News / #paper Tag Research papers 500 articles archived under #paper · RSS Sign in to follow arXiv — Machine Learning research 1d ago PAIR: Pairwise-Aware Inclusion Reweighting for Adaptive Rollout Allocation in RLVR arXiv:2608.11368v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) spends most of its compute generating groups of long reasoning trajectories. Recent allocators reduce this cost by assigning budgets to prompts, rollouts, or tokens according to… 26 arXiv — Machine Learning research 1d ago Towards an approach to multivariate outlier detection for District Heating System data arXiv:2608.11375v1 Announce Type: new Abstract: In this paper, we test different methods for multivariate detection of outliers in the data of transmitted heat energy in the selected substation of local District Heating System, by also considering outside ambient temperature,… 37 arXiv — Machine Learning research 1d ago Reoptimization Algorithms for Contextual Bandits with Knapsack Constraints arXiv:2608.11383v1 Announce Type: new Abstract: We study new algorithms for Contextual Bandits with Knapsack. In these problems, there are finitely many types of customers, products, and resources. Each product is made from a fixed combination of resources, and resources have… 7 arXiv — Machine Learning research 1d ago Mechanism Design for Generative Engines: From Exploitation toward Win-Win Outcomes arXiv:2608.11390v1 Announce Type: new Abstract: Generative engines are reshaping the web ecosystem by making citations a key mechanism for allocating attention, attribution, and downstream value. This creates a strategic tension: content providers are incentivized to optimize… 10 arXiv — Machine Learning research 1d ago Unmasking Toxic Mimicry in Medical Offline Reinforcement Learning for ICU Sepsis Management via Counterfactual Clinical Audits arXiv:2608.11410v1 Announce Type: new Abstract: Offline reinforcement learning (RL) offers considerable promise for optimizing ICU treatment decisions, yet standard evaluation metrics Mean Squared Error (MSE) and Fitted Q-Evaluation (FQE) assess only behavioral imitation and… 37 arXiv — Machine Learning research 1d ago Diffusion-Based Data-Driven Assortment Optimization arXiv:2608.11419v1 Announce Type: new Abstract: Assortment optimization is a fundamental problem in revenue management, typically addressed using parametric choice models such as the multinomial logit (MNL) and its variants. While these models enable tractable formulations,… 36 arXiv — Machine Learning research 1d ago Analysis of Federated Aggregation under Model Poisoning and Backdoor Attacks: A Reconstructed Cross-Dataset and Cross-Architecture Benchmark arXiv:2608.11423v1 Announce Type: new Abstract: Robust comparisons of federated aggregation methods require joint consideration of predictive performance, threat definitions, metric semantics, and execution provenance. A 500-cell seed-1 evaluation matrix was reconstructed across… 5 arXiv — Machine Learning research 1d ago Click2Poly: A VLM for vector mapping buildings and walls arXiv:2608.11424v1 Announce Type: new Abstract: Accurate vector mapping of buildings and walls is critical for geospatial applications but remains a labor-intensive process. While recent deep learning methods have improved automatic extraction, in order to meet cartographic… 36 arXiv — Machine Learning research 1d ago Three Tokens Force Exponential Feature Rank in Nonnegative Kernel Attention arXiv:2608.11427v1 Announce Type: new Abstract: Full attention exposes every token pair, whereas kernel attention compresses a sequence into a fixed-dimensional sketch. We show that this distinction becomes exponential at the first context length containing two competing… 29 arXiv — Machine Learning research 1d ago AutoGrable: What Is a Good Graph for a Table? arXiv:2608.11431v1 Announce Type: new Abstract: Graph learning presupposes a graph, and tables and relational databases do not come with one. Applying a GNN to them requires deciding which entities become nodes, which of them to connect, and through which relations---a decision… 18 arXiv — Machine Learning research 1d ago Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates arXiv:2608.11435v1 Announce Type: new Abstract: Forward and inverse modeling of parametric dynamical systems requires surrogate models that are not only accurate for state prediction, but also informative for parameter calibration. However, a systematic end-to-end differentiable… 17 arXiv — Machine Learning research 1d ago XGBoost "is all you need": the case of forecasting transmitted heat energy in District Heating Systems arXiv:2608.11446v1 Announce Type: new Abstract: This paper presents a comparative study of two distinct approaches, XGBoost and Long-Short Term Memory (LSTM), for forecasting transmitted heat energy in District Heating Systems (DHS). The objective is to explore scenarios in… 23 arXiv — Machine Learning research 1d ago PAC-Bayes Beyond Parameter Space: Behavioral Equivalence, Z-Information, and Exact Complexity Decomposition arXiv:2608.11465v1 Announce Type: new Abstract: PAC-Bayes theory provides generalization guarantees by controlling the Kullback--Leibler (KL) divergence between posterior and prior distributions over a chosen hypothesis representation. However, predictive risk depends only on… 17 arXiv — Machine Learning research 1d ago Dual-Primal Graph VAEs for Noisy Label Aggregation arXiv:2608.11473v1 Announce Type: new Abstract: Inferring the ground-truth from noisy crowdsourced labels is an important theoretical and practical problem. Neural network-based methods offer an alternative to classical Bayesian models which require specifying a family of… 36 arXiv — Machine Learning research 1d ago Convergence Guarantees of Gradient Descent for Neural Networks via Generalized Lipschitz Smoothness arXiv:2608.11479v1 Announce Type: new Abstract: We establish convergence guarantees of gradient descent for general feedforward neural networks of arbitrary width or depth, with no special requirements on the initialization or dataset. We only assume that the activation… 14 arXiv — Machine Learning research 1d ago Defending against Model Extraction for GNNs with Model Reprogramming arXiv:2608.11495v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) serve as the backbone for high-stakes applications in Machine-Learning-as-a-Service (MLaaS). Still, their black-box deployment exposes them to Model Extraction (ME) attacks, in which adversaries steal… 24 arXiv — Machine Learning research 1d ago HyperFix: Combinatorial Nonlinear Correction for Task Vector Merging arXiv:2608.11499v1 Announce Type: new Abstract: Task vectors enable model merging without joint retraining. In practice, the subset of task vectors to be merged may vary, but many existing methods use scalar tuning for a particular subset, requiring repeated tuning across… 32 arXiv — Machine Learning research 1d ago RelShap: Relationally Consistent Shapley Explanations arXiv:2608.11508v1 Announce Type: new Abstract: Machine learning pipelines commonly flatten relational data into single-table representations, discarding structural constraints. Widely used Shapley value-based feature attributions then rely on feature independence, evaluating… 30 arXiv — Machine Learning research 1d ago Let it Cook: Learning to Wait in Sequential Decision Making arXiv:2608.11511v1 Announce Type: new Abstract: In sequential decision making, an agent typically observes its environment and acts at every timestep. However, such active participation may not always be necessary; tasks such as brewing coffee include periods that are served… 20 arXiv — Machine Learning research 1d ago FLARE++: Low-rank attention with dynamic attention routing arXiv:2608.11519v1 Announce Type: new Abstract: Full self-attention is a strong token mixer for PDE surrogates on irregular domains, but its quadratic cost limits its use on high-resolution problems. Efficient latent-attention models such as the Fast Low-rank Attention Routing… 32 arXiv — Machine Learning research 1d ago Hierarchical Federated Transfer Learning in Digital Twin-Based Vehicular Networks arXiv:2608.11532v1 Announce Type: new Abstract: In recent research on the Digital Twin-based Vehicular Ad hoc Network(DT-VANET), Federated Learning (FL) has shown its ability to provide data privacy. However, Federated learning struggles to adequately train a global model when… 30 arXiv — Machine Learning research 1d ago Robust Ambiguity Detection (RAD) From Model- and Feature-Space Consistency arXiv:2608.11541v1 Announce Type: new Abstract: Machine learning models should be robust, in the sense of remaining predictively consistent under permissible variations. A model's predictions should ideally remain unchanged when it is replaced by a functionally equivalent one,… 6 arXiv — Machine Learning research 1d ago Certifying What Helps Customer-Return Timing: A Screen-and-Confirm Test for Conditioning Signals, and Why Decay Is Nearly Enough arXiv:2608.11555v1 Announce Type: new Abstract: Practitioners enrich customer-return models with ever more signals (lifetime value, category, recency/frequency, calendar, geography), and the temporal-point-process (TPP) literature follows suit with covariate- and… 7 arXiv — Machine Learning research 1d ago When Offline Evaluation Misleads: A Diagnostic Protocol for Reward and Policy Selection in Delayed-Feedback Contextual Bandits arXiv:2608.11560v1 Announce Type: new Abstract: Personalizing marketing messages with contextual multi-armed bandits (CMABs) drives real business value, yet the objective that ultimately matters - a downstream conversion - is observed only weeks later, too late to drive online… 4 arXiv — Machine Learning research 1d ago Sparse and robust geometric twin support vector machine via asymmetric RoBoSS loss function arXiv:2608.11567v1 Announce Type: new Abstract: In real-world scenarios, the training data usually contains redundant features, label noise and feature noise, which provide severe challenges for the efficiency of machine learning methods. Since standard support vector machine… 31 arXiv — Machine Learning research 1d ago RECAST: A Machine-Learning Framework for Correction and Super-Resolution of Coarse-Grid PDE Solvers arXiv:2608.11572v1 Announce Type: new Abstract: Coarse-grid numerical solvers can substantially reduce the computational cost of time-dependent PDE simulation, but under-resolution often degrades both the trajectory and the spatial fidelity of the solution. We introduce RECAST… 7 arXiv — Machine Learning research 1d ago Dion3: Full-Stack Orthogonal Updates arXiv:2608.11612v1 Announce Type: new Abstract: The Muon optimizer incurs a significant overhead cost due to its cubic-time Newton-Schulz orthogonalization step. When weights are sharded, communication overhead compounds this computational cost, eroding the benefits of Muon in… 23 arXiv — Machine Learning research 1d ago A Local Sinkhorn Framework for Conditional Distribution Reconstruction of Multidimensional Random Fields arXiv:2608.11613v1 Announce Type: new Abstract: In this paper, we propose a local Sinkhorn divergence framework for conditional distribution reconstruction of multidimensional random fields. By utilizing the debiased Sinkhorn divergence, our proposed approach develops a… 32 arXiv — Machine Learning research 1d ago FM-LLM: A frequency-enhanced mixture-of-experts framework for adapting LLMs to time series forecasting arXiv:2608.11623v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) have spurred cross-modal solutions for time-series forecasting. However, existing methods rely heavily on textual prompts for modality alignment-introducing nontrivial computational… 23 arXiv — Machine Learning research 1d ago Transferable Above-Ground Biomass (AGB) Estimation Model from Multi-Sensor Data with Sparse Field Calibration arXiv:2608.11638v1 Announce Type: new Abstract: Spatially continuous quantification of forest above-ground biomass (AGB) is what makes carbon accounting credible and mitigation strategies actionable. While field inventories provide high localized accuracy, they are spatially… 17 arXiv — Machine Learning research 1d ago Towards a Formal Definition of Agent Memory: Basis, Span, Optimality, and the Sequential Memory Problem arXiv:2608.11654v1 Announce Type: new Abstract: Despite the wide deployment of memory in large-model agents, there is no unified formal account of what a memory is or when it is optimal. This paper takes a first step toward this account. The central idea is that memory is a… 10 arXiv — Machine Learning research 1d ago Continuous-Latent Predictive Modeling with Semantic Alignment for EEG-Language Foundation Models arXiv:2608.11656v1 Announce Type: new Abstract: Recent advances in EEG foundation models have demonstrated the potential of large-scale pretraining to enable generalizable neural decoding across subjects, recording environments, and datasets. However, dominant pretraining… 18 arXiv — Machine Learning research 1d ago Is Per-Agent Policy Composition Safe? Rethinking Successor-Feature Transfer in Cooperative Multi-Agent Reinforcement Learning arXiv:2608.11658v1 Announce Type: new Abstract: Many reinforcement learning systems, from fleet management to traffic signal control, must serve an objective that changes dynamically after deployment, and retraining a policy for each new objective is prohibitively expensive. For… 14 arXiv — Machine Learning research 1d ago Low-Interaction-Rank Learning: Unifying Multiplicative Dual-Encoder Heads arXiv:2608.11661v1 Announce Type: new Abstract: A multiplicative dual-encoder network computes a real-valued output for a pair of inputs as the inner product of their separate encodings. This architecture has been developed independently in operator learning, bipartite matching,… 26 arXiv — NLP / Computation & Language research 1d ago Rubric Dropout: A Simple Way to Mitigate Reward Hacking in Rubric-as-Reward RL arXiv:2608.11669v1 Announce Type: cross Abstract: Reinforcement learning against rubrics, lists of criteria graded by an LLM judge, has become a standard way to post-train language models on tasks with no deterministic answer. The rubric, however, is a fixed proxy for quality,… 37 arXiv — Machine Learning research 1d ago GCPO: Diagnosing and Constraining Subspace Geometry in Rollout RL for LLMs arXiv:2608.11674v1 Announce Type: new Abstract: On-policy rollout methods such as GRPO are central to post-training of large language models, yet they frequently suffer from training instabilities, cross-task capability degradation, and response-length inflation. Although prior… 34 arXiv — Machine Learning research 1d ago FunnelCausalNet: Funnel-aware Joint Conversion-Revenue Uplift for Multi-tier Coupon Allocation arXiv:2608.11675v1 Announce Type: new Abstract: Coupon campaigns seek to lift both conversion and revenue, but gross merchandise value (GMV) follows a deterministic funnel from conversion to conditional order value and is zero-inflated and heavy-tailed. We propose… 29 arXiv — Machine Learning research 1d ago Drift and Dependence: Layer-wise Information-Theoretic Bounds for Replay-Based Continual Learning arXiv:2608.11690v1 Announce Type: new Abstract: Continual learning must absorb new tasks without erasing old ones, and replay---mixing a small buffer of past examples into current training---is among the most effective remedies for catastrophic forgetting. Yet its generalization… 15 arXiv — NLP / Computation & Language research 1d ago LEMUR: Latent Entropy-aware Multimodal Unlearning via Visual-anchored Reasoning Redirection arXiv:2608.11691v1 Announce Type: cross Abstract: Reinforcement-learning (RL) post-training equips multimodal large reasoning models (MLRMs) with exploratory chains of thought (CoT), substantially improving visual reasoning. However, we find that this capability introduces a… 18 arXiv — Machine Learning research 1d ago REOPD: Reliability-Adaptive Reward Extrapolation for On-Policy Distillation arXiv:2608.11698v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student on its own trajectories under dense token-level supervision from a teacher. Reward-extrapolation methods such as ExOPD amplify the teacher-reference log-likelihood ratio to move beyond… 8 arXiv — Machine Learning research 1d ago Consolidator: Learning Persistent Routed Memory Across Context Boundaries arXiv:2608.11701v1 Announce Type: new Abstract: Copying short-term memory (STM) into a slower store can preserve state across a context boundary, but persistence alone does not ensure that the retained state influences subsequent memory access. We test this distinction in a… 4 arXiv — Machine Learning research 1d ago Robust and Efficient Noisy-Label Time-Series Classification via Dynamic Time Warping Based Granular Ball Computing arXiv:2608.11704v1 Announce Type: new Abstract: Dynamic Time Warping (DTW)-based Nearest-Neighbor (NN) classifiers are effective for time-series classification but are vulnerable to mislabeled training samples and require numerous DTW computations during inference. We propose… 6 arXiv — Machine Learning research 1d ago High-dimensional Multi-objective Bayesian Optimization with Learned Variable Interactions arXiv:2608.11713v1 Announce Type: new Abstract: Multi-objective Bayesian optimization (MOBO) is effective in identifying the Pareto fronts for expensive black-box problems. However, most current MOBO approaches are limited to low-dimensional decision space due to its exponential… 35 arXiv — Machine Learning research 1d ago Chain-of-Thought Shows the Path to a Tree: Realizing Branching Complexity arXiv:2608.11716v1 Announce Type: new Abstract: Chain of Thought (CoT) lifts the expressive ceiling of bounded-depth Transformers, with characterizations tying the number of CoT steps to circuit complexity classes. What remains largely missing are concrete instantiations with… 6 arXiv — NLP / Computation & Language research 1d ago Epiplexity Guided Data Selection and Generation for Out-of-Distribution Generalization arXiv:2608.11746v1 Announce Type: cross Abstract: Modern systems are increasingly expected to transfer across tasks not specified during training. What data facilitates generalization in these new, unanticipated settings? One hypothesis is that data with more structural… 35 arXiv — Machine Learning research 1d ago MOON: Multi-Objective OrthoNormalized Updates for Multitask Learning arXiv:2608.11749v1 Announce Type: new Abstract: Multi-objective optimization (MOO) has demonstrated significant success in multi-task learning by mitigating task conflicts through gradient manipulation. However, most existing methods flatten model parameters into vectors and… 8 arXiv — Machine Learning research 1d ago TradingMoE: Routing the Right Experts in Evolving Markets arXiv:2608.11785v1 Announce Type: new Abstract: Large language models (LLMs) have shown strong potential for financial analysis and trading, but direct trading remains challenging because the predictive capabilities required can vary across assets, decision fields, and market… 36 arXiv — Machine Learning research 1d ago High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving arXiv:2608.11790v1 Announce Type: new Abstract: Accurate Global Navigation Satellite System (GNSS)-based localization is essential for safe and reliable autonomous driving. However, spoofing attacks can manipulate vehicle position estimates. Continuous and subtle attacks are… 5 arXiv — Machine Learning research 1d ago Orientation, not magnitude: the causal structure of task-vector interference in merged language models arXiv:2608.11797v1 Announce Type: new Abstract: Model merging by task arithmetic works until it doesn't, and the field diagnoses why with magnitudes: layerwise representation bias, deviations from cross-task linearity, parameter overlap. Tracking the exact layerwise cross-term… 9 arXiv — Machine Learning research 1d ago JAPE: Joint Anomaly Prediction and Intrinsic Explanation in Multivariate Time Series arXiv:2608.11801v1 Announce Type: new Abstract: Multivariate time-series anomaly prediction aims to identify whether and when anomalies will occur over a future horizon from historical observations. Existing methods primarily characterize anomalies as deviations in future… 18 Page 5 of 10 · 500 articles ← Newer Older →
