AI news archive.
10,659 articles filed under Research, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchBenthicDINO: Physics-Informed Self-Distillation for View-Invariant Side-Scan Sonar Representations
arXiv:2608.23215v2 Announce Type: replace-cross Abstract: Automated interpretation of side-scan sonar (SSS) imagery is traditionally hindered by view-dependence, as recorded intensities inextricably conflate intrinsic se…
- arXiv cs.AIresearchIndicDetect: Evaluating Cross-Lingual LLM-Generated Text Detection for Hindi, Telugu, and Tamil
arXiv:2608.29919v2 Announce Type: replace-cross Abstract: The rapid proliferation of LLMs has further heightened the need to develop dependable AI-generated text detection, especially beyond English. Nevertheless, curren…
- arXiv cs.AIresearchMind the Phase: Effective Rank and Representation Health in Legged Locomotion
arXiv:2609.06958v2 Announce Type: replace-cross Abstract: Reinforcement learning has become the leading paradigm in legged locomotion, enabling complex behaviors from backflips to parkour via massively parallel simulatio…
- arXiv cs.AIresearchGardenBench: A lightweight, daily evaluation of LLM capabilities
arXiv:2610.23866v1 Announce Type: new Abstract: We introduce GardenBench, a benchmark with 11 test suites that evaluate the capabilities of Large Language Models (LLMs) across a range of tasks. By systematically promptin…
- arXiv cs.AIresearchWhat Social Media Teaches Us About Accumulative AI Risks
arXiv:2610.24006v1 Announce Type: new Abstract: Prominent AI safety discussions emphasize existential threats and catastrophic events, such as AI-enabled nuclear conflict or engineered biological outbreaks. This position…
- arXiv cs.AIresearchBeyond Explicit Intent: Discovering and Shaping Artistic Intent through Human-AI Co-Creation
arXiv:2610.24010v1 Announce Type: new Abstract: Generative AI is becoming an important medium for artistic creation, yet existing interactions often assume that creators can specify intentions in advance and accurately c…
- arXiv cs.AIresearchUnified Multiparadigm Fusion Intelligence for Rare Disease Diagnosis
arXiv:2610.24024v1 Announce Type: new Abstract: Rare diseases (RDs) affect an estimated 300 million people globally, leaving patients to navigate a protracted diagnostic odyssey constrained by clinical scarcity and fragm…
- arXiv cs.AIresearchLogicVal:A Logic-Formalized Benchmark for Constraint Satisfaction in Text-to-Image Generation
arXiv:2610.24051v1 Announce Type: new Abstract: Text-to-Image (T2I) generative models have made significant progress in producing high-fidelity images from natural-language prompts. Alongside this progress, numerous benc…
- arXiv cs.AIresearchCache2LoRA: Understanding and Improving Context Internalization
arXiv:2610.24107v1 Announce Type: new Abstract: Context-to-LoRA methods encode documents as low-rank parameter updates, allowing language models to answer without retaining the source text in their decoding context. How…
- arXiv cs.AIresearchA Conditional No-Hair Theorem for Transformers: How Language Models Forget Their Prompt
arXiv:2610.24133v1 Announce Type: new Abstract: We ask how much an autoregressive transformer retains of its prompt after generating $t$ tokens. Consider two different prompts followed by the same continuation text, so t…
- arXiv cs.AIresearchTorchTPU - A Hybrid Eager/Compiled Architecture for Native PyTorch Execution on TPU
arXiv:2610.24161v4 Announce Type: replace Abstract: TorchTPU is an open-source collaboration between Google and Meta that introduces a native and principled PyTorch backend for Google TPUs. It enables seamless out-of-the…
- arXiv cs.AIresearchDistillation, Self-Training, and the Fragility of Learned Chemical Reasoning
arXiv:2610.24199v1 Announce Type: new Abstract: Automating synthesis planning for small-molecule drug design requires chemical reasoners that are accurate as well as open to inspection and adaptation, yet frontier langua…
- arXiv cs.AIresearchTraining-Free Prompt Selection for Efficient Reinforcement Learning With Partial Rollouts
arXiv:2610.24229v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has emerged as a prominent paradigm for training reasoning models, but its computational cost makes efficient data sel…
- arXiv cs.AIresearchProbing Ambiguity: Adversarial Intent Resolution for Robust Text-to-SQL
arXiv:2610.24248v1 Announce Type: new Abstract: Text-to-SQL systems typically assume a one-to-one mapping between natural-language queries and correct SQL translations. In practice, however, many queries are inherently a…
- arXiv cs.AIresearchCan Compact Open-Weight Large Language Models Recover Mobility Events from Incomplete Trajectories? A Controlled Evaluation Using Air Trips
arXiv:2610.24266v1 Announce Type: new Abstract: Incomplete mobility trajectories can obscure the observations needed to identify important travel events and their endpoints. This study evaluates whether compact, locally…
- arXiv cs.AIresearchFrom SEC Filings to Financial Signals: Evaluating LLMs on Stock Market Reactions and Analyst Forecasts
arXiv:2610.24268v1 Announce Type: new Abstract: Form 10-Q MD&A sections combine long-form management narrative with accounting and forward-looking information. Benchmarks for financial filings commonly evaluate question…
- arXiv cs.AIresearchCME-SpectrumBench: Can LLMs Analyze Condensed Matter Spectral Data?
arXiv:2610.24304v1 Announce Type: new Abstract: Large Language Models (LLMs) are presently well assessed by expert-level mathematics and physics benchmarks which focus on theoretical, symbolic reasoning. However, we lack…
- arXiv cs.AIresearchThe Judge Can Debias Itself: Awareness and Self-Debiasing for Reliable LLM-as-a-Judge
arXiv:2610.24320v1 Announce Type: new Abstract: LLM-as-a-Judge systems are increasingly employed for automated evaluation, yet remain susceptible to systematic biases that undermine their reliability. We demonstrate that…
- arXiv cs.AIresearchContinuous Ontology Assurance through External Resources -- An Ontology Engineering Method with a Case Study in Software Language Engineering
arXiv:2610.24322v1 Announce Type: new Abstract: Domain ontologies require review against knowledge recorded in evolving external resources. We propose COATER, a method that manages executable review components called arr…
- arXiv cs.AIresearchScreening LLM Judges Without Ground Truth: A Preliminary Evaluation of an AI Dental Hygiene Coach
arXiv:2610.24335v1 Announce Type: new Abstract: Evaluating a fine-tuned coaching model with expert graders is slow and expensive, and an LLM judge cannot be trusted without ground truth. We present a staged pipeline that…
- arXiv cs.AIresearchFlashRT-PAI: Fast Kernels Are Not Fast Pipelines for Physical AI Inference
arXiv:2610.24349v1 Announce Type: new Abstract: Vision-language-action (VLA), video-action (VA), and world action models (WAMs) form the backbone of modern physical AI systems, yet their real-time single-batch inference…
- arXiv cs.AIresearchDKnown-Jev: Fine-Tuning and Evaluation of a JEV-Style Model for Tasks Involving Normative Knowledge
arXiv:2610.24358v1 Announce Type: new Abstract: Tasks involving normative knowledge include concept interpretation, eligibility determination, procedure explanation, material requirements, and service-outcome assessment,…
- arXiv cs.AIresearchA Two-Stage Hybrid Framework for Inferring Air Trips from Mobile Location-based Service (LBS) Data under Incomplete Airport Sightings
arXiv:2610.24366v1 Announce Type: new Abstract: Mobile device location-based service (LBS) data provide large-scale spatiotemporal observations that can help airport planners understand air travelers' mobility patterns.…
- arXiv cs.AIresearchWAQS: Weight Absorption for Quadratic Probing and Affine Steering
arXiv:2610.24367v1 Announce Type: new Abstract: Activation steering provides a lightweight alternative to fine-tuning for controlling large language model behavior. Existing methods, however, often face a trade-off betwe…
- arXiv cs.AIresearchBeyond Next-Screen Prediction: The Decision Value of GUI World Models
arXiv:2610.24372v1 Announce Type: new Abstract: GUI world models are increasingly used to improve action selection by predicting the consequences of candidate actions, but it is unclear how much of the resulting gain com…
- arXiv cs.AIresearchTrust the Edge, Doubt the Arrow: Auditing Validation Signals for Text-Mined Clinical Causal Knowledge Graphs
arXiv:2610.24390v1 Announce Type: new Abstract: Clinical causal retrieval-augmented generation systems increasingly use knowledge graphs (KGs) mined from notes, yet extracted assertions remain candidates that require aud…
- arXiv cs.AIresearchMSCR: Jointly Balancing Utilization Across Modalities and Discovering Synergistic Information
arXiv:2610.24395v1 Announce Type: new Abstract: In multimodal learning, modality imbalance often lets one modality dominate optimization and keeps the model from fully exploiting cross-modal interactions. Balance-oriente…
- arXiv cs.AIresearchLearning to Compose: Recursive Self-Improvement of Shared Executable Stacks for Zero-Shot Long-Horizon Robot Manipulation
arXiv:2610.24464v1 Announce Type: new Abstract: Individually competent robot skills can fail when composed: tools may lack a required capability, completion signals may misrepresent physical progress, and one skill may l…
- arXiv cs.AIresearchPluralistic Alignment in Large Language Models: Objectives, Human References, and Preference Representations
arXiv:2610.24471v2 Announce Type: replace Abstract: Pluralistic alignment aims to represent meaningful variation in human preferences rather than collapse heterogeneous judgments into a single target. Yet existing work o…
- arXiv cs.AIresearchConCI: A Controlled Counterfactual Benchmark for Contextual Integrity in LLMs
arXiv:2610.24494v1 Announce Type: new Abstract: Contextual integrity (CI) holds that the appropriateness of sharing personal information depends on the context of the information flow, not on the information alone. Howev…
- arXiv cs.AIresearch$M^2Net$: Unifying Scale-Specific Structures and Prototype Decomposition for Spatial-Temporal Forecasting
arXiv:2610.24516v1 Announce Type: new Abstract: Spatial-temporal forecasting is pivotal for intelligent urban management yet remains challenging due to the intricate coupling of spatial dynamics and temporal non-stationa…
- arXiv cs.AIresearchAxiomatic World Modeling for Physics Reasoning
arXiv:2610.24519v1 Announce Type: new Abstract: Recent research-level physics-reasoning benchmarks for LLMs reveal a failure mode that lies not in knowledge or execution, but in modeling the world being reasoned about. M…
- arXiv cs.AIresearchComparing Sparsified MLPs and Transcoders: Many Transcoder Features Are Neurons in Disguise
arXiv:2610.24521v1 Announce Type: new Abstract: MLP neurons in transformer language models are widely understood to be polysemantic, motivating transcoders - sparse, learned approximations of MLP layers - as interpretabl…
- arXiv cs.AIresearchRethinking EEG Spatial Super-Resolution as Dynamic State Decomposition and Filtering
arXiv:2610.24528v1 Announce Type: new Abstract: EEG spatial super-resolution aims to recover high-density neural signals from sparse electrode observations. Existing methods have achieved substantial progress through spa…
- arXiv cs.AIresearchConcordance Plausibility Check for Intervention-Conditioned Human Digital Twins
arXiv:2610.24577v1 Announce Type: new Abstract: Intervention-conditioned human digital twins predict treatment alternatives that cannot be observed in the same patient. Ordinary predictive accuracy therefore cannot estab…
- arXiv cs.AIresearchCADS: Measuring the Incremental Contribution of LLM Proposers in Sequential Biological Screens
arXiv:2610.24597v1 Announce Type: new Abstract: Large language models are increasingly used to guide sequential biological screens, yet standard evaluations rely on raw hit counts that conflate a proposer's value with th…
- arXiv cs.AIresearchFrequency-Domain Membership Inference Does Not Beat Confidence Thresholding: A Band-Resolved Analysis of Why
arXiv:2610.24643v1 Announce Type: new Abstract: A widely repeated account of membership inference holds that models lean on fine-grained detail for samples they have memorized, so degrading an input's resolution should e…
- arXiv cs.AIresearchFrom Prediction to Action: Population Health World Model for Digital Medicine
arXiv:2610.24662v2 Announce Type: replace Abstract: Digital medicine now captures data that traces individual health trajectories and reveals population health dynamics through electronic health records, claims, remote m…
- arXiv cs.AIresearchMM-LeJEPA: Correlated Gaussian Regularization for Multimodal Joint-Embedding Predictive Architectures
arXiv:2610.24681v1 Announce Type: new Abstract: LeJEPA derives an isotropic Gaussian embedding target by minimizing, under its task assumptions, a Fisher information criterion that controls the task-averaged squared pred…
- arXiv cs.AIresearchVerifying Human-Written Reasoning References
arXiv:2610.24690v1 Announce Type: new Abstract: Evaluating the reasoning of AI systems often relies on human-written reasoning chains as references, yet the logical support for their individual steps is rarely verified.…
- arXiv cs.AIresearchSpherical Physics-informed Neural Operator with Multi-scale Coupling for Meteorological Downscaling
arXiv:2610.24708v1 Announce Type: new Abstract: Meteorological downscaling is crucial for high-resolution regional climate forecasting and disaster early warning. While neural operators have emerged as a promising paradi…
- arXiv cs.AIresearchSQuIREL: A Context-Relative Framework for Measuring Entity Richness in Wikidata
arXiv:2610.24709v1 Announce Type: new Abstract: Wikidata is a large, heterogeneous knowledge graph and applying data quality metrics requires context-specific approaches. The "richness" quality metric is currently under-…
- arXiv cs.AIresearchToward Collective Model Intelligence: Characterizing and Coordinating Models
arXiv:2610.24739v1 Announce Type: new Abstract: Independently developed AI models accumulate diverse and complementary capabilities, but a growing model collection does not automatically realize Collective AI. Addressing…
- arXiv cs.AIresearchAre We Evaluating VLM Token Pruning Right? Looking Beyond Accuracy and Token Count
arXiv:2610.24740v1 Announce Type: new Abstract: Visual token pruning aims to reduce inference cost while preserving the capabilities of the original VLM. Yet existing evaluations rely on aggregate task accuracy and retai…
- arXiv cs.AIresearchIndustrialCAD-1400: Benchmarking Detailed Industrial Assemblies from Text
arXiv:2610.24789v1 Announce Type: new Abstract: Industrial assemblies require more than a recognizable shape: functional parts, interfaces, dimensions and service features must satisfy a detailed request together. We int…
- arXiv cs.AIresearchMedical Fine-Tuning Reshapes, Not Reduces, Patient-Facing AI Risk: A Rubric-Based, LLM-Judge Evaluation Framework
arXiv:2610.24807v1 Announce Type: new Abstract: Patient-facing medical question answering with large language models (LLMs) is moving from research demonstrations to production deployments, yet evaluation remains anchore…
- arXiv cs.AIresearchPattern-Driven Evaluation of LLM Code Optimization: Isolating Compiler-Transcendent Semantic Reasoning
arXiv:2610.24835v1 Announce Type: new Abstract: Existing evaluations of LLM-based code optimization primarily measure end-to-end speedup, obscuring whether a model actually performs the intended optimization. For compile…
- arXiv cs.AIresearchA Cross-Domain Evaluation of Prompting Techniques for Large Language Models
arXiv:2610.24913v1 Announce Type: new Abstract: Prompt engineering has become a central mechanism for guiding the behavior of Large Language Models (LLMs) across a wide range of reasoning and language understanding tasks…
- arXiv cs.AIresearchMeans-Ends Analysis Helps LLMs Plan in Continuous-State Domains
arXiv:2610.24928v1 Announce Type: new Abstract: LLM planning research has traditionally focused on discrete-state domains, where actions form a finite, enumerable set. Existing LLM planning frameworks largely assume acti…
- arXiv cs.AIresearchLowNet: Looped Wavelet Neural Networks with 24 Learnable Parameters for Solving Poisson Equations
arXiv:2610.24941v1 Announce Type: new Abstract: Poisson equations frequently appear in various fields, such as mathematics, physics and informatics. Solving Poisson equation, however, is challenging. Traditional methods…