AI news archive.
10,661 articles filed under Research, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchIs invariance all you need for algorithmic fairness? Removing demographic information can create new bias
arXiv:2609.32004v1 Announce Type: cross Abstract: Encoded demographic information in internal model representations is a commonly assumed risk factor for algorithmic bias, with demographic representation invariance often…
- arXiv cs.AIresearchTriO: Tri-Modal Unsupervised Occupancy World Model for Anything Perception
arXiv:2609.32013v2 Announce Type: replace-cross Abstract: We present TriO, a multi-modal unsupervised world model that predicts 4D occupancy, obstacle segmentation, flow and LiDAR. In contrast to prior work, TriO utilize…
- arXiv cs.AIresearchVoiceNet: Fine-Grained Voice Understanding Beyond Emotion at Scale
arXiv:2609.32016v1 Announce Type: cross Abstract: Expressive speech synthesis has outpaced expressive speech perception: systems now render fine-grained vocal performances that no public benchmark can score. Most benchma…
- arXiv cs.AIresearchDepth Any Seen: Which Surfaces and How Far?
arXiv:2609.32027v1 Announce Type: cross Abstract: When several surfaces are visible along a ray, recovering visible 3D structure from one image requires jointly estimating their presence and metric depth. Depth Any Seen…
- arXiv cs.AIresearchAmnesia by Design, Memory By Necessity: Persistent State for Document Intelligence
arXiv:2609.32041v1 Announce Type: cross Abstract: Modern Document AI reads contracts, extracts fields, reasons over tables, and grounds answers to page regions, then forgets everything. Processing an amendment the next d…
- arXiv cs.AIresearchTracing Decoder Artifacts for Compact Synthetic Speech Screening
arXiv:2609.32050v1 Announce Type: cross Abstract: Recent advances in speech synthesis and voice cloning have increased the need for reliable synthetic-speech detection, yet high-accuracy detectors increasingly rely on la…
- arXiv cs.AIresearchReFM: Semantic-Aware Refinement Flow Model for Motion Retargeting
arXiv:2609.32068v1 Announce Type: cross Abstract: Motion retargeting transfers motion across characters with different skeletal structures while preserving semantic intent and physical plausibility. Despite recent progre…
- arXiv cs.AIresearchWhen Should a Human Take Back Control? Optimal Delegation under Turbulent AI Risk
arXiv:2609.32083v1 Announce Type: cross Abstract: Deploying AI systems requires deciding when to delegate tasks and when humans should intervene to monitor and mitigate risk induced by AI operations. These decisions are…
- arXiv cs.AIresearchEmergent One-Third Scaling Law as Attention Tries to Concentrate
arXiv:2609.32100v1 Announce Type: cross Abstract: The neural scaling law relating longer training to better performance through a power law is central to today's large language models (LLMs), yet its origin remains debat…
- arXiv cs.AIresearchEmpowering Hybrid Attention Models on NPUs
arXiv:2609.32114v1 Announce Type: cross Abstract: Hybrid attention models have emerged as a crucial architecture for Large Language Models (LLMs) (e.g., the Qwen3.5 and Kimi series). Their memory and computational effici…
- arXiv cs.AIresearchREALM: Regime-Switching, Explainable, and Activation-Induced Linear Models
arXiv:2609.32141v1 Announce Type: cross Abstract: Deep ReLU networks are piecewise-affine mappings that partition the input space into cells, each characterized by a distinct activation pattern. This structure motivates…
- arXiv cs.AIresearchSpectral Reversal: Counteracting Singular Value Bias for Graph Prompting
arXiv:2609.32143v1 Announce Type: cross Abstract: Pre-training Graph Neural Networks (GNNs) via self-supervised learning has become a dominant paradigm, yet efficiently adapting frozen encoders remains a challenge. Graph…
- arXiv cs.AIresearchTyped Decision Models: An Early Evidence Audit and Evaluation Checklist
arXiv:2609.32160v1 Announce Type: cross Abstract: Typed decision models (TDMs) return probability distributions over caller-defined options without generating text. TypeSafe released Jev, a commercial typed decision mode…
- arXiv cs.AIresearchUncertainty-Aware Selection of Online Algorithms with Simulator Ensembles
arXiv:2609.32170v1 Announce Type: cross Abstract: The performance of online reinforcement learning depends critically on design choices, especially those that affect exploration. These choices are often selected by fitti…
- arXiv cs.AIresearchKeyRec: Bounded Visual Memory for Streaming and Long-Video Understanding
arXiv:2609.32182v1 Announce Type: cross Abstract: Vision-language models are increasingly used to understand long videos and continuous streams. However, dense visual tokens accumulate with video duration, making long-co…
- arXiv cs.AIresearchPresence Is Not Faithfulness: Figurative Vehicle Intrusion in Text-to-Image Generation
arXiv:2609.32188v1 Announce Type: cross Abstract: Text-to-image (TTI) models increasingly generate high-quality images from natural-language prompts, yet figurative language exposes a failure: a vehicle that should guide…
- arXiv cs.AIresearchEvaluating Single and Multi-Omics Based Explainable Artificial Intelligence (MOXAI) for Molecular Subclass Classification of Adult-Type Diffuse Gliomas
arXiv:2609.32190v1 Announce Type: cross Abstract: DNA methylation (DNAM) profiling has emerged as a powerful diagnostic tool for classifying brain and solid tumors. However, existing computational models typically analyz…
- arXiv cs.AIresearchRank Confidence Sequences:Anytime-valid Leaderboards
arXiv:2609.32211v1 Announce Type: cross Abstract: Leaderboards rank models by their average scores on benchmark items, and they are consulted repeatedly while the evaluation is still running. Existing confidence interval…
- arXiv cs.AIresearchDP-Rec: Towards Dynamic Patching for Efficient Long-Sequence Recommendation
arXiv:2609.32215v1 Announce Type: cross Abstract: Transformers have redefined sequential recommendation by effectively modeling dynamic user behaviors and long-range dependencies. However, they remain inherently ineffici…
- arXiv cs.AIresearchAutoPDEBench: Benchmarking LLM Auto-Research for Neural PDE Solver Design
arXiv:2609.32245v1 Announce Type: cross Abstract: Partial differential equations (PDEs) are essential for modeling complex physical systems, and neural solvers have recently emerged as powerful data-driven tools for nume…
- arXiv cs.AIresearchDS-VLA: A Dendritic-inspired Vision-Language-Action Model for Robust Action Control
arXiv:2609.32253v1 Announce Type: cross Abstract: Vision-language-action (VLA) models have achieved strong performance in language-conditioned manipulation, yet success under nominal evaluation does not necessarily trans…
- arXiv cs.AIresearchSupporting and Performing Culture from the Inside
arXiv:2609.32281v1 Announce Type: cross Abstract: Anthropology and related disciplines which study culture have often found it useful to consider their epistemological and methodological approaches in terms of emic versu…
- arXiv cs.AIresearchA Solvable Theory of Pre-training Data Poisoning: Regime-Dependent Scaling Exponents
arXiv:2609.32288v1 Announce Type: cross Abstract: Pre-training data poisoning of large language models is usually studied using targeted backdoors and their survival through safety post-training, which leaves open a more…
- arXiv cs.AIresearchAffordance-Conditioned Decision Making: Bridging the Semantic-Spatial Gap in Zero-Shot Cross-Floor Vision-and-Language Navigation
arXiv:2609.32292v2 Announce Type: replace-cross Abstract: Vision-and-language navigation increasingly relies on general-purpose semantic planners, yet translating correct high-level intent into reliable physical executio…
- arXiv cs.AIresearchTRAP: Understanding and Mitigating Privacy Memorization in Language Models
arXiv:2609.32293v1 Announce Type: cross Abstract: Fine-tuning a language model on sensitive records can leave it able to reproduce them. We ask when this memorization arises and how to prevent it without knowing in advan…
- arXiv cs.AIresearchPhase Space Attention:A Hairer Lift Circumvents the Single-Layer Induction Obstruction
arXiv:2609.32319v1 Announce Type: cross Abstract: We circumvent the Sanford-Hsu-Telgarsky (SHT) single-layer induction obstruction within a linear, one-step, causal, bilinear, symplectically consistent design class on th…
- arXiv cs.AIresearchSuperposed Inference for Hyperdimensional Computing
arXiv:2609.32320v1 Announce Type: cross Abstract: Hyperdimensional computing (HDC) is attractive for efficient and robust learning, but conventional inference still encodes every query independently, repeatedly paying th…
- arXiv cs.AIresearchActive Feature Acquisition With Incomplete Training Data
arXiv:2609.32325v1 Announce Type: cross Abstract: In many prediction tasks, acquiring all features can be a prohibitively expensive or outright impossible task. Further, in many cases a static subset of features may not…
- arXiv cs.AIresearchProgressive-View On-Policy Distillation for Regional-to-Global Transfer in Multimodal LLMs
arXiv:2609.32333v1 Announce Type: cross Abstract: Regional-to-global distillation uses crop-conditioned guidance to improve full-image understanding. The challenge is to effectively transfer the teacher's crop-based adva…
- arXiv cs.AIresearchAnalog-Friendly Predictive Coding without Activation Derivatives
arXiv:2609.32350v1 Announce Type: cross Abstract: Predictive coding (PC) is a local, energy-based alternative to backpropagation (BP) whose iterative inference dynamics make it attractive for implementation on analog har…
- arXiv cs.AIresearchEyeVQA: Benchmarking Ophthalmic Vision-Language Models from Recognition to Spatial Grounding
arXiv:2609.32352v3 Announce Type: replace-cross Abstract: Vision-language models (VLMs) have shown increasing potential for medical image understanding, yet their capabilities in ophthalmic imaging remain insufficiently…
- arXiv cs.AIresearchDiffPTS: Rethinking Diffusion ELBO for Probabilistic Time Series Forecasting
arXiv:2609.32363v2 Announce Type: replace-cross Abstract: Probabilistic time series forecasting requires modeling and predicting complex and time-varying distributions. Recently, Denoising Diffusion Probabilistic Model (…
- arXiv cs.AIresearchTimeES: Probabilistic and Deterministic Time Series Forecasting via Evolutionary Spectra
arXiv:2609.32384v2 Announce Type: replace-cross Abstract: Real-world time series are inherently non-stationary, with trends, periodic patterns, and uncertainty evolving over time. While the Fourier domain offers a natura…
- arXiv cs.AIresearchAutomatic Speech Recognition for the Basa\`{a} Language: A Low-Resource Approach
arXiv:2609.32408v1 Announce Type: cross Abstract: The rapid advancement of Artificial Intelligence (AI) and Natural Language Processing (NLP) has revolutionized the way humans interact with machines. Among the most impac…
- arXiv cs.AIresearchRethinking Training-Inference Mismatch in LLM Reinforcement Learning: Where It Arises and How to Correct It
arXiv:2609.32444v1 Announce Type: cross Abstract: We study training-inference mismatch in reinforcement learning with verifiable rewards (RLVR) for large language models, where rollouts are sampled by an inference engine…
- arXiv cs.AIresearchDRAM: Delta-rule Recurrent Associative Memory for Robot Manipulation Policies
arXiv:2609.32453v2 Announce Type: replace-cross Abstract: Robotic manipulation is inherently history-dependent, yet most pretrained robotic policies condition on only the current observation or a short temporal window. E…
- arXiv cs.AIresearchDe-biasing Skeleton-based Action Recognition with Convex Hull Adaptive Shift
arXiv:2609.32454v1 Announce Type: cross Abstract: Skeleton sequences can represent both individual actions and multi-entity interactions, encompassing human bodies, hands, objects, and robots. Existing approaches to reco…
- arXiv cs.AIresearchSeeing Parts, Reasoning about Worlds: Visual Inference under Partial Observation
arXiv:2609.32456v1 Announce Type: cross Abstract: World modeling under partial observation requires reasoning about the complete worlds that remain compatible with limited visual evidence. Occluded objects and unseen reg…
- arXiv cs.AIresearchAdapting Nonstationary Multi-output Gaussian Processes to Bayesian Optimization
arXiv:2609.32464v1 Announce Type: cross Abstract: Multi-objective Bayesian optimization (MOBO) commonly relies on independent Gaussian processes (GPs) with stationary kernels, limiting its ability to represent nonstation…
- arXiv cs.AIresearchBison: Cross-Dataset Learning for Unseen-Compound Perturbation Prediction
arXiv:2609.32467v1 Announce Type: cross Abstract: Predicting transcriptional responses to unseen compounds is limited by fragmented chemical coverage and heterogeneous experimental platforms and gene panels. To assess mo…
- arXiv cs.AIresearchExplaining Textual Entailment with Lexical Entailments: Using LLMs to Supply Lexical Relations for Formal Proofs
arXiv:2609.32491v1 Announce Type: cross Abstract: Large Language Models (LLMs) are highly capable of natural language reasoning and appear to store a great deal of lexical knowledge, but it is still unclear how much of t…
- arXiv cs.AIresearchSoFT: Soft Targets for Generalizable LLM Fine-Tuning
arXiv:2609.32493v2 Announce Type: replace-cross Abstract: Distillation enables student language models to acquire new capabilities from expert teachers. However, integrating knowledge from multi-teacher, multi-domain dem…
- arXiv cs.AIresearchLearning an Anchored Prompt Space for Continual Adaptation of Large Language Models
arXiv:2609.32499v2 Announce Type: replace-cross Abstract: Continually adapting large language models requires acquiring new knowledge while preserving previously learned capabilities. Although jointly adapting model para…
- arXiv cs.AIresearchRondo: Unsupervised Discovery of Recurring Temporal Structure
arXiv:2609.32500v1 Announce Type: cross Abstract: Many real-world time series data exhibit structural properties at multiple scales, from short, recurring units to complex sequences composed of these units. Unsupervised…
- arXiv cs.AIresearchActivation Flow: Manufacturing Activations for Steering
arXiv:2609.32530v2 Announce Type: replace-cross Abstract: Difference-in-means steering requires activations recorded while a model shows the desired behavior, which a sandbagging model withholds by deliberately underperf…
- arXiv cs.AIresearchWhat Does a ProcGen Generalization Gap Measure? Action Rules, Residual Entropy, and the Missing Random Floor
arXiv:2609.32532v2 Announce Type: replace-cross Abstract: A generalization gap in reinforcement learning, return on training levels minus return on held-out levels, is usually reported without a reference point. We argue…
- arXiv cs.AIresearchDepthBench: Measuring How Residual Connections Enable More Computational Depth
arXiv:2609.32534v1 Announce Type: cross Abstract: Depth is a natural way to increase the computational capacity in Transformers, yet the contribution of deeper layers can diminish as depth grows larger. Recent approaches…
- arXiv cs.AIresearchIn-Flight KV Cache with Clean Anchors for Faster Autoregressive Video Diffusion
arXiv:2609.32540v2 Announce Type: replace-cross Abstract: Few-step autoregressive video diffusion generates a long video by splitting the video into temporal chunks and generating chunk-by-chunk, each through a short seq…
- arXiv cs.AIresearchHarnessing Coupled Stream Completion For Human-Object Interaction Modeling
arXiv:2609.32551v2 Announce Type: replace-cross Abstract: Text-conditioned human-object interaction (HOI) generation requires body motion, object trajectories & rotations, and hand articulation to remain coordinated. The…
- arXiv cs.AIresearchFeature Space Guidance for Breast Cancer Classification in DCE-MRI
arXiv:2609.32555v1 Announce Type: cross Abstract: Dynamic contrast enhanced breast MRI (DCE-MRI) is a powerful clinical tool for breast cancer detection, providing high resolution anatomical detail together with rich tem…