tasks. Implementing an inference feature can require coordinating multiple cha…
- arXiv cs.AIagentsCliffCompaction: Cost-Efficient Compaction for Long-Horizon Coding Agents
arXiv:2609.26779v1 Announce Type: new Abstract: Agents often work on complex problems that require millions of tokens of context, which necessitates compacting across sessions due to limited context windows. We develop C…
- arXiv cs.AIresearchFinancial sentiment analysis using FinBERT with application in predicting stock movement
arXiv:2306.02136v3 Announce Type: cross Abstract: In this study, we integrate sentiment analysis within a financial framework by leveraging FinBERT, a fine-tuned BERT model specialized for financial text, to construct an…
- arXiv cs.AIresearchNot All 4-bit Quantizers Are Equal: Deployment-Time Mitigation of PII Leakage in Fine-Tuned Small Language Models
arXiv:2609.25014v1 Announce Type: cross Abstract: Organizations fine-tune small language models on private data and then compress them to 4 bits for resource-efficient deployment. We show that the compression method also…
- arXiv cs.AIresearch"As a Language Model...": Chat Template Switches LLM Self-Referential Voice and Activation Steering Reproduces It
arXiv:2609.25021v1 Announce Type: cross Abstract: Large Language Models (LLMs) tend to add disclaimers like "I'm just an AI" when asked about something related to themselves. The self-reports from such responses are used…
- arXiv cs.AIagentsAIBuildAI-2.5: Efficient Autonomous AI Model Development Through LLM-Guided Tree Search
arXiv:2609.25047v1 Announce Type: cross Abstract: Autonomous agents that automatically build artificial intelligence (AI) models could broaden access to AI across science and engineering. A popular line of such agents fr…
- arXiv cs.AIresearchTeaching a Moving Student: Rethinking the Curriculum of On-Policy Distillation
arXiv:2609.25048v2 Announce Type: replace-cross Abstract: In on-policy distillation (OPD), the student determines which states receive teacher supervision. As its policy evolves, earlier response prefixes become less lik…
- arXiv cs.AIresearchMitigating LLM Over-Refusal via Dynamic Semantic Routing Calibration
arXiv:2609.25049v2 Announce Type: replace-cross Abstract: Large language models (LLMs) aligned for safety often suffer from over-refusal, incorrectly rejecting benign yet safety-related instructions. Prior studies primar…
- arXiv cs.AIresearchFrontierMath Erd\H{o}s
arXiv:2609.25050v1 Announce Type: cross Abstract: We introduce FrontierMath Erd\H{o}s (FME), a benchmark of 68 Erd\H{o}s problems that are open as of August 2026. To solve a task in FME, AI systems must resolve (prove or…
- arXiv cs.AIresearchLLM-Driven Training-free Location-Attribute Synergic Fusion: A Closed-Loop Paradigm for Dual-source Encrypted POIs and LULC Mapping
arXiv:2609.25051v1 Announce Type: cross Abstract: Dual-source encrypted points of interest (DSEP), POIs from two encrypted coordinate systems, suffer from intertwined location and attribute uncertainties, including nonli…
- arXiv cs.AIagentsSelf-Cleaning and Captured Anyway: One Measured Primitive for Error in a Store an Agent Writes to Itself, and What a Falling Score Actually Measures
arXiv:2609.25052v1 Announce Type: cross Abstract: "An agent that writes its conclusions into a store it later retrieves from closes a loop usually reported as one-way contamination. Taking the loop to the infinite-tenure…
- arXiv cs.AIresearchLatentPort: Beyond KV Cache - Cross-Model Transfer of Recurrent Memory in Hybrid Language Models: A 4B-to-9B Hybrid-State Handoff Without Target Prefix Replay
arXiv:2609.25053v1 Announce Type: cross Abstract: Can one language model hand its live memory to another without the receiver rereading the context? We demonstrate useful persistent hybrid-state transfer across one archi…
- arXiv cs.AIresearchPhysics-guided deep metric learning with continuous time embeddings for open-world radar pulse de-interleaving
arXiv:2609.25057v1 Announce Type: cross Abstract: Radar pulse de-interleaving is a foundational Electronic Support Measures (ESM) task that aims to separate chronologically interleaved pulse streams from multiple non-coo…
- arXiv cs.AIresearchFederating Quantum and Classical Computing: A Privacy-Preserving Hybrid Approach
arXiv:2609.25082v1 Announce Type: cross Abstract: Quantum machine learning (QML) is increasingly recognized as one of the most promising near-term applications of quantum computing, viewed as a next-frontier candidate be…
- arXiv cs.AIresearchYou've Seen Enough: Quality-Constrained Image Coding for Machines
arXiv:2609.25108v2 Announce Type: replace-cross Abstract: Visual data is increasingly consumed by machine-vision systems rather than by human observers. Image Coding for Machines (ICM) compresses images assuming the main…
- arXiv cs.AIresearchRachel: A general-purpose language model directs and revises retrosynthetic routes
arXiv:2609.25118v1 Announce Type: cross Abstract: Retrosynthetic planning advances through decisions that reshape the remaining chemical problem: a locally plausible disconnection can leave precursors whose chemoselectiv…
- arXiv cs.AIresearchWILSON - Multi-magnification composites as a foundation for patient-level pathology analysis and diagnostic text generation
arXiv:2609.25123v2 Announce Type: replace-cross Abstract: Pathologists examine tissue sections across multiple magnifications and slides, integrating morphological information to establish a diagnosis. In contrast, most…
- arXiv cs.AIagentsImpact Is Not Invalidation: Ask About the Claim, Not the Diff
arXiv:2609.25130v1 Announce Type: cross Abstract: Memory systems for coding agents must decide, when a repository changes, which of their stored claims have become false. Content anchoring invalidates a claim whenever th…
- arXiv cs.AIresearchThe Probabilistic Structure of Large Language Models
arXiv:2609.25134v1 Announce Type: cross Abstract: This paper presents a probabilistic perspective on large language models (LLMs), developed with the aim of bringing together, in a single self-contained account, tools th…
- arXiv cs.AIresearchStable Unsupervised Continual Chunking with Sheaf SyncMap
arXiv:2609.25143v1 Announce Type: cross Abstract: Unsupervised Continual chunking is a fundamental problem in machine learning and neuroscience, where the goal is to identify groups of states that frequently co-occur in…
- arXiv cs.AIresearchBrain-Inspired Hierarchical Modularity for General Continual Learning
arXiv:2609.25146v1 Announce Type: cross Abstract: Continual learning, the ability to learn from sequential experience while retaining and adapting prior knowledge, is central to intelligent systems operating in changing…
- arXiv cs.AIresearchTowards Sustainable Magnetic Resonance Imaging: Insights from long-term, high-resolution energy recordings across an entire scanner fleet
arXiv:2609.25150v1 Announce Type: cross Abstract: Magnetic resonance imaging (MRI) is among the most energy-intensive diagnostic modalities in healthcare, yet its energy consumption and the factors influencing it remain…
- arXiv cs.AIresearchExposing Blind Spots in Deep Imbalanced Regression Evaluation
arXiv:2609.25152v1 Announce Type: cross Abstract: Deep Imbalanced Regression (DIR) addresses a common failure mode of regression models: target distributions are highly non-uniform, causing models to perform best in dens…
- arXiv cs.AIresearchBenchmarking Neural Defend ARCAS 1B: A Foundational Multimodal Deepfake Detection Model
arXiv:2609.25154v1 Announce Type: cross Abstract: AI-generated imagery evolves faster than benchmark-specific detector evaluations, making a single score an incomplete account of generalization. This paper evaluates Neur…
- arXiv cs.AIresearchMitigating Sequential Reappearance in Diffusion Data-Point Unlearning
arXiv:2609.25166v2 Announce Type: replace-cross Abstract: Diffusion data-point unlearning is typically evaluated immediately after each deletion, even though subsequent requests may repeatedly update the same model. We i…
- arXiv cs.AIagentsQwen-Audio-3.1-Realtime: Towards Reliable Agentic Voice Interaction
arXiv:2609.25176v2 Announce Type: replace-cross Abstract: Real-time voice assistants must reason over evolving requests, execute actions, and follow conversational rules. Qwen-Audio-3.1-Realtime brings these requirements…
- arXiv cs.AIresearchMulti-Term Fourier Graph Neural Network with Sample Relationship Learning for Enhanced Remaining Useful Life Prediction
arXiv:2609.25179v1 Announce Type: cross Abstract: Predicting the remaining useful life (RUL) is essential for effective predictive maintenance. Spatio-Temporal Graph Neural Networks (ST-GNNs), which can model both tempor…
- arXiv cs.AIresearchFrom Pattern Recognizers to Personalized Companions: A Survey of Large Language Models in Mental Health
arXiv:2609.25186v1 Announce Type: cross Abstract: The rising global prevalence of mental health conditions, together with longstanding barriers in traditional healthcare, such as limited resources, high cost, stigma, and…
- arXiv cs.AIresearchGroundedGEO: Auditing the Evidence Gap in Generative Search Rankings
arXiv:2609.25189v1 Announce Type: cross Abstract: Generative search systems rank products and services for consequential decisions, and publishers can cheaply make candidate text look relevant. Yet evidence status is not…
- arXiv cs.AIagentsIndirect tipping: a social attack surface in AI agent populations
arXiv:2609.25194v1 Announce Type: cross Abstract: As generative AI agents are deployed at scale, safety will depend not only on technical safeguards and individual model design, but also on collective equilibria that det…
- arXiv cs.AIagentsTrains but Doesn't Learn: A Post-Training Delivery Benchmark for LLM Agents as Forward-Deployed Engineers
arXiv:2609.25237v1 Announce Type: cross Abstract: Post-training is becoming a service (PTaaS): a customer hands an operator data and a goal, and a forward-deployed engineer (FDE) returns a fine-tuned, evaluated, and depl…
- arXiv cs.AIresearchHow Children Design and Reason about Trustworthy AI Chatbots
arXiv:2609.25244v5 Announce Type: replace-cross Abstract: Children increasingly interact with AI chatbots, making trust calibration essential to AI literacy. Prior research has examined children's trust in AI mainly as u…
- arXiv cs.AIresearchGeometric and Semantic Coupling for Interaction Understanding in 3D Scenes
arXiv:2609.25247v2 Announce Type: replace-cross Abstract: Understanding interaction in a 3D scene requires recovering movable parts, their motion, and where they can be operated. These quantities are related, and their p…