AI news archive.
19,854 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchWorld Models, Trees and Foundation Models for Retail Forecasting: Evidence from Four Public Data Sets
arXiv:2610.25170v1 Announce Type: cross Abstract: A retailer makes different decisions at different grains of the product, store and time hierarchy: store orders for an item in a store, supplier funding for an item acros…
- arXiv cs.AIresearchReranking Answers of Large Language Models with Knowledge Graphs
arXiv:2610.25185v1 Announce Type: cross Abstract: Answering natural language questions over knowledge graph data is challenging due to the vast number of facts, which can be difficult to process and navigate. One potenti…
- arXiv cs.AIresearchViCoR: Estimating Visual Necessity via Counterfactual Residuals for Multimodal Medical Data Selection
arXiv:2610.25202v1 Announce Type: cross Abstract: Medical vision-language models often exhibit hidden stratification, where high overall performance masks failures on subtle visual findings and overlapping clinical condi…
- arXiv cs.AIagentsNeuroAct: Advancing EEG Analysis and Decoding via Dual-Loop Autonomous Research
arXiv:2610.25211v1 Announce Type: cross Abstract: EEG analysis and decoding underpin brain-computer interfaces, cognitive assessment, and sleep monitoring. Fixed pipelines and reward-driven search do not explicitly deter…
- arXiv cs.AIresearchCalibration-Free Early Stopping for Chain-of-Thought Reasoning via E-processes
arXiv:2610.25212v1 Announce Type: cross Abstract: Reasoning large language models (LLMs) benefit from test-time scaling, motivating adaptive policies that spend tokens when they help and stop early otherwise. Existing ru…
- arXiv cs.AIagentsAssessing the Empirical Evidence for Loss of Control from Agentic General-Purpose AI
arXiv:2610.25241v1 Announce Type: cross Abstract: Theoretical literature warns that advanced generalist agentic systems might pursue instrumental goals that are misaligned with human preferences, thus posing risks of irr…
- arXiv cs.AIresearchBatchParScale: Sparse Batch-Mixing for Sequence Models
arXiv:2610.25254v1 Announce Type: cross Abstract: Recent test-time scaling methods improve model performance by increasing inference-time compute. One practical form of this is parallel scaling, where a model samples mul…
- arXiv cs.AIagentsEG-GRPO: Evidence-Guided Step-level Credit Assignment for Deep Search Agents
arXiv:2610.25269v1 Announce Type: cross Abstract: LLM-based search agents demonstrate strong capabilities in long-horizon information seeking and reasoning, typically trained via reinforcement learning. However, existing…
- arXiv cs.AIresearchVision as Proprioception: Estimating Humanoid Robot Pose from Video
arXiv:2610.25288v1 Announce Type: cross Abstract: Estimating a humanoid robot's internal state from video has a wide range of real-world applications but remains unexplored. During interactions with a robot, its onboard…
- arXiv cs.AIresearchWorld Model Interpretability: From Decoding Representations to Understanding Latent Worlds
arXiv:2610.25296v1 Announce Type: cross Abstract: Emerging Joint-Embedding Predictive Architectures (JEPAs) are moving beyond representation learning towards latent world models that support prediction, planning, and con…
- arXiv cs.AIresearchLearning When to Abort in Transformer Planning: A Mechanistic Study
arXiv:2610.25300v1 Announce Type: cross Abstract: Planning does not by itself imply the ability to recognise errors, but recognising errors can improve planning capacity. In this paper, we study this phenomenon in Transf…
- arXiv cs.AIresearchShared-Private Cross-Modal Discrepancy Learning for Imbalanced Multi-Source Audio-Visual Deepfake Detection
arXiv:2610.25301v1 Announce Type: cross Abstract: Audio-visual deepfake detectors are often trained under a single dataset or manipulation regime, but multi-source training collections may contain heterogeneous attacks a…
- arXiv cs.AIresearchAdaFedXplain: Adaptive Federated Learning with Explainable AI for Ransomware Detection
arXiv:2610.25318v1 Announce Type: cross Abstract: Attacks using ransomware have developed into complex multiphase campaigns that target vital infrastructure, resulting in annual damages of billions of dollars. Convention…
- arXiv cs.AIresearchWhere and Why Search-Augmented LLMs Fail When Reasoning over Rapidly Evolving Knowledge
arXiv:2610.25323v1 Announce Type: cross Abstract: As the world changes, new information is published while older records remain online. This complicates reasoning for large language models (LLMs), which must retrieve evi…
- arXiv cs.AIresearchFormally Verified Autoresearch for Analyzing the Expressivity of Multi-Head Attention
arXiv:2610.25341v1 Announce Type: cross Abstract: Multi-head attention is a central component of the transformer architecture, yet how its expressivity depends on the number of heads remains poorly understood. We study a…
- arXiv cs.AIresearchLocal Evidence, Global Failure: Diagnosing Speech-Vision Temporal Composition in Audio-Visual Language Models
arXiv:2610.25352v1 Announce Type: cross Abstract: Audio-visual large language models (AV-LLMs) can fail at full-video speech-vision decisions even when useful visual evidence is locally recoverable. We introduce Temporal…
- arXiv cs.AIresearchCHSM8: A Chess Transformer that Follows Natural-Language Style Prompts
arXiv:2610.25356v1 Announce Type: cross Abstract: We present CHSM8, a 210M-parameter chess transformer that plays moves conditioned on a free-text description of a playing style, e.g. "go for the Sicilian Defense", "soli…
- arXiv cs.AIresearchCD-OPD: Contextual Digest for On-Policy Distillation
arXiv:2610.25359v1 Announce Type: cross Abstract: Teacher takeover in on-policy distillation (OPD) can produce incorrect responses even when the student and teacher independently answer the same problem correctly, a fail…
- arXiv cs.AIresearchAligning Cultural Behaviors in Arabic Language Models via Preferences
arXiv:2610.25362v1 Announce Type: cross Abstract: Arabic LLMs have improved rapidly, but aligning them with country-specific cultural behavioral preferences remains underexplored. Previous work has focused primarily on i…
- arXiv cs.AIagentsMemDerive: A Diagnostic Benchmark for Agent Memory over Evolving Data
arXiv:2610.25373v1 Announce Type: cross Abstract: Long-running agents rely on memory of their past interactions for task state, such as what has been completed and which conditions still hold. Such state is usually a der…
- arXiv cs.AIresearchMOSAIC: Multi-Objective Search for Allocating Inference Cache Across LLM Decoder Layers
arXiv:2610.25431v1 Announce Type: cross Abstract: The Key-Value (KV) cache is the main memory bottleneck of long-context LLM inference. Token eviction methods such as SnapKV, H2O, AdaKV and L2Norm shrink it, but they giv…
- arXiv cs.AIresearchEnhanced Masked Diffusion Unlearning
arXiv:2610.25447v1 Announce Type: cross Abstract: Masked diffusion language models (MDLMs) generate text by iteratively unmasking tokens with bidirectional context. As these models reach real-world deployment, machine un…
- arXiv cs.AIresearchReliability-Preserving Compression for Deployable Medical Image Segmentation
arXiv:2610.25460v1 Announce Type: cross Abstract: Post-training compression of pretrained medical segmentation models commonly uses quantization, pruning, or distillation to reduce model size and computational cost. Exis…
- arXiv cs.AIresearchDiaLong: Benchmarking Reminiscence in Long-Context Dialogues
arXiv:2610.25463v2 Announce Type: replace-cross Abstract: How well can transformer-based Large Language Models (LLMs) retain and recall memories in long contexts of dialogue? LLMs are known to forget long-range factual i…
- arXiv cs.AIresearchMultimodal-Conditioned Latent Diffusion Models for Spatiotemporal Brain MRI Forecasting
arXiv:2610.25481v2 Announce Type: replace-cross Abstract: Spatiotemporal forecasting of 3D anatomical changes is a critical generative vision challenge for modeling Alzheimer's Disease (AD) progression. While brain MRI f…
- arXiv cs.AIresearchPRIMA: Pose Refined Inductive Motion Adapter for Zero Shot Social Bodily Behavior Recognition
arXiv:2610.25482v1 Announce Type: cross Abstract: Recognizing fine-grained bodily behaviors, such as self-grooming, postural shifts, and backchanneling, is a useful intermediate step for computational social signal analy…
- arXiv cs.AIresearchDynamics-Aligned Representation Learning under Induced Partial Observability
arXiv:2610.25511v1 Announce Type: cross Abstract: Model-based reinforcement learning (MBRL) has enabled sample-efficient learning of continuous control policies from high-dimensional observations through learned latent d…
- arXiv cs.AIagentsWhen Interpretations Persist: Downstream Influence in Gaze-Aware Assistants
arXiv:2610.25512v1 Announce Type: cross Abstract: AI assistants may carry forward not only observations but also interpretations of what a person is doing or may do next across time. Once retained, these interpretations…
- arXiv cs.AIresearchATEST: Adaptive Resource-Aware Test-Time Scaling for LLM Inference
arXiv:2610.25519v1 Announce Type: cross Abstract: Test-time scaling (TTS) improves large language model (LLM) reasoning by sampling multiple answers, but fixed sampling budgets ignore both query difficulty and the changi…
- arXiv cs.AIresearchModaliff: A Unified Token Diffusion Model for Any-to-Any Generation
arXiv:2610.25533v1 Announce Type: cross Abstract: Any-to-any generation seeks a single model that translates flexibly among text, image, and audio, yet existing approaches either require fully aligned multimodal tuples o…
- arXiv cs.AIresearchResidential Construction Image Dataset Using CSI Divisions for Deep Learning-based Object Detection
arXiv:2610.25535v1 Announce Type: cross Abstract: Accurate recognition of construction site elements is essential for the application of deep learning (DL) in the construction industry. Despite rapid advances in computer…
- arXiv cs.AIagentsBenchmark for Structured Retrieval-Augmented Generation in Perovskite Photovoltaics
arXiv:2610.25575v1 Announce Type: cross Abstract: While retrieval-augmented language models increasingly serve as literature assistants in the physical sciences, existing benchmarks evaluate them primarily on qualitative…
- arXiv cs.AIagentsWhen Better Opportunities Backfire: Service Worker Responses to Parallel AI Deployment in Customer Acquisition
arXiv:2610.25603v1 Announce Type: cross Abstract: As AI voice agents get deployed in high-volume contact centers, firms can route low-intent leads to AI and allocate high-intent leads to human workers. Drawing on sequent…
- arXiv cs.AIresearchSafety Offset Learning: When Benign Fine-Tuning Misaligns LLMs
arXiv:2610.25611v1 Announce Type: cross Abstract: Safety risks from fine-tuning are commonly characterized by the harmfulness of the training data:harmful fine-tuning is considered dangerous, while benign fine-tuning is…
- arXiv cs.AIresearchWeighted State Souping for Efficient Long-Context Retrieval
arXiv:2610.25621v1 Announce Type: cross Abstract: State space models (SSMs) combine fast inference and fixed state size with competitive language-modeling performance. Recently, state souping has been proposed as a proce…
- arXiv cs.AIagentsMapSteal: Map-based Autonomous Knowledge Stealing Attack Against Large Language Models
arXiv:2610.25626v1 Announce Type: cross Abstract: Knowledge acquisition from black-box large language models (LLMs) offers a practical approach to adapting smaller student models. However, many existing methods rely on p…
- arXiv cs.AIagentsSelecting and Composing Agent Design Patterns: Industrial Case Evidence and Controlled Reference-System Experiments
arXiv:2610.25629v1 Announce Type: cross Abstract: Agent pattern catalogs describe architectural alternatives, but engineers also need evidence for selecting and composing them. We extend a cognitive-function--execution-t…
- arXiv cs.AIresearchACorD: Adaptive Correspondence Discovery for Medical Image Registration
arXiv:2610.25638v1 Announce Type: cross Abstract: Medical image registration is a fundamental task for aligning anatomical structures across images. Exhaustively searching for point-wise correspondences is prohibitively…
- arXiv cs.AIresearchConsistency Training Suppresses Cue Following Without Teaching Cue Selectivity
arXiv:2610.25650v1 Announce Type: cross Abstract: Language models often change answers because of a cue, a hint such as "I believe the answer is B" that gives no valid evidence. Consistency training (CT) trains a model t…
- arXiv cs.AIresearchA "feature ODE" describing the learning behavior of shallow MLPs on simple functions
arXiv:2610.25652v1 Announce Type: cross Abstract: We study the gradient flow training dynamics of two-layer multi-layer perceptrons (MLPs) on anisotropic Gaussian data. Even in this simple setting, solving the dynamics i…
- arXiv cs.AIresearchBeyond Leaderboards: A Method for Application-Specific Capability Profiling of Large Language Models
arXiv:2610.25659v1 Announce Type: cross Abstract: Public leaderboards rank large language models (LLMs) in general, but an engineer has to choose a model for a specific application, architecture and cost. This paper pres…
- arXiv cs.AIresearchCross-Pollination Retrieval: Finding Transferable Ideas Across Fields in Scientific Literature
arXiv:2610.25678v1 Announce Type: cross Abstract: Many scientific advances come from cross-pollination, carrying an idea from one field over to a problem in another. Yet retrieving papers across fields remains underexplo…
- arXiv cs.AIresearchMT-CC: Multi-Group Temperature Scaling for Asymmetric Calibration Behavior in Class-Incremental Learning
arXiv:2610.25689v1 Announce Type: cross Abstract: As deep neural networks are required to continuously adapt to evolving data, class-incremental learning (CIL) has become an active research area. However, most existing w…
- arXiv cs.AIresearchProgress-Guided Preference Generation for Aligning Generative Control Policies
arXiv:2610.25692v1 Announce Type: cross Abstract: Generative policies have achieved strong performance in imitation learning tasks, but their success is often constrained by the limited availability of expert demonstrati…
- arXiv cs.AIresearchCausal Humility: Governing the Authority of Fairness Claims Under Causal Uncertainty
arXiv:2610.25709v1 Announce Type: cross Abstract: AI systems increasingly shape consequential decisions in employment, lending, healthcare, and public services, making fairness an important problem for auditing and gover…
- arXiv cs.AIresearchCorrected Block Sparse Spectral Optimization: Exact Models, Finite Identification, and Local Dynamics
arXiv:2610.25721v1 Announce Type: cross Abstract: The block generalized-power method pairs threshold-based support selection with inexpensive Stiefel updates, but the standard block formulation conflates two nonequivalen…
- arXiv cs.AIresearchAnatomy of Off-Policy Policy Gradient: Importance Sampling, KL Regularization, and Baselines
arXiv:2610.25725v1 Announce Type: cross Abstract: Reinforcement learning has become a central tool for large language model (LLM) post-training, where policy gradient methods are routinely deployed off-policy, even thoug…
- arXiv cs.AIresearchNo Matter Who You Are: Addressivity and Sycophancy in Large Language Models
arXiv:2610.25728v1 Announce Type: cross Abstract: Sycophancy, where an LLM becomes overly agreeable, deferential, or flattering toward the user, has been identified as a major failure mode. While post-training has been i…
- arXiv cs.AIresearchA Calibrated Instrument for Detecting Disposition Drift in Language Models
arXiv:2610.25735v1 Announce Type: cross Abstract: Before language models are released, they are tested for harmful traits such as willingness to carry out dangerous requests, deception, power seeking, and sycophancy. The…
- arXiv cs.AIresearchCognitively Decoupled Meta-Induction for Out-of-Distribution Generalization
arXiv:2610.25749v1 Announce Type: cross Abstract: In-context learning (ICL) tackles downstream tasks conditioned on demonstrations. This paradigm relies heavily on neighbor-based matching between queries and demonstratio…