A Quantum/Classical Example Oracle Separation for Making Things Up
arXiv:2608.11648v1 Announce Type: cross Abstract: We study the power of quantum examples, as compared to classical examples, in the PAC learning framework. Here, we have two…
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MOON: Multi-Objective OrthoNormalized Updates for Multitask Learning
arXiv:2608.11749v1 Announce Type: cross Abstract: Multi-objective optimization (MOO) has demonstrated significant success in multi-task learning by mitigating task conflicts through gradient manipulation. However, most existing methods…
Drift and Dependence: Layer-wise Information-Theoretic Bounds for Replay-Based Continual Learning
arXiv:2608.11690v1 Announce Type: cross Abstract: Continual learning must absorb new tasks without erasing old ones, and replay---mixing a small buffer of past examples into current training---is…
Reliable Inference in Edge-Cloud Model Cascades via Conformal Alignment
arXiv:2510.17543v3 Announce Type: replace-cross Abstract: Edge intelligence enables low-latency inference via compact on-device models, but assuring reliability remains challenging. We study edge-cloud cascades that must preserve…
Tight Nonasymptotic Local Convergence of Sinkhorn-Knopp
arXiv:2608.11760v1 Announce Type: cross Abstract: We revisit the Sinkhorn-Knopp (SK) algorithm for the matrix scaling problem. Despite extensive literature on the global convergence of SK and…
Mind the Gap: Structure-Aware Consistency in Preference Learning
arXiv:2604.27733v2 Announce Type: replace-cross Abstract: Aligning Large Language Models (LLMs) with human intent, whether through explicit reward modeling or direct methods such as DPO, fundamentally relies…
A Theoretical Framework for Modular Learning of Robust Generative Models
arXiv:2602.17554v3 Announce Type: replace-cross Abstract: Training large-scale generative models is resource-intensive and relies heavily on heuristic dataset weighting. We address two fundamental questions: Can we train…
Agentic Bayesian Optimization through Surrogate-Augmented Autoresearch
arXiv:2608.00316v2 Announce Type: replace-cross Abstract: Bayesian optimization (BO) has become the standard tool for sample-efficient optimization and owes its efficiency to uncertainty-aware search driven by generic…
Gauge-Fixing the Forward-Forward Objective: A Whitened Goodness Derived from a Likelihood-Ratio Account
arXiv:2607.12501v3 Announce Type: replace-cross Abstract: The Forward-Forward algorithm trains each layer locally, so that a scalar goodness - the sum of squared activations - is high…
CGRL: Causal-Guided Representation Learning for Node-Level Out-of-Distribution Generalization
arXiv:2603.24304v3 Announce Type: replace Abstract: Graph Neural Networks (GNNs) deliver strong performance on graph tasks, but their accuracy drops significantly under out-of-distribution (OOD) scenarios. Under distribution…
Transit Destination Inference from Tap-In-Only Bus Smart-Card Data: A Hierarchical Bayesian Approach
arXiv:2608.11223v1 Announce Type: cross Abstract: Entry-only automatic fare collection systems record boardings but not alightings, preventing direct construction of origin-destination (OD) matrices. This study develops a…
Predictive Allostatic Organization in Recurrent and Spiking Agents Under Partial Observability
arXiv:2608.11506v1 Announce Type: new Abstract: Adaptive behavior under partial observability depends on internal organization that carries information beyond the current observation. Drawing on Barrett and Miller's…
Lapis: Laplacian Spiking Attention via First-Spike Timing and Membrane Leakage
arXiv:2608.11865v1 Announce Type: new Abstract: Self-attention has become central to spiking vision transformers, yet its query-key scoring is still largely inherited from dense networks. Existing spiking…
Adaptive Hybrid Particle Swarm Optimization with Gradient Descent
arXiv:2608.11258v1 Announce Type: cross Abstract: Gradient injection helps Particle Swarm Optimization (PSO) only when the swarm has identified a basin with smooth local structure, not universally.…
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…
Federated Learning for the Design of Parametric Insurance Indices under Heterogeneous Renewable Production Losses
arXiv:2601.12178v2 Announce Type: replace Abstract: We propose a federated learning framework for the calibration of parametric insurance indices under heterogeneous renewable energy production losses. Producers locally…
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…
Deep Activity Model: A Generative Approach for Human Mobility Pattern Synthesis
arXiv:2405.17468v3 Announce Type: replace Abstract: Human mobility plays a crucial role in transportation, urban planning, and public health, but current approaches face important limitations. Existing deep…
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…
Adaptive Bregman Proximal Stochastic Gradient with a Stabilized Barzilai–Borwein Step Size
arXiv:2608.12009v1 Announce Type: cross Abstract: Bregman proximal stochastic gradient (BPSG) methods bring variance-reduced composite optimization to objectives whose geometry is poorly captured by Euclidean smoothness. Their…
Lifecycle-Optimal Tokenization: Vocabulary Size as a Deployment-Regime-Dependent Infrastructure Parameter
arXiv:2608.11361v1 Announce Type: new Abstract: Tokenizer vocabulary size is a foundational design choice in large language model (LLM) infrastructure, yet it is typically fixed at training…
Hybrid-Policy Self-Editing for Composable Unstructured Knowledge Editing
arXiv:2608.11660v1 Announce Type: cross Abstract: Large language models (LLMs) achieve remarkable performance across natural language tasks, yet they are trained on static corpora and their knowledge…
Market-Information-Aware Gated-LoRA of Foundation Models for Transferable Day-Ahead Electricity Price Forecasting
arXiv:2608.11359v1 Announce Type: new Abstract: Electricity price forecasting is crucial for market participants but remains difficult because prices are volatile, market-specific, and closely tied to anticipated…
Forward Trajectory Steering for Hamilton-Jacobi Reachability Analysis
arXiv:2608.11480v1 Announce Type: cross Abstract: Hamilton-Jacobi (HJ) reachability provides a mathematically rigorous framework for safe control of dynamical systems, but its practical application is bottlenecked by…