AI news archive.
10,659 articles filed under Research, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchSensor-Language-Action Models
arXiv:2610.08244v1 Announce Type: new Abstract: Sensors are useful not only for understanding the world but also for deciding what to do next. Existing sensor models however largely stop at perception: they recognize sta…
- arXiv cs.AIresearchLeanPlan: Optimal Planning with LLM-Generated Heuristics and Admissibility Proofs
arXiv:2610.08246v1 Announce Type: new Abstract: Frontier large language models (LLMs) can generate heuristic functions that guide search to achieve state-of-the-art performance in satisficing planning, where any plan is…
- arXiv cs.AIresearchzkLLMPoT: Efficient Zero Knowledge Proof of Training for Large Language Models
arXiv:2610.08258v2 Announce Type: replace Abstract: Auditing the claimed outcomes of large language model (LLM) training is challenging when model weights and training data are private, while cryptographically proving th…
- arXiv cs.AIresearchCoDe-LoRA: Mitigating the Orthogonality Dilemma in Continual Learning of LLMs via Knowledge Consolidation and Decoupling
arXiv:2610.08312v1 Announce Type: new Abstract: Continual learning (CL) is essential for Large Language Models (LLMs) to sequentially adapt to evolving tasks. To mitigate catastrophic forgetting, recent advances implemen…
- arXiv cs.AIresearchThe Standardization Trap: Certifying Joint Label Processing in Tabular Foundation Models
arXiv:2610.08314v1 Announce Type: new Abstract: Linear regression and kernel smoothing offer tractable explanations of in-context learning: in both, the features determine the weight assigned to each context label. Howev…
- arXiv cs.AIresearchAn AI-Assisted Formalization of the Poincar\'e Conjecture
arXiv:2610.08329v1 Announce Type: new Abstract: We present an AI-assisted Lean 4 formalization of the Poincar\'e conjecture. The project began with limited reusable formal infrastructure for the geometric analysis behind…
- arXiv cs.AIresearchMoF: Preference-Aware Mixture Modeling for Black-Box LLM Personalization
arXiv:2610.08330v1 Announce Type: new Abstract: Proprietary Large Language Models (LLMs) have demonstrated remarkable capabilities across a wide range of tasks, yet aligning their outputs with diverse user preferences re…
- arXiv cs.AIresearchExplainable Failure Prediction and Prevention in Maritime
arXiv:2610.08363v1 Announce Type: new Abstract: Maritime systems operate in highly dynamic environments where unexpected equipment failures can compromise safety, reliability, and operational efficiency. Recent advances…
- arXiv cs.AIresearchAssemState: Manual and Physical-State-Guided Reasoning for Zero-shot Furniture Assembly
arXiv:2610.08446v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have made significant progress in visual understanding, but precise 3D spatial reasoning integrated with physical environment remai…
- arXiv cs.AIresearchCylindrical Geodesic Flow Matching for Quasiperiodic Physiological Signal Transformation
arXiv:2610.08510v1 Announce Type: new Abstract: Paired translation between quasiperiodic physiological waveforms (i.e., recovering a target oscillatory signal from the source) is central to the interpretation of cardiova…
- arXiv cs.AIresearchToward Alignment Scaling Laws: A Framework and First Preregistered Measurements
arXiv:2610.08540v1 Announce Type: new Abstract: Whether alignment gets easier or harder as models grow is often argued from isolated findings, as if alignment were one property. We treat it as a family of measurable scal…
- arXiv cs.AIresearchAnyBottle: A Recipe to Only Keep the Concepts You Really Need
arXiv:2610.08552v1 Announce Type: new Abstract: Concept bottleneck models (CBMs) make predictions inspectable and intervenable by routing them through human-interpretable concepts, but originally required concept annotat…
- arXiv cs.AIresearchAdaptive Power Sampling for LLM Reasoning
arXiv:2610.08563v1 Announce Type: new Abstract: Sequence-level power sampling has recently emerged as a training-free approach to reasoning by sampling from a sharpened output distribution of a base large language model…
- arXiv cs.AIresearchParallel Predictive World Models for Accurate and Efficient Long-Horizon Planning
arXiv:2610.08627v1 Announce Type: new Abstract: Long-horizon world-model planning typically relies on autoregressive rollouts, where predicted states are repeatedly fed back into the model. This preserves temporal struct…
- arXiv cs.AIresearchVeriFine: Scaling Verification for Self-Improvement in Embodied Reasoning
arXiv:2610.08761v1 Announce Type: new Abstract: Self-improving policies continually expose new failure patterns, changing what their judges must be able to verify. However, current fixed judges constrain both optimizatio…
- arXiv cs.AIresearchSherpa: Teaching LLMs to Teach Adaptively
arXiv:2610.08778v1 Announce Type: new Abstract: Large language models (LLMs) have become increasingly capable problem solvers, but being able to solve a problem is not the same as being able to teach it. Existing approac…
- arXiv cs.AIresearchOncoNoteBERT: A Foundation Representation Model for Natural Language Processing of Real-World Outpatient Oncology Notes
arXiv:2610.03829v1 Announce Type: cross Abstract: Real-world outpatient oncology notes contain specialised terminology, tumour staging expressions, treatment names, toxicity descriptions, and institution-specific de-iden…
- arXiv cs.AIresearchHow Much Do LLM-as-a-Judge Design Choices Matter? A Systematic Comparison of Prompt Designs, Rating Scales, and Models
arXiv:2610.05094v1 Announce Type: cross Abstract: Researchers increasingly use Large Language Models as judges (LLM-as-a-judge) to evaluate model outputs. Yet there are no standards for how to design these judges. Typica…
- arXiv cs.AIresearchWhen Can World Models Recover Physical Laws?
arXiv:2610.06877v1 Announce Type: cross Abstract: Accurate prediction does not establish that a world model has recovered a physical law: distinct dynamics can generate identical records under the same observation protoc…
- arXiv cs.AIresearchNeutrosophic Ensemble Classification for Uncertainty-Aware Bearing Fault Detection: Evidence from Laboratory and Variable-Speed Industrial Benchmarks
arXiv:2610.06880v1 Announce Type: cross Abstract: Machine learning classifiers for bearing fault detection produce scalar confidence scores that conflate confident errors with genuinely ambiguous predictions, and the con…
- arXiv cs.AIresearchComparative review of hybrid forecasting models for short-term prediction of building thermal load
arXiv:2610.06881v2 Announce Type: replace-cross Abstract: In this paper, a comparative review of different hybrid models for short-term forecasting of building thermal demand is carried out. Particularly, the assessment…
- arXiv cs.AIresearchLearning When to Refine: Long-Horizon Reinforcement Learning for Budgeted Neural-Operator PDE Solvers
arXiv:2610.06883v1 Announce Type: cross Abstract: Neural operators provide fast surrogates for time-dependent PDEs, but autoregressive deployment creates a refinement-allocation problem: prediction errors vary over space…
- arXiv cs.AIresearchDynamical low-rank equilibrium computation for stochastic games between advanced persistent threats and moving target defense
arXiv:2610.06885v2 Announce Type: replace-cross Abstract: Moving target defense (MTD) against advanced persistent threats (APTs) in industrial control systems (ICS) has well-established game-theoretic formulations, but t…
- arXiv cs.AIresearchZero-Shot Visualization: Exploring Text Corpora with User-Prompted Axes
arXiv:2610.06889v1 Announce Type: cross Abstract: We study the application of large language models (LLMs) to the visual exploration of textual corpora. We introduce zero-shot visualization (ZSV), a task in which users s…
- arXiv cs.AIresearchAxiom Satisfiability of Linear Rewards in Alignment
arXiv:2610.06892v1 Announce Type: cross Abstract: Learning from human preference data is the dominant route to aligning language models with human values. In linear social choice, where rewards are linear in a fixed feat…
- arXiv cs.AIresearchComponent and Dimension Sparsity in Transformer Refusal Mechanisms
arXiv:2610.06903v1 Announce Type: cross Abstract: Activation steering manipulates large language model behavior by intervening on internal activations, but the mechanistic basis of these interventions remains poorly unde…
- arXiv cs.AIresearchAttSVD:Prompt-Adaptive Low-Rank KV Cache Compression via Attention-Guided SVD
arXiv:2610.06927v1 Announce Type: cross Abstract: The key-value (KV) cache of autoregressive transformers grows linearly with context length and dominates memory at long context. Most training-free remedies evict low-imp…
- arXiv cs.AIresearchLearning to Decide, Not to Reason: Parameter-Efficient Decision Operators via Low-Rank Activation Steering
arXiv:2610.06950v2 Announce Type: replace-cross Abstract: Injecting skills into a frozen language model currently costs a million parameters and a reinforcement-learning pipeline. We introduce DecSteer, a System-1 decisi…
- arXiv cs.AIresearchVisual-Invariance-Augmented Feature Optimal Alignment for Transferable Adversarial Attacks against Closed-Source MLLMs
arXiv:2610.06977v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) remain vulnerable to transferable adversarial examples, especially in black-box settings where only open-source surrogate models…
- arXiv cs.AIresearchCrystalJev: calibrated foundation-model probabilities decide what to compute next in materials discovery
arXiv:2610.06985v2 Announce Type: replace-cross Abstract: Atomistic foundation models screen hypothetical crystals by thresholding predicted energies, an output that states neither how likely a candidate is to be stable…
- arXiv cs.AIresearchDART-ES: Difficulty-Aware Reweighting and Targeted Replay for Fine-Tuning LLMs with Evolution Strategies
arXiv:2610.06993v1 Announce Type: cross Abstract: Evolution Strategies (ES) enable memory efficient full parameter fine-tuning of large language models (LLMs) using only forward computation. However, standard ES uniforml…
- arXiv cs.AIresearchTARE: Weigh a Never-Poisoned Twin Before Reading Backdoor-Defense Costs
arXiv:2610.06994v1 Announce Type: cross Abstract: Backdoor-defense leaderboards print a clean-accuracy drop and read it as removal cost. Measured on the poisoned victim alone, the drop cannot separate removal from what t…
- arXiv cs.AIresearchMask-Guided KV Cache Eviction in Block Diffusion Language Models
arXiv:2610.06996v1 Announce Type: cross Abstract: Block diffusion language models keep a large key-value (KV) cache throughout generation and attend to it at every denoising step, limiting both memory capacity and genera…
- arXiv cs.AIresearchWhere Does the Audio Jailbreak Live? A Controlled Frequency-Depth Audit of AdvWave-P on Qwen2-Audio
arXiv:2610.07005v1 Announce Type: cross Abstract: We audit frequency and decoder-depth claims for AdvWave-P, an additive audio jailbreak, on Qwen2-Audio. The protocol masks frequency components of the perturbation in the…
- arXiv cs.AIresearchWhich Image Property Carries the Jailbreak? A Controlled Dissection of Image-to-Text Jailbreaks
arXiv:2610.07009v1 Announce Type: cross Abstract: Image-to-text jailbreaks place harmful intent in text, image content, or the relationship between them. We examine image-side factors across four published attack familie…
- arXiv cs.AIresearchAnchor and Adapt: Asymmetric Prompt Adaptation for Few-Shot Industrial Anomaly Detection
arXiv:2610.07016v1 Announce Type: cross Abstract: In few-shot industrial anomaly detection, the few normal target images provide no direct defect supervision, making anomaly prompts difficult to learn from these samples…
- arXiv cs.AIresearchAn Empirical Fault Vulnerability Exploration of ReRAM-based Process-in-Memory CNN Accelerators
arXiv:2610.07029v1 Announce Type: cross Abstract: Resistive random-access memory (ReRAM)-based Processing-in-Memory (PIM) accelerator is a promising platform for processing massively memory intensive matrix-vector multip…
- arXiv cs.AIresearchInvestigating Model Compression for Neural Machine Translation in the Biomedical Domain
arXiv:2610.07032v1 Announce Type: cross Abstract: Large-scale pretrained transformer models have achieved state-of-the-art performance across diverse machine translation tasks, including multilingual settings. Knowledge…
- arXiv cs.AIresearchTRIAGE: Direction-Aware Mismatch Stabilization of Native NVFP4 Reinforcement Learning
arXiv:2610.07043v2 Announce Type: replace-cross Abstract: Low-precision execution can substantially accelerate reinforcement learning (RL) for large language models, but discrepancies between learner and sampler executio…
- arXiv cs.AIresearchLearning to Simulate Individuals from Macro Social Signals
arXiv:2610.07062v1 Announce Type: cross Abstract: Large language models are increasingly used to simulate how individuals respond to new situations, yet the behavioral reasoning behind these responses is either inherited…
- arXiv cs.AIresearchDemo: Vision-Language Model-Guided Online Calibration of an Electromagnetic Digital Twin
arXiv:2610.07081v2 Announce Type: replace-cross Abstract: An electromagnetic (EM) digital twin gives mobile robots wireless situational awareness but depends on material conductivities that change with the environment. O…
- arXiv cs.AIresearchGraph-Based Recognition of Simulated Train-Driver States From Facial and Upper-Body Keypoints
arXiv:2610.07083v2 Announce Type: replace-cross Abstract: Driver fatigue poses a significant challenge to railway safety, with traditional systems like the dead-man switch offering limited and basic alertness checks. Thi…
- arXiv cs.AIresearchT-CCL: Resource Efficient and Performant Collective Communication using Tensor Memory Accelerator
arXiv:2610.07098v1 Announce Type: cross Abstract: Large transformer-based models increasingly depend on multi-GPU execution, which requires frequent collective communication among GPUs. Existing communication libraries o…
- arXiv cs.AIresearchMuon Is Theoretically Wrong For Convolutions, But Empirically Effective
arXiv:2610.07103v1 Announce Type: cross Abstract: Muon, an optimizer known for its efficiency, has a clear interpretation for matrix-valued updates, but convolutional kernels are stored as four-dimensional tensors. Stand…
- arXiv cs.AIresearchBeyond Successor Accuracy: State Retention for Recursive Self-Improvement in Recommendation
arXiv:2610.07105v1 Announce Type: cross Abstract: Recommendation recursive self-improvement (Rec-RSI) feeds recommender outputs into subsequent training. Evaluating each round solely through its latest model assumes that…
- arXiv cs.AIresearchLiLib: Lifelong Air-to-Ground Path-Loss Prediction on UAVs via a Drift-Triggered Model Library
arXiv:2610.07111v1 Announce Type: cross Abstract: UAVs that act as relays or base stations need accurate air-to-ground path-loss predictions for rate adaptation and placement, but propagation conditions change as a UAV m…
- arXiv cs.AIresearchWill the Judge Flip? Predicting Position-Sensitive LLM Judgments from Residual Stream Activations
arXiv:2610.07115v1 Announce Type: cross Abstract: The order in which candidate responses are presented can change an LLM judge's verdict. Detecting such a position flip ordinarily requires judging each pair in both order…
- arXiv cs.AIresearchJailbreaking Open-Weight LLMs via Random Embedding Perturbations
arXiv:2610.07125v1 Announce Type: cross Abstract: While open-weight models have enjoyed steady progress in capabilities and wide adoption across multiple domains, their safety remains an important concern. One key featur…
- arXiv cs.AIresearchPlaySuite: A Large-Scale Benchmark for Interactive Visual Intelligence
arXiv:2610.07127v1 Announce Type: cross Abstract: Recent advances in multimodal foundation models yield strong performance on static perception and reasoning benchmarks, yet such evaluations largely overlook a central as…
- arXiv cs.AIresearchAggregating User Preferences while Ensuring Equity, Diversity, and Inclusion using Graph Summarization
arXiv:2610.07128v1 Announce Type: cross Abstract: Aggregating the preferences of diverse user groups into a collective outcome raises fundamental challenges of equity, diversity, and inclusion (EDI): classical aggregatio…