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  1. arXiv cs.AIresearch
    SetGRPO: Calibrating Grader-Induced Policy Optimization

    arXiv:2610.36807v1 Announce Type: cross Abstract: Rubric-based reinforcement learning uses fine-grained grader feedback to train large language models on open-ended tasks, but grader randomness can alter GRPO updates in…

  2. arXiv cs.AIresearch
    TAPESTRY: A Single Backbone for Video Generation and Robot Control

    arXiv:2610.36823v1 Announce Type: cross Abstract: Pretrained video generation models encode rich priors about physical interactions, but leveraging them for robot control typically requires either resource-intensive vide…

  3. arXiv cs.AIresearch
    When All Rollouts Fail: Policy-Compatible Joint Decoding for Hard-Problem Reasoning

    arXiv:2610.36849v1 Announce Type: cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) derives its learning signal from binary rewards via on-policy exploration and becomes a powerful paradigm for improv…

  4. arXiv cs.AIresearch
    ActiveAlign: Aligning Egocentric Manipulation via Active Perception

    arXiv:2610.36859v1 Announce Type: cross Abstract: Real-to-Sim-to-Real (Real2Sim2Real) enables structured world representations for planning, interpretability, and safe execution. Most existing approaches rely on passive…

  5. arXiv cs.AIresearch
    AdaGround: Token-Normalized Adaptive Zooming with Verifier-in-the-Loop Refinement for GUI Grounding

    arXiv:2610.36874v1 Announce Type: cross Abstract: GUI grounding on high-resolution screens fails mostly on small targets, and zooming in is a common training-free remedy. However, most existing zooming pipelines do not m…

  6. arXiv cs.AIresearch
    Developing a Speech Language Model for Basque

    arXiv:2610.36911v1 Announce Type: cross Abstract: Although the recent development of LLMs has paved the way for multi-modal interaction, minority languages face difficulties keeping pace. This work presents the first ope…

  7. arXiv cs.AIresearch
    Self-Keyed In-Parameter Memorization for External Memory-Free Dialogue Recall in Frozen Language Models

    arXiv:2610.36948v1 Announce Type: cross Abstract: A large language model maintains conversational content in an external storage that is outside the model and grows as the dialogue continues. This work assumes an environ…

  8. arXiv cs.AIresearch
    DCKV: Learned Transform Coding of the Prompt KV Cache in Hybrid Language Models

    arXiv:2610.36950v1 Announce Type: cross Abstract: Hybrid language models keep a key-value (KV) cache only in their few full-attention layers, but this cache is still the part of a prompt's state that grows with the promp…

  9. arXiv cs.AIresearch
    Dense Representation Learning and Differentiable Shape Modeling for Spine Landmark Detection

    arXiv:2610.36951v1 Announce Type: cross Abstract: Spine landmark detection from spinal X-ray is a key step for estimating spine deformation severity, for building biomechanical models, and for pre-operative planning. We…

  10. arXiv cs.AIresearch
    PailitaoMMSearch2.0 Technical Report: Scaling Generative Retrieval to Unified End-to-End Multimodal Search

    arXiv:2610.36958v1 Announce Type: cross Abstract: Generative retrieval models have been increasingly adopted in search and recommendation systems. However, industrial generative retrieval models are commonly specialized…

  11. arXiv cs.AIresearch
    Advancement or Acceleration? How Data Curation Improves LLM Training

    arXiv:2610.36983v1 Announce Type: cross Abstract: While data curation is widely credited with improving large language model training, a basic question remains unresolved: does curation expand what a model can ultimately…

  12. arXiv cs.AIresearch
    LearnPrunerV2: Learnable Progressive Token Pruning for Vision-Language Models

    arXiv:2610.36986v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have demonstrated remarkable multimodal capabilities but suffer from prohibitive computational overhead due to the massive number of visual…

  13. arXiv cs.AIresearch
    Evaluating Priority Dispatch for Premium Membership in On-demand Taxi-sharing

    arXiv:2610.37011v1 Announce Type: cross Abstract: In this paper, we analyze the dispatch-level feasibility of introducing premium membership into an on-demand taxi-sharing service using a sequential optimal insertion met…

  14. arXiv cs.AIresearch
    V-LUMEN: Visual Lookup Memory for Embedding Scaling in Vision-Language Models

    arXiv:2610.37019v1 Announce Type: cross Abstract: Embedding-level scaling expands the capacity of language models through lookup-based memory rather than by increasing model depth, width, or dense computation. Extending…

  15. arXiv cs.AIresearch
    Crop Yield Prediction Using Regression Models: A Comparative Evaluation of Model Performance

    arXiv:2610.37022v1 Announce Type: cross Abstract: Reliable crop-yield prediction can support agricultural planning and resource allocation. This study evaluates five regression models for predicting crop yield from envir…

  16. arXiv cs.AIresearch
    Interpretable Deep Learning Models for Breast Cancer Diagnosis Using Medical Imaging

    arXiv:2610.37026v1 Announce Type: cross Abstract: Deep learning shows promise for breast cancer diagnosis, but limited interpretability hinders clinical adoption. We benchmark ten ImageNet-pretrained models (ResNet50, VG…

  17. arXiv cs.AIresearch
    Zooming without Zooming v2: From Seeing Details to Connecting Evidence for Generalizable Multimodal Perception

    arXiv:2610.37037v1 Announce Type: cross Abstract: Multimodal perception forms the foundation of multimodal intelligence. In particular, spatial perception and multimodal long-context understanding are two pivotal tasks t…

  18. arXiv cs.AIresearch
    Exploring the Limits of the Delta Learning Hypothesis: Single-Pair Generator Biases in Direct Preference Optimization

    arXiv:2610.37058v1 Announce Type: cross Abstract: Direct Preference Optimization (DPO) typically relies on preference pairs generated from diverse model pools and ranked by an external LLM judge. The recently proposed de…

  19. arXiv cs.AIresearch
    EnergyCal: Taming Loss Spikes in Muon-Family Optimizers for Sparse MoE Training

    arXiv:2610.37062v1 Announce Type: cross Abstract: Sparse mixture-of-experts (MoE) language-model training can exhibit large loss spikes with Muon-family optimizers. We introduce EnergyCal, a lightweight rule that attenua…

  20. arXiv cs.AIresearch
    Learning to Look Beyond Screens: Transferable Visual Observation from GUI Grounding

    arXiv:2610.37093v1 Announce Type: cross Abstract: Visual perception is evolving from passive recognition toward active, task-oriented observation. We investigate GUI grounding as a scalable source of spatial supervision…

  21. arXiv cs.AIresearch
    Hardware-Matched Spiking Neural Networks for Real-Time Purkinje Cell Spike Classification

    arXiv:2610.37104v1 Announce Type: cross Abstract: Distinguishing Purkinje cell (PC) simple spikes (SSs) from complex spikes (CSs) is key to studying cerebellar function. PC recordings commonly rely on wired headstages, w…

  22. arXiv cs.AIresearch
    A First-Step Bias Restores Lost Diversity in Diffusion Model Distillation

    arXiv:2610.37110v1 Announce Type: cross Abstract: Distribution-matching distillation enables high-quality image generation in only a few denoising steps. However, distilled student models often map different initial nois…

  23. arXiv cs.AIresearch
    MRI-to-CT Translation of Spinal Images via Anatomy-Guided Pseudo-Pairing and Adversarial Diffusion

    arXiv:2610.37134v1 Announce Type: cross Abstract: Magnetic Resonance Imaging (MRI) is routinely used to diagnose spinal disorders, but surgical planning often requires Computed Tomography (CT) for better visualization of…

  24. arXiv cs.AIresearch
    What the Primary Lund Plane Omits: A Model-Stitching Diagnosis of a Jet-Tagger Representation Gap

    arXiv:2610.37137v1 Announce Type: cross Abstract: Lund-plane and Particle Transformer (ParT) jet taggers can differ in performance because one representation is weaker, or because a weaker downstream computation reads an…

  25. arXiv cs.AIresearch
    Generative Replay for Equilibrium Propagation: Toward Edge-Friendly Continual Learning in Hopfield Networks

    arXiv:2610.37139v1 Announce Type: cross Abstract: Equilibrium Propagation (EqProp) offers a biologically grounded and hardware-aligned alternative to backpropagation for training Hopfield Networks. However, its behavior…

  26. arXiv cs.AIresearch
    Beyond Parameter Protection: Fisher-Shaped EWC for Replay-Free Continual Learning

    arXiv:2610.37145v1 Announce Type: cross Abstract: In replay-free continual learning, Elastic Weight Consolidation (EWC) uses Fisher information matrix (FIM) to protect acquired knowledge by penalizing changes to historic…

  27. arXiv cs.AIresearch
    GCSR-OCC: Geometry Calibration and Semantic Routing for Open-Vocabulary Occupancy Prediction

    arXiv:2610.37149v1 Announce Type: cross Abstract: Open-vocabulary 3D occupancy prediction represents scene geometry and semantics in a unified voxel grid, enabling recognition beyond predefined categories. One approach r…

  28. arXiv cs.AIresearch
    Retrieve to Act: Motion Primitive Graph Retrieval for Robust VLA Execution

    arXiv:2610.37215v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) policies demonstrate remarkable semantic generalization, yet remain highly vulnerable to out-of-distribution (OOD) visual shifts during execu…

  29. arXiv cs.AIresearch
    When Is a Relation Worth Trusting? Manipulation Costs, Exposure, and the Trust Trap in Multi-Relational Graph Learning

    arXiv:2610.37239v2 Announce Type: replace-cross Abstract: Multi-relational graph detectors learn from clean data how much to trust each relation, but an adversary pays a different price to manipulate each relation and ea…

  30. arXiv cs.AIresearch
    Aligning Large Language Models for Safety in African Languages: A Case Study of Hausa

    arXiv:2610.37245v1 Announce Type: cross Abstract: Safety alignment research for large language models (LLMs) remains concentrated on high-resource languages, leaving open how existing alignment methods perform in low-res…

  31. arXiv cs.AIresearch
    A Lightweight Attention-Based CNN with Saliency-Map Interpretability for Skin Cancer Detection

    arXiv:2610.37314v1 Announce Type: cross Abstract: Skin cancer is among the most prevalent and life threatening forms of cancer worldwide. Early and accurate diagnosis significantly improves patient survival rates. Howeve…

  32. arXiv cs.AIresearch
    WCC: A Learning-Based Framework for Deciding When to Apply Cooperative Coevolution in Large-Scale Optimization

    arXiv:2610.37329v1 Announce Type: cross Abstract: Cooperative Coevolution (CC) and Non-Decomposition Algorithms (NDAs) are two primary approaches for large-scale global optimization (LSGO). Although both have achieved su…

  33. arXiv cs.AIresearch
    CoS-VQ: Coordinated Shared-Scale Vector Quantization for Large Language Models

    arXiv:2610.37336v1 Announce Type: cross Abstract: Large language models (LLMs) require substantial memory, motivating low-bit weight quantization for efficient deployment. Existing vector quantization (VQ) methods often…

  34. arXiv cs.AIresearch
    Channel Selection for Mixture-of-Experts Decoding Needs No Calibration Data

    arXiv:2610.37386v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models are bottlenecked by loading routed-expert weights from memory during interactive decoding at small batch sizes. Because most intermediate…

  35. arXiv cs.AIresearch
    JEPA-Inspired Latent Field Prediction for Sparse-Pilot MIMO-OFDM Channel Reconstruction

    arXiv:2610.37391v1 Announce Type: cross Abstract: Accurate acquisition of full channel state information (CSI) is essential for multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) wirele…

  36. arXiv cs.AIresearch
    Learning Quality-Controllable Robot Policies with Iterative Hindsight Relabeling

    arXiv:2610.37393v1 Announce Type: cross Abstract: Robot policy evaluation often relies on a binary success signal for task completion. In real-world deployment, however, desired execution behaviors are also defined by qu…

  37. arXiv cs.AIresearch
    Bayes-Adaptive MDPs for Rollout Allocation to Enhance GRPO Training

    arXiv:2610.37429v1 Announce Type: cross Abstract: Group Relative Policy Optimization (GRPO) has demonstrated strong performance in LLM post-training. However, it allocates a uniform rollout budget to every training quest…

  38. arXiv cs.AIresearch
    Representing the Unseen: Rethinking Visual Imagination for Spatial Reasoning

    arXiv:2610.37437v1 Announce Type: cross Abstract: Visual world models increasingly support spatial reasoning by generating RGB views of unobserved states. However, RGB has become the default interface largely because it…

  39. arXiv cs.AIresearch
    PerceptRL: Making Visual Perception Rewardable in MLLMs from Answers to Interactions

    arXiv:2610.37471v1 Announce Type: cross Abstract: Fine-grained visual perception remains a bottleneck during post-training of multimodal large language models (MLLMs), as perceptual errors can constrain gains from reason…

  40. arXiv cs.AIresearch
    How Reliable Is Individualized Functional-Network Attribution in Resting-State fMRI Cognitive Prediction in ADNI?

    arXiv:2610.37472v1 Announce Type: cross Abstract: Individualized attribution estimates which functional networks drive a model prediction for a given subject and is often proposed as an interpretable resting-state fMRI (…

  41. arXiv cs.AIresearch
    HGPRGDel: GPR-Aware Learning and Ranking for Growth-Coupled Gene Deletion Design

    arXiv:2610.37478v1 Announce Type: cross Abstract: Designing microbial strains for growth-coupled production, in which cellular growth is linked to the synthesis of a target compound through genetic interventions, is a fu…

  42. arXiv cs.AIresearch
    Follow the Gradient: Tracing Safety Degradation Back to Training Data

    arXiv:2610.37481v1 Announce Type: cross Abstract: Fine-tuning Large Language Models (LLMs) on instruction data can quietly erode their safety, even when no training example looks harmful. Because this safety-degrading da…

  43. arXiv cs.AIresearch
    Orthogonal and Parametrized Multi-Attribute Steering of LLMs

    arXiv:2610.37517v2 Announce Type: replace-cross Abstract: Activation steering offers an effective and efficient way to modify an LLM's behavior at inference time. However, it remains unclear how to apply steering such th…

  44. arXiv cs.AIresearch
    The Structure Gap: When More Data Cannot Replace Structured Reasoning

    arXiv:2610.37523v1 Announce Type: cross Abstract: A persistent belief in modern AI is that sufficiently large learners trained on sufficiently much data can make explicit domain knowledge optional. This paper examines a…

  45. arXiv cs.AIresearch
    Which Hand Was Late? Diagnosis for Robot Failure Recovery in Bimanual Tool Use

    arXiv:2610.37533v1 Announce Type: cross Abstract: Failure diagnosers for robot manipulation are increasingly vision--language models (VLMs), trained and evaluated on single-arm failures produced by perturbing a successfu…

  46. arXiv cs.AIresearch
    GroundControl: Satellite-Conditioned Multi-View Diffusion for Reconstruction-Free Novel View Synthesis

    arXiv:2610.37545v1 Announce Type: cross Abstract: Multi-view or video diffusion models have recently emerged as state-of-the-art approaches for novel-view synthesis from sparse image collections. While they can produce h…

  47. arXiv cs.AIresearch
    When, Where, and What to Correct: Human-Guided Adaptive Residual Correction for Robot Policies

    arXiv:2610.37547v1 Announce Type: cross Abstract: Imitation policies that reliably execute most of a manipulation trajectory can still fail in localized regions requiring last-mile precision. Updating the full policy or…

  48. arXiv cs.AIresearch
    Kinematic Constraint-Referenced Evaluation for Articulated Object Manipulation

    arXiv:2610.37550v1 Announce Type: cross Abstract: Manipulation policies are evaluated predominantly by binary task success, which cannot tell whether the commanded gesture is the one the object's kinematics admit. We int…

  49. arXiv cs.AIresearch
    When uncertainty quantification fails: structural vulnerabilities and corrections for selective prediction under clinical class imbalance

    arXiv:2610.37561v1 Announce Type: cross Abstract: Background. Selective prediction systems improve the safety of clinical artificial intelligence by deferring ambiguous cases to human experts while automating high-confid…

  50. arXiv cs.AIresearch
    REGER: Modeling inter-item Relations with Semantic IDs for Generative Recommendation

    arXiv:2610.37584v2 Announce Type: replace-cross Abstract: Personalized recommendation depends on learning semantic and collaborative relations among items from online content and user interactions. Generative recommendat…