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  1. arXiv cs.AIresearch
    Demystifying the Unreasonable Effectiveness of Greedy Alignment Methods

    arXiv:2604.17207v2 Announce Type: replace-cross Abstract: Greedy AI alignment methods based on Bradley-Terry reward-model fitting and KL-regularized Alignment are remarkably effective in both offline and online preferenc…

  2. arXiv cs.AIresearch
    Learning Evidence Highlighting for Frozen LLMs

    arXiv:2604.22565v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) can reason well, yet often miss decisive evidence when it is buried in long, noisy contexts. We introduce HiLight, an Evidence Emphas…

  3. arXiv cs.AIresearch
    SGP-SAM: Self-Gated Prompting for Transferring 3D Segment Anything Models to Lesion Segmentation

    arXiv:2604.22825v2 Announce Type: replace-cross Abstract: Large segmentation foundation models such as the Segment Anything Model (SAM) have reshaped promptable segmentation in natural images, and recent efforts have ext…

  4. arXiv cs.AIresearch
    DRAGON: A Benchmark for Evidence-Grounded Visual Reasoning over Diagrams

    arXiv:2604.25231v2 Announce Type: replace-cross Abstract: Diagram question answering (DQA) requires models to interpret structured visual representations such as charts, maps, infographics, circuit schematics, and scient…

  5. arXiv cs.AIresearch
    VUDA: Enabling Controlled Spatial Sharing of Graphics and Compute on NVIDIA GPUs

    arXiv:2605.01352v2 Announce Type: replace-cross Abstract: Graphics and compute increasingly share a single GPU in embodied AI simulators, AI-enabled games, and VR systems. Running these workloads concurrently can improve…

  6. arXiv cs.AIresearch
    Query-Dependent Use of Generated Descriptions for Reliable Visual Question Answering

    arXiv:2605.01733v5 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) hallucinate objects that are not present, and a growing line of work tries to curb this by feeding the model its own generated capti…

  7. arXiv cs.AIresearch
    Federated Semi-Supervised Graph Neural Networks with Prototype-Guided Pseudo-Labeling for Privacy-Preserving Gestational Diabetes Mellitus Prediction

    arXiv:2605.01810v2 Announce Type: replace-cross Abstract: Gestational Diabetes Mellitus (GDM) is a high-prevalence pregnancy complication that requires accurate early risk stratification to reduce maternal and fetal morb…

  8. arXiv cs.AIresearch
    RoboAlign-R1: Distilled Multimodal Reward Alignment for Robot Video World Models

    arXiv:2605.03821v2 Announce Type: replace-cross Abstract: Existing robot video world models are typically trained with low-level objectives such as reconstruction and perceptual similarity, which are poorly aligned with…

  9. arXiv cs.AIresearch
    Demystifying Manifold Constraints in LLM Pre-training

    arXiv:2605.04418v2 Announce Type: replace-cross Abstract: The recent success of matrix optimizers (e.g., Muon) suggests that specific normalization of momentum, such as orthogonalization and row-wise normalization, benef…

  10. arXiv cs.AIresearch
    Two-Stage Learned Decomposition for Scalable Routing on Multigraphs

    arXiv:2605.05389v2 Announce Type: replace-cross Abstract: Most neural methods for Vehicle Routing Problems (VRPs) are limited to Euclidean settings or simple graphs. In this work, we instead consider multigraphs, where p…

  11. arXiv cs.AIresearch
    One Turn Too Late: Learning When to Intervene Against Multi-Turn Malicious Intent

    arXiv:2605.05630v3 Announce Type: replace-cross Abstract: Hidden malicious intent in multi-turn dialogue poses a growing threat to deployed large language models (LLMs). Rather than exposing a harmful objective in a sing…

  12. arXiv cs.AIresearch
    SymDrift: One-Shot Generative Modeling under Symmetries

    arXiv:2605.06140v3 Announce Type: replace-cross Abstract: Generative modeling of physical systems, such as molecules, requires learning distributions that are invariant under global symmetries, such as rotations in three…

  13. arXiv cs.AIresearch
    When to Trust Imagination: Adaptive Action Execution for World Action Models

    arXiv:2605.06222v3 Announce Type: replace-cross Abstract: World Action Models (WAMs) jointly predict future visual observations and actions, but typically execute a fixed number of actions before replanning, regardless o…

  14. arXiv cs.AIresearch
    Are We Making Progress in Multimodal Domain Generalization? A Comprehensive Benchmark Study

    arXiv:2605.06643v2 Announce Type: replace-cross Abstract: Despite the growing popularity of Multimodal Domain Generalization (MMDG) for enhancing model robustness, it remains unclear whether reported performance gains re…

  15. arXiv cs.AIresearch
    UniPool: Learning Expert-to-Layer Ownership from Brief Global Access

    arXiv:2605.06665v2 Announce Type: replace-cross Abstract: Most Mixture-of-Experts (MoE) transformers preassign each expert to one layer for the whole of training. We study whether a brief global-access phase can learn a…

  16. arXiv cs.AIresearch
    Enabling Unsupervised Training of Deep EEG Denoisers With Intelligent Partitioning

    arXiv:2605.06724v2 Announce Type: replace-cross Abstract: Denoising electroencephalogram (EEG) is an inherently challenging task, since neural activity is not only subtle but also inseparable from spectrally overlapping…

  17. arXiv cs.AIresearch
    Skip What You Can Predict: Predictive Repositioning for Policy Optimization for Efficient LLM Training

    arXiv:2605.06755v2 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards (RLVR) can improve the reasoning ability of large language models, but repeatedly updating a policy on the same rol…

  18. arXiv cs.AIresearch
    On Privacy in Data-Space Tabular Diffusion Models: Influential Factors, Attacker Knowledge, and Metrics

    arXiv:2605.06835v2 Announce Type: replace-cross Abstract: Tabular data plays an important role in many fields and industries, including those with elevated privacy considerations and risks. As such, there is a rising int…

  19. arXiv cs.AIresearch
    MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text

    arXiv:2605.06903v2 Announce Type: replace-cross Abstract: Large language models are widely used in everyday writing, making reliable AI-generated text detection crucial for academic integrity, content moderation, and pro…

  20. arXiv cs.AIresearch
    In-Context Credit Assignment via the Core

    arXiv:2605.06920v2 Announce Type: replace-cross Abstract: We propose incentive-aligned mechanisms for in-context credit assignment: the task of assigning credit for AI-generated content among creators whose intellectual…

  21. arXiv cs.AIresearch
    BGM-IV: AI-Powered Bayesian Generative Modeling for Instrumental Variable Regression with High-Dimensional Covariates

    arXiv:2605.07029v2 Announce Type: replace-cross Abstract: Instrumental-variable (IV) regression enables causal estimation under endogeneity, but modern IV problems often involve nonlinear structural effects and high-dime…

  22. arXiv cs.AIresearch
    RRCM: Ranking-Driven Retrieval over Collaborative and Meta Memories for LLM Recommendation

    arXiv:2605.07129v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have emerged as a promising paradigm for next-generation recommender systems, offering strong semantic understanding and natural-lang…

  23. arXiv cs.AIresearch
    Encoder-Decoder Transformers: Logical Characterizations and Periodicity

    arXiv:2605.07705v2 Announce Type: replace-cross Abstract: We give logical characterizations of encoder-decoder transformers, the foundational architecture for LLMs that also sees use in various settings that benefit from…

  24. arXiv cs.AIresearch
    Memory-Efficient Looped Transformer: Decoupling Compute from Memory in Looped Language Models

    arXiv:2605.07721v3 Announce Type: replace-cross Abstract: Recurrent LLM architectures have emerged as a promising approach for improving reasoning, as they enable multi-step computation in the embedding space without gen…

  25. arXiv cs.AIresearch
    GazeVLM: Active Vision via Internal Attention Control for Multimodal Reasoning

    arXiv:2605.07817v2 Announce Type: replace-cross Abstract: Human visual reasoning is governed by active vision, a process where meta-cognitive control drives top-down goal-directed attention, dynamically routing foveal fo…

  26. arXiv cs.AIresearch
    One Token Per Frame: Reconsidering Visual Bandwidth in World Models for VLA Policy

    arXiv:2605.07931v4 Announce Type: replace-cross Abstract: Vision-language-action (VLA) models can use visual prediction to anticipate future states, but dense visual features make the generative sequence grow with the nu…

  27. arXiv cs.AIresearch
    LAGO: Language-Guided Adaptive Object-Region Focus for Zero-Shot Visual-Text Alignment

    arXiv:2605.08156v2 Announce Type: replace-cross Abstract: Zero-shot visual recognition often depends on localized parts, attributes, and textures that are diluted in global image representations. Existing training-free l…

  28. arXiv cs.AIresearch
    AIPO: Learning to Reason from Active Interaction

    arXiv:2605.08401v3 Announce Type: replace-cross Abstract: Recent advances in LLMs have demonstrated strong reasoning capabilities, largely stimulated by RLVR. However, the exploration of existing RLVR algorithms remains…

  29. arXiv cs.AIresearch
    Recovering Physical Dynamics from Discrete Observations via Intrinsic Differential Consistency

    arXiv:2605.08454v2 Announce Type: replace-cross Abstract: Recovering continuous-time dynamics from discrete observations is difficult because local supervision loses fidelity as the observation interval grows. We replace…

  30. arXiv cs.AIresearch
    FraudBench: A Multimodal Benchmark for Detecting AI-Generated Fraudulent Refund Evidence

    arXiv:2605.08820v2 Announce Type: replace-cross Abstract: Artificial Intelligence (AI)-generated images have become increasingly realistic and readily adaptable to real-world claims, creating new challenges for verifying…

  31. arXiv cs.AIresearch
    Towards Effective Theory of LLMs: A Representation Learning Approach

    arXiv:2605.09294v2 Announce Type: replace-cross Abstract: We propose Representational Effective Theory (RET), a framework for describing large language model computation in terms of learned macrostates rather than micros…

  32. arXiv cs.AIresearch
    Neural Cluster First, Route Second: Capacitated Vehicle Routing via Differentiable Optimal Transport

    arXiv:2605.09301v2 Announce Type: replace-cross Abstract: The Capacitated Vehicle Routing Problem (CVRP) underpins modern last-mile logistics, where routing decisions recur over the same fixed service area, like a city.…

  33. arXiv cs.AIresearch
    PoDAR: Power-Decoupled Audio Representation for Generative Modeling

    arXiv:2605.10084v2 Announce Type: replace-cross Abstract: The performance of audio latent diffusion models is primarily governed by generator expressivity and the modelability of the underlying latent space. While recent…

  34. arXiv cs.AIresearch
    Investigating Single-Block Recurrence in Vision Transformers for Image Recognition

    arXiv:2605.10661v2 Announce Type: replace-cross Abstract: Vision Transformers (ViTs) implement depth by stacking independently parameterized blocks, but it remains unclear how much of this parameterization is necessary a…

  35. arXiv cs.AIresearch
    When and How to Canonize: A Generalization Perspective

    arXiv:2605.11008v3 Announce Type: replace-cross Abstract: While invariant architectures are standard for processing symmetric data, there is growing interest in achieving invariance by applying group averaging or canoniz…

  36. arXiv cs.AIresearch
    Internalizing Curriculum Judgment for LLM Reinforcement Fine-Tuning

    arXiv:2605.11235v2 Announce Type: replace-cross Abstract: In LLM Reinforcement Fine-Tuning (RFT), curriculum learning drives both efficiency and performance. Yet, current methods externalize curriculum judgment via handc…

  37. arXiv cs.AIresearch
    Deep Minds and Shallow Probes

    arXiv:2605.11448v2 Announce Type: replace-cross Abstract: Neural representations are not unique objects. Even when two systems realize the same downstream computation, their hidden coordinates may differ by reparameteriz…

  38. arXiv cs.AIresearch
    Every Bit, Everywhere, All at Once: A Binomial Multibit LLM Watermark

    arXiv:2605.11653v2 Announce Type: replace-cross Abstract: With LLM watermarking already being deployed commercially, practical applications increasingly require multibit watermarks that encode more complex payloads, such…

  39. arXiv cs.AIresearch
    EHR-RAGp: Prototype-Guided Retrieval of Longitudinal Electronic Health Records for Clinical Prediction Models

    arXiv:2605.12335v2 Announce Type: replace-cross Abstract: Electronic Health Records (EHR) contain rich longitudinal patient information and are widely used in predictive modeling applications. However, effectively levera…

  40. arXiv cs.AIresearch
    CoRe-Gen: Robust Spectrum-to-Structure Generation under Imperfect Fingerprint Conditions

    arXiv:2605.12980v2 Announce Type: replace-cross Abstract: Molecular structure elucidation from tandem mass spectra (MS/MS) remains challenging, particularly for de novo generation beyond database coverage. A common appro…

  41. arXiv cs.AIresearch
    Watermarking Should Be Treated as a Monitoring Primitive

    arXiv:2605.13095v4 Announce Type: replace-cross Abstract: Watermarking is a primary means for providers of generative models to meet legal requirements to mark synthetic content. A watermark embeds a hidden signal into g…

  42. arXiv cs.AIresearch
    Cross Modality Image Translation In Medical Imaging Using Generative Frameworks

    arXiv:2605.13686v2 Announce Type: replace-cross Abstract: Magnetic Resonance Imaging (MRI), Computed Tomography (CT), and Positron Emission Tomography (PET) provide complementary information about tissues. Medical image-…

  43. arXiv cs.AIresearch
    Where Should Diffusion Enter a Language Model? Geometry-Guided Hidden-State Replacement

    arXiv:2605.14368v2 Announce Type: replace-cross Abstract: Continuous diffusion language models require choosing a representation space in which denoising operates, yet it remains unclear which representations are most co…

  44. arXiv cs.AIresearch
    EverAnimate: Minute-Scale Human Animation via Latent Flow Restoration

    arXiv:2605.15042v2 Announce Type: replace-cross Abstract: We propose EverAnimate, an efficient post-training method for long-horizon animated video generation that preserves visual quality and character identity. Long-fo…

  45. arXiv cs.AIresearch
    Goal-Conditioned Supervised Learning for LLM Fine-Tuning

    arXiv:2605.16345v2 Announce Type: replace-cross Abstract: Large language models often require fine-tuning to better align their behavior with user intent at deployment. Existing approaches are commonly divided into onlin…

  46. arXiv cs.AIresearch
    Reducing Hallucination in Multimodal Large Language Models through Hard Grounding Preference Supervision

    arXiv:2605.16411v4 Announce Type: replace-cross Abstract: Hallucination remains a major challenge in vision-language models (VLMs), particularly when linguistically plausible responses are unsupported by visual evidence.…

  47. arXiv cs.AIresearch
    DeepArrhythmia: Segment-Contextualized ECG Arrhythmia Classification via Selective Evidence Acquisition

    arXiv:2605.16441v2 Announce Type: replace-cross Abstract: Beat-level Electrocardiography (ECG) arrhythmia detection aims to assign an arrhythmia class to each beat in a recording, yet many existing systems treat beats as…

  48. arXiv cs.AIresearch
    Fidelity Probes for Specification--Code Alignment

    arXiv:2605.17246v2 Announce Type: replace-cross Abstract: Software modernization often relies on natural-language specifications recovered from an existing implementation. Incorrect or missing requirements can lead to de…

  49. arXiv cs.AIresearch
    DCFold: Efficient Protein Structure Generation with Single Forward Pass

    arXiv:2605.17899v2 Announce Type: replace-cross Abstract: AlphaFold3 introduces a diffusion-based architecture that elevates protein structure prediction to all-atom resolution with improved accuracy. This state-of-the-a…

  50. arXiv cs.AIresearch
    Concise and Logically Consistent Conformal Sets for Neuro-Symbolic Concept-Based Models

    arXiv:2605.18202v3 Announce Type: replace-cross Abstract: Neuro-Symbolic Concept-based Models (NeSy-CBMs) are a family of architectures that integrate neural networks with symbolic reasoning for enhanced reliability in h…