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  1. arXiv cs.AIresearch
    SLEM: Spectrum-Aware Latent Expert Merging

    arXiv:2610.16484v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models scale model capacity efficiently by activating only a small subset of experts for each input, while still requiring all parameters to be s…

  2. arXiv cs.AIresearch
    Growing and Transferring Pathways for LLM Reinforcement Learning

    arXiv:2610.16489v1 Announce Type: cross Abstract: Reinforcement learning (RL) can substantially improve the reasoning capabilities of large language models, but an effective training run requires considerable resources.…

  3. arXiv cs.AIresearch
    pi-Net: Empirical Latent Representations for Differentiable Physics Heads in Data-Scarce Systems

    arXiv:2610.16504v1 Announce Type: cross Abstract: Developing reliable predictive models for multi-physics systems often forces a compromise between computationally demanding physical simulators and data-hungry, opaque ma…

  4. arXiv cs.AIresearch
    PatTransBench: an ipc-stratified, multi-dimensional benchmark for patent machine translation evaluation

    arXiv:2610.16538v1 Announce Type: cross Abstract: We present PatTransBench, a 12,000-item Chinese-English/Japanese/Korean patent machine translation (PatMT) benchmark with a four-dimensional evaluation protocol. The benc…

  5. arXiv cs.AIresearch
    Heuristics are Not Enough: Calibrated and Corrected Caching for Video Diffusion Acceleration

    arXiv:2610.16545v1 Announce Type: cross Abstract: Feature caching has become a mainstream training-free strategy for accelerating video diffusion models by reusing intermediate outputs across denoising steps. However, ex…

  6. arXiv cs.AIresearch
    VLA-GAUGE: Systematically Evaluating Generalization and Robustness in Vision-Language-Action Models

    arXiv:2610.16567v1 Announce Type: cross Abstract: Vision-Language-Action models (VLAs) have achieved high success rates on familiar manipulation tasks, yet it remains unclear whether such scores reflect genuine zero-shot…

  7. arXiv cs.AIresearch
    Towards Modality-Agnostic Seizure Classification: A Unified Deep Learning Framework for Heterogeneous EEG and Intracranial EEG Signals

    arXiv:2610.16596v2 Announce Type: replace-cross Abstract: Seizure prediction and detection, essential for clinical treatment of epilepsy, remain the crucial task of this neurological disease. EEG and iEEG are widely used…

  8. arXiv cs.AIresearch
    MixLID: Token-Level Language Identification in Mixed-Language Text

    arXiv:2610.16601v1 Announce Type: cross Abstract: Processing multilingual text requires both identifying a broad range of languages and distinguishing the language of each token in inputs containing multiple languages. W…

  9. arXiv cs.AIresearch
    Answer It or Not? Towards Prompt-Adapted Adversarial Images on Vision Language Models

    arXiv:2610.16622v1 Announce Type: cross Abstract: With the advancement in language modeling, research on adversarial images has recently shifted from image classifiers to vision-language models (VLMs). Despite the new, t…

  10. arXiv cs.AIresearch
    Integrating Feature Understandability into Feature Selection for Human-Centred Tabular Explanations

    arXiv:2610.16627v1 Announce Type: cross Abstract: Existing human-centred XAI research predominantly evaluates explanations after they have been generated. However, this fails to provide actionable insights into improving…

  11. arXiv cs.AIresearch
    AeroChem: Closed-loop Physics-Informed State Space Modeling for Long-term Chemically-Reactive Air Quality Forecasting--Extended Version

    arXiv:2610.16630v1 Announce Type: cross Abstract: Accurate long-term air quality forecasting is challenging due to long-range transport, meteorological variability, and nonlinear chemical reactions underlying secondary p…

  12. arXiv cs.AIresearch
    REEL: Learning to Retrieve, Evaluate, and Evolve Visual Memory for Any Long-Horizon Multi-Shot Video Generation

    arXiv:2610.16632v1 Announce Type: cross Abstract: Memory-based long-video generation aims to combine user control with long-range visual consistency. We organize this process into three functional components: a planner,…

  13. arXiv cs.AIresearch
    SuPER-Mamba: Surprisal Prioritization for Extended-Context Routing in Mamba

    arXiv:2610.16636v1 Announce Type: cross Abstract: State space models provide efficient linear-complexity processing for long sequences, but their performance frequently degrades as context length grows. We propose SuPER-…

  14. arXiv cs.AIresearch
    Learning Incompressible 3D Flows from Sparse Samples: A Set Transformer Approach to Divergence-Free Kernel Fitting

    arXiv:2610.16645v1 Announce Type: cross Abstract: Recovering divergence-free velocity fields from sparse and corrupted observations requires reconciling physical consistency, expressive representations, and robustness to…

  15. arXiv cs.AIresearch
    Feature-Context Consistency: Unsupervised Adversarial Detection with Drift Stability on Attributed Graphs

    arXiv:2610.16694v1 Announce Type: cross Abstract: Adversarial detection on evolving attributed graphs faces two challenges: fraud labels arrive late or not at all, and natural distributional drift erodes any trained deci…

  16. arXiv cs.AIresearch
    VAttnPO: Visual Attention-Guided Policy Optimization

    arXiv:2610.16735v1 Announce Type: cross Abstract: Multimodal reinforcement learning with verifiable rewards commonly assigns one sequence advantage to an entire response. This outcome-level signal distinguishes overall r…

  17. arXiv cs.AIresearch
    Before Attention Sinks Form: Hidden-State Geometry Reveals and Modulates Their Formation

    arXiv:2610.16745v1 Announce Type: cross Abstract: Attention sinks are usually studied after they have formed. We ask whether a measurable hidden-state change appears beforehand and whether changing that geometry alters w…

  18. arXiv cs.AIresearch
    Relational Learning as World Modeling

    arXiv:2610.16763v1 Announce Type: cross Abstract: Relational learning typically predicts from a database state, but decision making asks a different question: how will that state change under an action? In operational sy…

  19. arXiv cs.AIresearch
    InfoVis: Unified Slide Image Generation and Editing

    arXiv:2610.16784v1 Announce Type: cross Abstract: Generating and editing presentation slides requires models to combine accurate text rendering, instruction following, visual grounding, aesthetic design, and precise edit…

  20. arXiv cs.AIresearch
    Logit Leakage through Floating-Point Bias Addition

    arXiv:2610.16790v1 Announce Type: cross Abstract: Language model APIs can expose token-specific biases while withholding logits and token probabilities. Existing bias-based extraction recovers relative logits, leaving a…

  21. arXiv cs.AIresearch
    StableJudge: A Lightweight Adversarial Defense Framework for LLM-as-a-Judge

    arXiv:2610.16814v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as judges to assign scalar scores that drive downstream decision-making, including tasks such as paper review and recom…

  22. arXiv cs.AIresearch
    Growing to See: Efficient Pretraining of Self-Supervised Vision Transformers

    arXiv:2610.16817v1 Announce Type: cross Abstract: Progressive depth growth builds large networks by starting with shallow models and inserting layers during training. Recent advances in large language models have renewed…

  23. arXiv cs.AIresearch
    DTA-GT: Direction- and Topology-Aware Graph Transformer for Neural Network Representation Learning

    arXiv:2610.16822v1 Announce Type: cross Abstract: Architecture attribute predictors reduce the cost of neural architecture search by estimating accuracy or latency from a small set of evaluated candidates. The key diffic…

  24. arXiv cs.AIresearch
    Unsupervised Data Drift Monitoring for Deployed Deepfake Speech Detectors

    arXiv:2610.16826v1 Announce Type: cross Abstract: Deepfake speech detectors are typically evaluated as binary classifiers on fixed benchmarks, but deployed systems face evolving attacks, codecs, speakers, and recording c…

  25. arXiv cs.AIresearch
    A Scaled-Up Empirical Study of Syntactic Language Models

    arXiv:2610.16837v1 Announce Type: cross Abstract: Syntactic language models (SLMs) that generate sentences along with their syntactic tree structures have shown promise in both syntactic generalization and downstream tas…

  26. arXiv cs.AIresearch
    Few-for-Many Best-Arm Identification in Multi-Objective Bandits

    arXiv:2610.16840v1 Announce Type: cross Abstract: Real-world systems often serve many objectives but can deploy only a few options, whose performance must be learned from noisy feedback. Modeling each option as an arm in…

  27. arXiv cs.AIresearch
    Towards Cost-Efficient Video Dataset Construction with Large Language Models

    arXiv:2610.16857v1 Announce Type: cross Abstract: Research on video classification models has witnessed significant growth recently, accompanied by a significant increase in the demand for datasets to train such models.…

  28. arXiv cs.AIresearch
    Comparing GenAI to Machine Learning and Manual Review for eDiscovery

    arXiv:2610.16925v3 Announce Type: replace-cross Abstract: Keeling et al. [Keeling2026Generative] report on a case study recently conducted by Redgrave LLP in which they assert that Relativity's Generative AI Review tool…

  29. arXiv cs.AIresearch
    KNN Implementation Details Can Dramatically Change Performance: An Example from Cover Trees

    arXiv:2610.16940v1 Announce Type: cross Abstract: Nearest neighbor search algorithms are widely used and have a long history, but we find that key implementation details are seldom reviewed in articles about them. These…

  30. arXiv cs.AIresearch
    UA-Bench: Benchmarking Large Audio-Language Models on Underwater Acoustic Recognition

    arXiv:2610.16942v1 Announce Type: cross Abstract: Large audio-language models (LALMs) are fast becoming a general interface to sound, yet how far their broad pretraining carries into specialized domains remains largely o…

  31. arXiv cs.AIresearch
    Social Priors: Descriptions of AI Users Shape How Language Models Trust and Cooperate

    arXiv:2610.16946v1 Announce Type: cross Abstract: Descriptions of how people use AI are becoming training data for the next generation of models. We ask whether what a model reads about its users changes how it treats pe…

  32. arXiv cs.AIresearch
    SarcasTraps: Effect of Sarcasm on Turkish Hate Speech Detection

    arXiv:2610.16957v1 Announce Type: cross Abstract: Standard hate speech detection datasets often emphasize explicit harmful language, but directed harm can also be expressed indirectly, without clearly hateful wording. Sa…

  33. arXiv cs.AIresearch
    Proactive Physical AI through Continuous Observation and Timely Intervention

    arXiv:2610.16967v1 Announce Type: cross Abstract: Physical AI is commonly formulated around an explicitly specified task: given a goal or instruction, a system perceives, reasons, and acts. In many real-world settings, h…

  34. arXiv cs.AIresearch
    The Value of Being Wrong: Self-Mined Visual In-Context Learning from Errors

    arXiv:2610.16977v1 Announce Type: cross Abstract: Visual in-context learning (ICL) enables vision-language models (VLMs) to adapt at test time via demonstration examples, but its effectiveness depends critically on the e…

  35. arXiv cs.AIresearch
    WeGR: Towards Unified Generative Retrieval via Behavior-aware Tokenization and Preference Alignment

    arXiv:2610.16979v3 Announce Type: replace-cross Abstract: Generative retrieval (GR) offers a promising paradigm for industrial search by unifying candidate generation within an autoregressive framework. However, effectiv…

  36. arXiv cs.AIresearch
    From Suboptimal to Optimal: One-Step Latent Flow Policies for Offline Reinforcement Learning

    arXiv:2610.16984v1 Announce Type: cross Abstract: Offline reinforcement learning aims to learn effective policies from fixed datasets without environment interaction. Although generative models such as diffusion and flow…

  37. arXiv cs.AIresearch
    TabGift: A Context-Efficient Foundation Model for Tabular Data Generation

    arXiv:2610.16990v1 Announce Type: cross Abstract: Tabular data generation aims to synthesize realistic samples from limited observations while faithfully capturing the underlying data distribution. Tabular foundation mod…

  38. arXiv cs.AIresearch
    Governing Copyright Responsibly in the Era of Generative AI

    arXiv:2610.17002v1 Announce Type: cross Abstract: Large language models are trained on collections that may include scholarly works, while authors generally lack work-level information about whether and how their works w…

  39. arXiv cs.AIresearch
    MAGNET: Manifold-Aware Graph Diffusion Network for Connectome Generation

    arXiv:2610.17014v2 Announce Type: replace-cross Abstract: Functional brain connectome represents neural connectivity as a matrix of pairwise interactions between brain regions. Generation of functional connectomes is not…

  40. arXiv cs.AIresearch
    ProbabilityBench: Model Evaluation and Calibration with Exact Ground-Truth Uncertainty

    arXiv:2610.17016v1 Announce Type: cross Abstract: Evaluating model uncertainty on real-world data is challenging because each instance provides only a single observed label, leaving true conditional class probabilities u…

  41. arXiv cs.AIresearch
    SPLICE: Sparse Physics Library Identification and Compositional Expansion

    arXiv:2610.17029v1 Announce Type: cross Abstract: Neural operator splitting composes a library of neural operators, one per physical mechanism, into zero-shot simulators of new equations. Existing approaches, however, re…

  42. arXiv cs.AIresearch
    Gradient Routing Localizes and Removes Unintended Behaviors in RL

    arXiv:2610.17062v1 Announce Type: cross Abstract: We propose a mitigation to reward hacking in reinforcement learning. Our setup involves a misspecified reward function that gives rise to unintended behavior, and a monit…

  43. arXiv cs.AIresearch
    Superintelligence and the Triple Risk of an AI Race

    arXiv:2610.17085v1 Announce Type: cross Abstract: On many estimates, artificial general intelligence (AGI) is likely to emerge within the next few decades or even sooner. Once it does, it may quickly surpass human intell…

  44. arXiv cs.AIresearch
    What the Machine Invented: Mining New Mathematical Instruments from OpenAI's October 2026 Release of AI-Generated Mathematics

    arXiv:2610.17090v1 Announce Type: cross Abstract: On 6 October 2026 OpenAI published an initial 722 AI-written mathematical manuscripts, organized into 372 problem families, in the public repository github.com/openai/mat…

  45. arXiv cs.AIresearch
    AIPOCH Open-Science: An Open-Source AI Research Workbench with Reproducible .science Packages

    arXiv:2610.17110v1 Announce Type: cross Abstract: AI-assisted research leaves instructions, computations, artifact revisions and checks whose relationships matter when another researcher receives the work. We present AIP…

  46. arXiv cs.AIresearch
    Calibrated Typed Decisions for Entity, Relation, and Event Extraction

    arXiv:2610.17113v1 Announce Type: cross Abstract: Information extraction models often perform well on the datasets they are trained on, but transferring to new domains and annotation guidelines remains challenging. Suppo…

  47. arXiv cs.AIresearch
    D-World: An Explicit World-Language-Action Model with Recursive Self-Improvement under Dual Control

    arXiv:2610.17114v1 Announce Type: cross Abstract: Frontier large language models (LLMs) now reason about space well enough to program robots, yet the world models behind robot policies are implicit, held in network weigh…

  48. arXiv cs.AIresearch
    D2: High-Capability Full-Duplex Spoken Language Models from Half-Duplex Backbones

    arXiv:2610.17124v1 Announce Type: cross Abstract: Full-duplex spoken language models (FD-SLMs) support simultaneous listening and speaking, but often lag behind half-duplex spoken language models (HD-SLMs) in general cap…

  49. arXiv cs.AIresearch
    SonicWorld: Source-Centric Latent Dynamics for Spatial Audio Reasoning

    arXiv:2610.17131v3 Announce Type: replace-cross Abstract: Dynamic spatial audio reasoning requires a model to associate changing acoustic observations with the correct source and recover its spatial state at a queried ti…

  50. arXiv cs.AIresearch
    Force-Modulated Dexterity: Unified Compliance for Contact-Rich Manipulation

    arXiv:2610.17161v1 Announce Type: cross Abstract: Teleoperation is widely used to collect high-quality demonstrations for robot learning. Dexterous manipulation, however, requires coordinated control of motion and contac…