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  1. arXiv cs.AIresearch
    PPAD-Completeness of Contiguous Envy-Free Cake Cutting with Additive Valuations

    arXiv:2610.19690v1 Announce Type: cross Abstract: We prove that computing a complete contiguous $\varepsilon$-envy-free cake allocation is PPAD-complete for normalized rational piecewise-constant additive valuations. The…

  2. arXiv cs.AIresearch
    SceneAE: Scene Generation and Reconstruction in Queryable 3D-Anchored Latent Space

    arXiv:2610.19708v1 Announce Type: cross Abstract: Recent video world models have increasingly adopted 3D memory mechanisms to integrate historical observations into a lightweight and persistent scene representation. This…

  3. arXiv cs.AIresearch
    ONCship: A Large-Scale Underwater Acoustic Corpus for Ship Recognition

    arXiv:2610.19722v1 Announce Type: cross Abstract: Recent advances in deep learning have significantly improved underwater acoustic vessel recognition. However, existing publicly available datasets are typically limited i…

  4. arXiv cs.AIresearch
    Recognizing Dialogue Ambiguity via Candidate Set Visual Grounding

    arXiv:2610.19723v1 Announce Type: cross Abstract: Interpreting an ambiguous utterance in real-world interactions often requires context beyond a single utterance. When the utterance refers to objects in a visual scene, i…

  5. arXiv cs.AIresearch
    Mitigating Video Hallucinations via Attention-Guided Representation Perturbation

    arXiv:2610.19728v1 Announce Type: cross Abstract: Video large language models (Video LLMs) often generate responses unsupported by the input video. Contrastive decoding (CD) can mitigate these hallucinations, but its eff…

  6. arXiv cs.AIresearch
    ProtModernBERT: Compute-Efficient Protein Language Modeling

    arXiv:2610.19738v1 Announce Type: cross Abstract: Large protein language models provide a powerful framework for learning sequence-function relationships and guiding experimental design. However, architectural improvemen…

  7. arXiv cs.AIresearch
    Does the Linguistic Register of Thinking Matter? Wenyan as a Compact Reasoning Register for Chinese LLMs

    arXiv:2610.19741v1 Announce Type: cross Abstract: Visible reasoning traces of Chinese reasoning-oriented LLMs are typically written in modern vernacular Chinese, which may be verbose under limited decoding budgets. We as…

  8. arXiv cs.AIresearch
    LiFi: LiDAR Generation from Multi-View Images via Geometric and Semantic Collaborative Guidance

    arXiv:2610.19786v1 Announce Type: cross Abstract: Generating LiDAR point clouds from multi-view camera images is a valuable task with applications in controllable data synthesis, cross-modal simulation and various percep…

  9. arXiv cs.AIresearch
    StateCraft: Augmenting Video World Models with Abstract-State Reasoning

    arXiv:2610.19795v1 Announce Type: cross Abstract: Video world models aim to simulate complex environments with realistic appearance and dynamics. Maintaining consistency over long interactions requires tracking past acti…

  10. arXiv cs.AIresearch
    VaryST: Generalizable Spatio-Temporal Forecasting Beyond the Closed-World Setting

    arXiv:2610.19813v1 Announce Type: cross Abstract: Spatio-temporal forecasting is fundamental to many real-world systems, yet deployment environments are inherently varying: temporal distributions may evolve, spatial doma…

  11. arXiv cs.AIresearch
    Memory-Efficient Subspace Optimization with Residual Correction: From Momentum SGD to Muon

    arXiv:2610.19844v1 Announce Type: cross Abstract: Memory-efficient subspace optimization has emerged as a practical approach to reducing the memory cost of LLM training while preserving optimization performance. Previous…

  12. arXiv cs.AIresearch
    Lost in the Fallback: How Reliably Do Typed Decision Models Use Fallback Options?

    arXiv:2610.19856v1 Announce Type: cross Abstract: Typed decision models (TDMs) are increasingly used in applications such as request routing and model selection, making reliable decisions critical to system performance.…

  13. arXiv cs.AIresearch
    Rationale Distribution Distillation via Flow Matching for Distributional Continuous Latent Reasoning

    arXiv:2610.19871v1 Announce Type: cross Abstract: Sampling multiple chain-of-thought rationales from a language model can uncover correct solutions missed by a single attempt. However, these rationales are typically leng…

  14. arXiv cs.AIresearch
    Neural Wasserstein Splines: Representation-Invariant Second-Order Priors for Trajectory Inference

    arXiv:2610.19878v1 Announce Type: cross Abstract: Population dynamics are often observed only as unpaired snapshots, which leave the evolution between measurements underdetermined. Second-order regularization can constra…

  15. arXiv cs.AIresearch
    Frustratingly Easy Majority Voting Using Length Conditioning

    arXiv:2610.19890v1 Announce Type: cross Abstract: Majority Voting (MV) is a simple and widely used strategy which improves the reasoning accuracy of Large Language Models (LLMs) by allocating additional inference-time co…

  16. arXiv cs.AIresearch
    DeepPV-MRF: End-to-End Partial-Volume Fraction Estimation from MR Fingerprinting Time Series

    arXiv:2610.19894v1 Announce Type: cross Abstract: Background: Estimating subvoxel tissue fractions from magnetic resonance fingerprinting (MRF) is challenging. Conventional dictionary matching and segmentation pipelines…

  17. arXiv cs.AIresearch
    Universal Sample-Based Embeddings of Higher-Order Objects

    arXiv:2610.19899v1 Announce Type: cross Abstract: Neural networks operate naturally on finite-dimensional vectors, yet many problems require reasoning about higher-order objects such as distributions, functions, and grap…

  18. arXiv cs.AIresearch
    Multimodal Medical Image Parsing with Task-Specific Low-Rank Adapters

    arXiv:2610.19901v1 Announce Type: cross Abstract: Adapting a single vision-language model to medical image parsing requires training choices that reflect the demands of each task. We study task-specific adaptation with Q…

  19. arXiv cs.AIresearch
    MUCO: A Mani-Unit-Structured Manipulation Framework for Compositional Long-Horizon Robot Tasks

    arXiv:2610.19913v1 Announce Type: cross Abstract: Learning and executing long-horizon robot manipulation as complete task trajectories raises data-collection costs, lim?its capability reuse, and causes local failures to…

  20. arXiv cs.AIresearch
    Does Machine Translation Retain Media Bias?

    arXiv:2610.19945v1 Announce Type: cross Abstract: Within the most recent two decades, machine translation (MT) has been advanced from a research area to a mature, deployed technology for prose text and most language pair…

  21. arXiv cs.AIresearch
    Learning Graph Energies for Finite-Time Generation

    arXiv:2610.19946v1 Announce Type: cross Abstract: Energy-based models can represent distributions over discrete structures such as molecular graphs, but an energy that is accurate at equilibrium need not yield accurate s…

  22. arXiv cs.AIresearch
    Quiet Triggers, Loud Footprints: A Tri-Space Measurement Study of Backdoor Stealthiness

    arXiv:2610.19947v1 Announce Type: cross Abstract: Backdoor attacks on deep neural networks are commonly evaluated by attack success rate and benign accuracy, yet their stealthiness remains inconsistently defined and meas…

  23. arXiv cs.AIresearch
    Safe-FCL: Continual Risk Awareness and Fine-Grained Safety Aggregation for Federated Continual Learning of LLMs

    arXiv:2610.19968v1 Announce Type: cross Abstract: Federated fine-tuning enables large language models (LLMs) to learn collaboratively from distributed client data, but malicious client updates can compromise global model…

  24. arXiv cs.AIresearch
    Empirical Boundaries of Reservoir Computing for Few-Shot Sequence Pattern Tasks

    arXiv:2610.19997v1 Announce Type: cross Abstract: Efficient sequence modeling remains a fundamental challenge in machine learning. Despite the success of Transformers, recurrent neural networks (RNNs) have recently re-em…

  25. arXiv cs.AIresearch
    A Strong Harness Narrows the Model Gap: A Comparative Evaluation for Legislative Document-to-XML Conversion

    arXiv:2610.19999v1 Announce Type: cross Abstract: Legal-content reproduction requires matching the source exactly in section hierarchy, verbatim text, citations, and amendment spans; a dropped citation or mislabeled amen…

  26. arXiv cs.AIresearch
    Provable Transformer Context Compression for In-Context Reinforcement Learning

    arXiv:2610.20004v1 Announce Type: cross Abstract: Transformers can perform in-context reinforcement learning without parameter updates. However, existing theoretical constructions often require context sizes that grow wi…

  27. arXiv cs.AIresearch
    On the Convergence of Semi-Gradient TD: A Mean Field Perspective

    arXiv:2610.20014v1 Announce Type: cross Abstract: Semi-gradient temporal-difference learning is a core algorithmic component of reinforcement learning, but bootstrapping with function approximation generally induces a no…

  28. arXiv cs.AIresearch
    MorphAct: Robot Policies Morphing with the Worlds They Act In

    arXiv:2610.20019v1 Announce Type: cross Abstract: Progress toward general intelligence in the physical world requires scaling robot learning across diverse environments and interactions. However, existing robot policies…

  29. arXiv cs.AIresearch
    SWE-Nexus: Automated Composition of Software Engineering Tasks from Test Execution

    arXiv:2610.20038v2 Announce Type: replace-cross Abstract: Historical code changes provide convenient task boundaries, but do not identify which production functions selected tests exercise or support composing validated…

  30. arXiv cs.AIresearch
    FoveaVLA: Foveation Actions Replace the Wrist Camera in VLAs

    arXiv:2610.20064v2 Announce Type: replace-cross Abstract: We present FoveaVLA, a Vision-Language-Action (VLA) model that replaces the wrist camera with learned foveation actions. Wrist cameras provide close-up detail but…

  31. arXiv cs.AIresearch
    Which Knowledge Should LLMs Trust? Uncovering a Generalizable Steering Direction Across Knowledge Conflicts

    arXiv:2610.20067v1 Announce Type: cross Abstract: Large Language Models (LLMs) frequently encounter conflicts between internal parametric knowledge and external contextual knowledge, yet the mechanisms governing this sel…

  32. arXiv cs.AIresearch
    Trainable at Depth, Solvable at Small Size: What the Loss Surface of a Polynomial Activation Dictates for Designing, Initializing and Training Networks

    arXiv:2610.20069v1 Announce Type: cross Abstract: What makes a deep network train, and what shape is its loss surface? We answer both with one construction at two scales: a polynomial activation f (z) = z + {\lambda}z 3…

  33. arXiv cs.AIresearch
    Rethinking Prediction Horizons: Decoupling Model Queries from State Updates in Few-Step MeanFlow

    arXiv:2610.20071v1 Announce Type: cross Abstract: MeanFlow predicts interval-average velocities, but conventional few-step sampling ties the interval queried from the model to the duration of the state update. We separat…

  34. arXiv cs.AIresearch
    AFCS: Atomic-Fact-Conditioned Synthesis for Factual Knowledge Pretraining

    arXiv:2610.20086v1 Announce Type: cross Abstract: Synthetic data is increasingly used in language-model pretraining. Existing knowledge-corpus synthesis pipelines, including WRAP and Nemotron-CC, usually take a source pa…

  35. arXiv cs.AIresearch
    From Spectral to Frobenius: When Muon Loses Its Spectral Implicit Bias

    arXiv:2610.20112v1 Announce Type: cross Abstract: Prior work on implicit bias shows that gradient descent selects the Frobenius max-margin direction on linearly separable problems, whereas Fan et al. (2025) established s…

  36. arXiv cs.AIresearch
    ACR-Net: Mitigating Semantic Dominance via Contrastive Acoustic-Semantic Decoupling

    arXiv:2610.20114v1 Announce Type: cross Abstract: Speech Emotion Recognition (SER) models and Audio LLMs fail when vocal tone contradicts textual semantics. Extensive training on congruent data engenders a rigid semantic…

  37. arXiv cs.AIresearch
    DreamHMR: From Video Generation to Human Motion Modeling via Structural Focusing

    arXiv:2610.20124v1 Announce Type: cross Abstract: Human mesh recovery (HMR) provides a geometric foundation for understanding human motion, but accurately reconstructing both body motion and fine hand articulation from v…

  38. arXiv cs.AIresearch
    MultiPartyTurnBench: Benchmarking Floor Control in Multi-Party Spoken Dialogue

    arXiv:2610.20172v1 Announce Type: cross Abstract: Full-duplex speech systems must decide when to enter, hold, or relinquish the conversational floor, even as multiple speakers overlap or backchannel without taking it. Ex…

  39. arXiv cs.AIresearch
    Cross-Model In-Context Neurofeedback Reveals (Limited) Activation Control in LLMs

    arXiv:2610.20179v2 Announce Type: replace-cross Abstract: Probes on activation vectors are widely used to detect misbehavior in language models, but their success relies on the assumption that models cannot control what…

  40. arXiv cs.AIresearch
    Scaling Multilingual Safety and Reasoning Evaluation through Reasoning-Guided Translation

    arXiv:2610.20221v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed across languages, yet their safety and reasoning capabilities remain predominantly evaluated in English. Translatin…

  41. arXiv cs.AIresearch
    Retrieval Over Training: Similarity search-based Model Selection for Time Series Anomaly Detection

    arXiv:2610.20243v2 Announce Type: replace-cross Abstract: Anomaly detection is a fundamental task for time-series analytics, with important implications for the downstream performance of many applications. Despite the la…

  42. arXiv cs.AIresearch
    FUSE: Fairness-aware Update Screening against Byzantine Exploitation in $q$-Fair Federated Learning

    arXiv:2610.20264v1 Announce Type: cross Abstract: Client-level fair federated learning, in the form of $q$-fair federated learning ($q$-FFL), agnostic federated learning, or tilted empirical risk minimization, has emerge…

  43. arXiv cs.AIresearch
    CSWBench: Evaluating Context-Sensitive Code-Switching in Creative Writing

    arXiv:2610.20272v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated multilingual capabilities across diverse language generation and understanding tasks. Yet effective code-switching requires…

  44. arXiv cs.AIresearch
    Beyond Static Cues: Unified Dynamic Detection of MLLM Backdoors via Dual-Flow Trajectory Analysis

    arXiv:2610.20319v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) are increasingly deployed in safety-critical domains, yet their susceptibility to backdoor attacks remains a formidable challenge…

  45. arXiv cs.AIresearch
    Read, Parse, Describe: Unified Document Parsing with Visual Element Description Generation

    arXiv:2610.20335v1 Announce Type: cross Abstract: Document understanding systems are typically evaluated as separate components via layout analysis, optical text recognition, reading-order prediction, and image captionin…

  46. arXiv cs.AIresearch
    Non-asymptotic Convergence of Average-reward Q-learning with Options

    arXiv:2610.20347v1 Announce Type: cross Abstract: We study the finite-sample convergence of Q-learning algorithms for the average-reward formulation of Reinforcement Learning (RL) with options. While options allow tempor…

  47. arXiv cs.AIresearch
    Human Demonstrations as Post-Training Data for Any Robot Body: Retargeting the Object, Not the Hand

    arXiv:2610.20351v1 Announce Type: cross Abstract: Human demonstrations are today used largely for pretraining vision-language-action models, with little ability to use the same data for target-embodiment or task-oriented…

  48. arXiv cs.AIresearch
    Cortex: Consolidating Context into Parametric Memory

    arXiv:2610.20399v1 Announce Type: cross Abstract: Context can improve large language model performance, but these gains may be lost after context removal. Inspired by biological systems consolidation, we formulate Memory…

  49. arXiv cs.AIresearch
    When Does Momentum Help in Reinforcement Learning with Verifiable Rewards?

    arXiv:2610.20413v1 Announce Type: cross Abstract: Momentum is a classical tool for accelerating convex optimization and a standard component of modern large language model training. Yet recent empirical work has question…

  50. arXiv cs.AIresearch
    One Size Does Not Fit All: Curvature-Aware Adaptive Perturbation for SAM

    arXiv:2610.20415v1 Announce Type: cross Abstract: Poor generalisation in deep neural networks is frequently associated with convergence to sharp minima. Sharpness-Aware Minimisation (SAM) improves generalisation of deep…