News / #paper Tag Research papers 500 articles archived under #paper · RSS Sign in to follow arXiv — Machine Learning research 1d ago Graph Dimensionality Reduction for Contextual Bandits: Structure-Specific Regret Bounds under Approximate Smoothness and Noisy Eigenspaces arXiv:2606.27917v1 Announce Type: new Abstract: Contextual bandits with graph-structured arms arise in recommendation, citation retrieval, and social advertising, where arms connected on a graph tend to share reward signal. Standard dimensionality reduction ignores this… 36 arXiv — Machine Learning research 1d ago Two-Stage Fine-Tuning for Protein Sequence Generation with Targeted Amino-Acid Composition arXiv:2606.27939v1 Announce Type: new Abstract: Protein language models are standard priors for biological sequence generation, but steering them toward explicit distributional design targets remains largely unexplored. We study a constrained protein generation problem in which… 24 arXiv — Machine Learning research 1d ago RECAST: Model Reconstruction via Counterfactual-Aware Wasserstein Geometry under Limited Data arXiv:2606.27948v1 Announce Type: new Abstract: Counterfactual explanations (CFs) help understand machine learning models by identifying minimal input changes that would lead to alternative model outcomes. Recent work demonstrates their utility for reconstructing black-box… 15 arXiv — Machine Learning research 1d ago Dual-Learning based Penalized Multi-Align Clustering for Multi-View Incomplete and Disorderly Data arXiv:2606.27984v1 Announce Type: new Abstract: Multimodal feature fusion can effectively capture complex patterns in real-world data by integrating complementary information from different modalities. However, in many applications, such as boiler combustion monitoring,… 18 arXiv — Machine Learning research 1d ago Benchmarking on Tasks That Matter: Dataset Selection for Preserving Model Rankings arXiv:2606.27997v1 Announce Type: new Abstract: Benchmarks of machine learning models often include many datasets, making evaluation expensive. For efficiency, it is preferable to perform evaluations on small, representative datasets instead. The selection of such subsets… 21 arXiv — Machine Learning research 1d ago OperatorSHAP: Fast and Accurate Shapley Value Estimation for Neural Operators arXiv:2606.28065v1 Announce Type: new Abstract: Understanding model predictions is essential for physical applications, where outputs often inform safety-critical decisions, such as structural load assessment, weather warnings, and clinical diagnosis. Shapley values satisfy many… 20 arXiv — Machine Learning research 1d ago Fair Classification with Efficient and Post-hoc Controllable Fairness-Accuracy Trade-off arXiv:2606.28097v1 Announce Type: new Abstract: Post-hoc controllability of fair machine learning models, the ability to control the trade-off between fairness and accuracy after training, is valuable for practical deployment. Existing post-processing methods provide such… 18 arXiv — Machine Learning research 1d ago When One Adapter Speaks for Many: Discovering Low-Rank Redundancy in Continual Fine-Tuning arXiv:2606.28117v1 Announce Type: new Abstract: Low-Rank Adaptation (LoRA) has become the standard tool for parameter-efficient fine-tuning of large pretrained models. When applied sequentially across tasks in Continual Learning (CL), the standard assumption is that each new… 38 arXiv — Machine Learning research 1d ago Dangerous Liaisons of Convex Learning and Non-Affine Aggregation arXiv:2606.28123v1 Announce Type: new Abstract: Last-iterate convergence and generalization guarantees in first-order convex learning hinge on the monotonicity of the update operator. While linear averaging preserves the monotonicity of gradient updates, this property is often… 17 arXiv — Machine Learning research 1d ago Beyond Sparse Supervision: Diffusion-Guided Learning for Few-Shot Graph Fraud Detection arXiv:2606.28134v1 Announce Type: new Abstract: Graph-based fraud detection is essential for safeguarding large-scale transaction systems, where undetected anomalies may lead to substantial financial losses and security risks. Real-world fraud graphs pose two coupled challenges:… 12 arXiv — Machine Learning research 1d ago MixTTA: Low-Rank Cross-Channel Mixing for Reliable Test-Time Adaptation arXiv:2606.28142v1 Announce Type: new Abstract: Test-Time Adaptation (TTA) methods commonly update the affine parameters of normalization layers to adapt deployed models under distribution shifts. However, per-channel affine parameters perform axis-aligned scaling and shifting,… 14 arXiv — Machine Learning research 1d ago Autoencoder Architectures for Athlete Performance Scoring from Wearable Telemetry arXiv:2606.28145v1 Announce Type: new Abstract: Wearable devices produce large, high dimensional training logs for everyday runners, and interpretation rather than data collection is now the limiting step. This paper evaluates five dimensionality reduction models, three… 20 arXiv — Machine Learning research 1d ago Regularized Reward-Punishment Reinforcement Learning arXiv:2606.28152v1 Announce Type: new Abstract: We propose KL-Coupled Policy Regularization (KCPR), a policy coordination framework for Reward-Punishment Reinforcement Learning (RPRL). Based on KCPR, we derive KL-Coupled Soft Optimality (KCSO) and develop its deep realization,… 11 arXiv — Machine Learning research 1d ago Recovering Sharp Conductivity Features in the Finite-Data Calder\'on Problem with Physics-Informed Neural Networks arXiv:2606.28158v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) have recently emerged as a promising framework for addressing the Calder\'on inverse problem from limited boundary data. In this work, we revisit neural Calder\'on inversion by introducing… 31 arXiv — Machine Learning research 1d ago CPAgents: Agentic Composite Phenotype Generation for Cardiac Disease Association arXiv:2606.28179v1 Announce Type: new Abstract: Identifying robust associations between cardiac imaging phenotypes and clinical diseases is fundamental to population-scale cardiovascular research and reliable risk stratification. However, current phenome-wide association studies… 13 arXiv — Machine Learning research 1d ago LLawCo: Learning Laws of Cooperation for Modeling Embodied Multi-Agent Behavior arXiv:2606.28182v1 Announce Type: new Abstract: Embodied agents operating in decentralized and partially observable environments have attracted growing attention in recent years. However, existing large language model (LLM)-based agents often exhibit behaviors that are… 28 arXiv — Machine Learning research 1d ago The Remittance Blueprint: Data-driven Intelligence for Sri Lanka arXiv:2606.28190v1 Announce Type: new Abstract: This study analyzes Sri Lankan migration and remittances over 32 years (1994-2025). Using a 384-month harmonized dataset, we apply exploratory data analysis, stationarity corrected time-series modeling (ADF, Johansen, VAR/VECM),… 29 arXiv — Machine Learning research 1d ago COCOLogic-V2: Identifying Logical Inconsistencies via Truly Hard-Negatives arXiv:2606.28194v1 Announce Type: new Abstract: While interpretable models such as concept bottleneck models (CBMs) and program synthesis methods enable verification of model decisions, their evaluation is typically limited to simple tasks, leaving complex reasoning on… 18 arXiv — Machine Learning research 1d ago Towards Value-Constrained Credit Assignment in Fully Delegated AI Cooperatives arXiv:2606.28217v1 Announce Type: new Abstract: We propose a framework for reward allocation in fully delegated AI cooperatives where humans are represented by agents that contribute data and participate in model updates under heterogeneous value constraints. The key idea is to… 32 arXiv — Machine Learning research 1d ago Physics-Informed Neural Network with Transfer Learning for State Estimation in Lithium-Ion Batteries using the Single Particle Model with Electrolyte arXiv:2606.28220v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) have emerged as a powerful tool for solving nonlinear partial differential equations (PDEs), including battery electrochemical models. They typically en-force conservation laws within the… 15 arXiv — Machine Learning research 1d ago Estimation--Prediction Tradeoff in Causal Probabilistic Temporal Graphs arXiv:2606.28225v1 Announce Type: new Abstract: Temporal link prediction is usually evaluated by predictive performance on unseen edges, but in probabilistic temporal graphs this criterion can conflate model error with irreducible uncertainty. We study this issue by… 32 arXiv — Machine Learning research 1d ago Disentangling Continuous-Time Latent Dynamics: Identifiability of Latent SDEs via Diffusion Shifts arXiv:2606.28228v1 Announce Type: new Abstract: Causal representation learning for time series has developed strong identifiability results in discrete-time latent causal models, but identifiability in continuous-time latent stochastic differential equation (SDE) models remains… 10 arXiv — Machine Learning research 1d ago How Width and Data Shape Generalization Scaling Laws in Quadratic Neural Networks arXiv:2606.28242v1 Announce Type: new Abstract: Understanding how performance scales jointly with model size and data is a central problem in modern machine learning. Existing theoretical works on scaling laws typically describe generalization as a function of data or compute,… 24 arXiv — Machine Learning research 1d ago Parameter Efficient Hybrid Transformer (PEHT) for Network Traffic Prediction via Dynamic Urban Congestion Integration arXiv:2606.28274v1 Announce Type: new Abstract: Accurate network traffic prediction is a critical element for efficient resource allocation in dynamic urban cellular networks. However, prediction remains challenging because network demand is influenced by complex mobility… 21 arXiv — NLP / Computation & Language research 1d ago Towards Automating Scientific Review with Google's Paper Assistant Tool arXiv:2606.28277v1 Announce Type: cross Abstract: Artificial intelligence is driving a revolution in scientific discovery, accelerating everything from hypothesis generation to mathematical theorem proving. However, this rapid acceleration is creating a systemic challenge:… 24 arXiv — Machine Learning research 1d ago Democratic ICAI: Debating Our Way to Steering Principles from Preferences arXiv:2606.28294v1 Announce Type: new Abstract: Preference-based alignment often struggles to capture the reasoning that underlies human judgments. Many evaluations rely on multiple interacting criteria, yet pairwise labels reveal only the final choice rather than the… 38 arXiv — Machine Learning research 1d ago VGB for Masked Diffusion Model: Efficient Test-time Scaling for Reward Satisfaction and Sample Editing arXiv:2606.28301v1 Announce Type: new Abstract: Inference-time scaling is a promising paradigm to improve generative models, especially when outputs must satisfy structural constraints or optimize downstream rewards. We consider Masked Diffusion Model (MDM) and introduce… 37 arXiv — Machine Learning research 1d ago Elastic Time: Dynamic Frame Rate Bottlenecks for Neural Audio Coding arXiv:2606.27320v1 Announce Type: cross Abstract: Neural audio autoencoders have become a core component of compression, feature extraction, and generation. However, while existing systems support variable bitrate, the vast majority of models still operate at a fixed latent… 38 arXiv — NLP / Computation & Language research 1d ago Formalizing Latent Thoughts: Four Axioms of Thought Representation in LLMs arXiv:2606.27378v1 Announce Type: new Abstract: We introduce an axiomatic evaluation framework for latent thought representations in LLMs, comprising metrics that are independent of downstream benchmark scores and reveal representational failures that benchmark accuracy masks.… 29 arXiv — NLP / Computation & Language research 1d ago Position: The Term "Machine Unlearning" Is Overused in LLMs arXiv:2606.27379v1 Announce Type: new Abstract: Large language models increasingly face demands to "forget" training data, knowledge, or behaviors due to regulatory deletion obligations, copyright/licensing disputes, and safety or product-policy requirements. This position paper… 15 arXiv — Machine Learning research 1d ago Forecasting Technological Directions in Wireless Networks and Mobile Computing via AutoML Framework arXiv:2606.27394v1 Announce Type: cross Abstract: The exponential increase in scientific publications has driven the emergence of new trends. Accurate forecasting of these developments is essential for researchers and professionals to stay updated with advancements in the field.… 19 arXiv — Machine Learning research 1d ago Test-Input Generation for Tensor Programs: What Actually Finds Kernel Bugs arXiv:2606.27396v1 Announce Type: cross Abstract: Test-input generation for tensor kernels is folkloric. Most projects pick a representative shape and dtype, run a fixed-shape allclose-style check, and ship. We make the choices explicit and measure them. Using the gpuemu… 18 arXiv — NLP / Computation & Language research 1d ago Recall Before Rerank: Benchmarking Deep Learning Models for Large-Scale Code-to-Code Retrieval arXiv:2606.27401v1 Announce Type: cross Abstract: Semantic code search and clone detection are essential for software development, maintenance, and reuse. This paper evaluates the effectiveness, efficiency, and scalability of contemporary deep learning models for first-stage… 35 arXiv — NLP / Computation & Language research 1d ago Delayed Verification Destabilizes Multi-Agent LLM Belief: Instability Thresholds and Optimal Corrector Placement arXiv:2606.27409v1 Announce Type: cross Abstract: Multi-agent large language model (LLM) systems often rely on verifier and critic agents to suppress hallucinations, but verification is delayed. During this delay, false claims can propagate through the agent network. We model… 25 arXiv — Machine Learning research 1d ago DFM: Difference Feature Modeling with Text-Guided Gated Contrastive Loss for Remote Sensing Image Change Captioning arXiv:2606.27410v1 Announce Type: cross Abstract: The primary goal of Remote Sensing Image Change Captioning (RSICC) is to automatically generate descriptions of changes between remote sensing images captured at different time points. Existing models still rely on a single… 5 arXiv — Machine Learning research 1d ago Directed Graph Topology Inference via Graph Filter Identification arXiv:2606.27455v1 Announce Type: cross Abstract: We address the problem of inferring a directed network from nodal measurements generated by linear diffusion dynamics on the sought graph. Observations are modeled as the outputs of a graph convolutional filter, i.e., a… 5 arXiv — Machine Learning research 1d ago The Decision Geometry of Covariance Estimation for the Global Minimum-Variance Portfolio under Heavy Tails arXiv:2606.27462v1 Announce Type: cross Abstract: The global minimum-variance portfolio (GMVP) is the canonical decision built from an estimated covariance matrix, yet covariance estimators are universally evaluated by matrix-norm loss, which is not the object the decision… 30 arXiv — NLP / Computation & Language research 1d ago Supersede: Diagnosing and Training the Memory-Update Gap in LLM Agents arXiv:2606.27472v1 Announce Type: new Abstract: Large language model (LLM) agents operate over long, multi-session interactions in which facts change: a user moves, a price updates, a plan is revised. Acting correctly requires using the current value of a fact and discarding… 16 arXiv — Machine Learning research 1d ago Support-Constrained RL Enables Real-World Policy Improvement without Real-World Experience arXiv:2606.27475v1 Announce Type: cross Abstract: Robots trained on real world data tend to be imprecise, slow, and brittle to perturbations. Improving these policies with reinforcement learning (RL) is an appealing alternative, but this process often requires expensive training… 28 arXiv — Machine Learning research 1d ago Sampling the Schwinger Model with Gauge-Equivariant Diffusion arXiv:2606.27481v1 Announce Type: cross Abstract: We present a first study of a diffusion-based approach to accelerated sampling of the $N_f = 2$ lattice Schwinger model. Our work is inspired by recent and growing successes in developing such generative models for ensemble… 9 arXiv — Machine Learning research 1d ago Large Language Model Teaches Visual Students: Cross-Modality Transfer of Fine-Grained Conceptual Knowledge arXiv:2606.27527v1 Announce Type: cross Abstract: Large Language Models (LLMs) possess broad conceptual knowledge acquired through large-scale text pretraining, yet their potential to supervise models in other modalities remains underexplored. In this work, we propose… 10 arXiv — Machine Learning research 1d ago Learning from Annotation Uncertainty: Entropy-Aware Curriculum for Speech Emotion Recognition arXiv:2606.27536v1 Announce Type: cross Abstract: Speech emotion recognition (SER) often relies on hard consensus labels that collapse annotator disagreement. We study distribution-based supervision for 9-class SER on MSP-Podcast 2.0 using a WavLM-Base multitask model for… 23 arXiv — Machine Learning research 1d ago Benchmarking Multi-Modal Graph-based Social Media Popularity Prediction arXiv:2606.27539v1 Announce Type: cross Abstract: Social media popularity prediction aims to forecast the future reach or influence of online content from early-stage observations. Accurate prediction enables key downstream applications, such as advertising optimization and… 25 arXiv — Machine Learning research 1d ago Advancing Speaker-Based Vocal Effort Classification with WavLM and Data Augmentation in Naturalistic Non-Calibrated Speech Recordings arXiv:2606.27543v1 Announce Type: cross Abstract: The variations in vocal effort range (e.g. whisper, soft, neutral, loud, shout) alter production and speech acoustics, reducing intelligibility and limiting the robustness of any subsequent speech technology. Classification is… 37 arXiv — NLP / Computation & Language research 1d ago EntMTP: Accelerating LLM Inference with Entropy Guided Multi Token Prediction arXiv:2606.27550v1 Announce Type: new Abstract: Multi-token prediction has been shown to increase data density during training, improve downstream text-generation quality, and serves as the defacto approach for self-speculative decoding. Existing foundation and open source… 29 arXiv — Machine Learning research 1d ago On the Inseparability of Instructions and Data in Shared-Embedding Sequence Models arXiv:2606.27567v1 Announce Type: cross Abstract: Prompt injection is the top security risk for LLM-integrated applications, yet every defense proposed so far has been broken. We prove this is not a coincidence: in shared-embedding architectures that lack enforced control-data… 20 arXiv — Machine Learning research 1d ago Distribution-based deep multiple instance learning for tumor proportion scoring in NSCLC arXiv:2606.27579v1 Announce Type: cross Abstract: Accurate assessment of tumor proportion score (TPS) in non-small cell lung cancer (NSCLC) is critical for treatment planning and prognosis. Key challenges include the tedious manual work required to annotate each slide, combined… 9 arXiv — Machine Learning research 1d ago Odyssey: Constructing Verifiable Local Truth-Preserving Foundation Models arXiv:2606.27593v1 Announce Type: cross Abstract: We introduce a categorical framework called ODYSSEY for constructing verifiable, local truth-preserving foundation models as compositions of foundries: building-block architectural components that specify a cover of local… 27 arXiv — Machine Learning research 1d ago Qwen-Image-2.0-RL Technical Report arXiv:2606.27608v1 Announce Type: cross Abstract: We present Qwen-Image-2.0-RL, a post-training pipeline that applies reinforcement learning from human feedback (RLHF) and on-policy distillation (OPD) to improve both the visual quality and instruction-following capability of the… 34 arXiv — NLP / Computation & Language research 1d ago Masked Language Flow Models arXiv:2606.27617v1 Announce Type: new Abstract: Masked Diffusion Models (MDMs) promise fast, parallel language generation, but their reverse transition factorises across token positions -- an approximation that breaks down in the few-step sampling regime where parallel… 14 Page 6 of 10 · 500 articles ← Newer Older →
