Trajectory inference via Acceleration Matching
arXiv:2608.03916v1 Announce Type: cross Abstract: Trajectory inference is a fundamental problem in many scientific domains: given a collection of unpaired snapshots of observations at discrete time…
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Online Shift Detection and Conformal Adaptation for Deployed Safety Classifiers
arXiv:2606.11949v3 Announce Type: replace-cross Abstract: Reasoning models deployed as safety monitors exhibit a systematic vulnerability: reasoning-token budget starvation. Adversarial inputs require $3.3times$ more reasoning tokens than…
Variational Approximated Restricted Maximum Likelihood Estimation for Spatial Data
arXiv:2604.07635v2 Announce Type: replace Abstract: This research considers a scalable inference for spatial data modeled through Gaussian intrinsic conditional autoregressive (ICAR) structures. The classical estimation method,…
Bridging Prediction and Attribution: Identifying Forward and Backward Causal Influence Ranges Using Assimilative Causal Inference
arXiv:2510.21889v2 Announce Type: replace Abstract: Causal inference identifies cause-and-effect relationships between variables. While traditional approaches rely on data to reveal causal links, a recently developed method,…
Adversarial observations in probabilistic State-Space Models for robust Reinforcement Learning
arXiv:2606.20880v2 Announce Type: replace Abstract: Decision-making under partial or adversarial observability requires accurate inference of the environment's latent state and its associated uncertainty. This work analyses…
NeuroMosaic: Anatomically Grounded Multimodal Large Language Modeling for Molecularly Aware Glioma Reasoning from 3D MRI and Clinical Narratives
arXiv:2608.03187v1 Announce Type: new Abstract: Multimodal medical large language models remain structurally weak for neuro-oncology because volumetric evidence is compressed into generic visual tokens and diagnostic…
Impacts of Single-objective Landscapes on Multi-objective Optimization
arXiv:2608.03266v1 Announce Type: new Abstract: This work revealed a relationship between a multi-objective optimization problem and single-objective optimization problems that exist in the multi-objective problem. This…
MuEvo: LLM-Driven Evolution of Multi-Heuristic Ensemble
arXiv:2608.03636v1 Announce Type: new Abstract: Large language model-based automated heuristic design (LLM-AHD) has shown strong potential in discovering effective heuristics for combinatorial optimization problems. However, existing…
Omega-S: A Functional Resilience Index for LLM Fine-Tuning
arXiv:2608.03887v1 Announce Type: cross Abstract: Fine-tuning a large language model on new data degrades what it previously learned. We present Omega-S, a drop-in penalty computed from…
AS-FedBridge: Pseudo-Spike Bridge Distillation for Heterogeneous ANN-SNN Federated Learning
arXiv:2608.03324v1 Announce Type: cross Abstract: Federated learning enables collaborative model training across distributed edge devices while strictly preserving data privacy. To facilitate practical deployment on resource-constrained…
Quantization Effects of Artificial Neural Networks for Embedded Edge-Computing Applications
arXiv:2511.05479v4 Announce Type: replace Abstract: This paper examines the use of Quantized Neural Networks (QNNs) for two resource-constrained scientific applications: automated calibration of semi-conductor quantum bits…
The Transformer Revolution, Part 1: Dynamic Processing through Output- Weight Interconnections
arXiv:2608.03921v1 Announce Type: cross Abstract: This paper offers a new interpretation of the Transformer during inference. Against the "stochastic parrot" view that large language models merely…
OR-Agent: Bridging Evolutionary Search and Structured Research for Automated Algorithm Discovery
arXiv:2602.13769v3 Announce Type: replace-cross Abstract: Automating heuristic design in complex, experiment-driven domains requires more than iterative mutation of solution algorithms. Current LLM-based evolutionary methods often rely…
Target-Aligned Fusion for Decision-Sequence Learning under Dynamics Shift
arXiv:2511.09173v3 Announce Type: replace Abstract: External trajectories can improve offline decision-sequence learning, but dynamics shift may make some source subsequences inconsistent with the target environment. We…
Can Training Logs Make Model Comparisons More Precise?
arXiv:2608.02705v1 Announce Type: new Abstract: Comparing stochastically trained models requires estimating both a performance difference and its uncertainty from repeated runs. We study whether training logs…
Patient-centered data science: an integrative framework for evaluating and predicting clinical outcomes in the digital health era
arXiv:2408.02677v2 Announce Type: replace Abstract: This study proposes a novel, integrative framework for patient-centered data science in the digital health era. We developed a multidimensional model…
NANQ: Noise-Floor-Aware Mixed-Precision Non-Uniform Quantization for Analog Compute-in-Memory
arXiv:2608.02700v1 Announce Type: new Abstract: Analog compute-in-memory (CIM) enables energy-efficient neural network inference, but device variation and read noise can severely degrade low-bit quantized models. Existing…
Less Traffic, Better Outcomes: Competition-Aware Request Dispatch in Real-Time Ad Exchanges
arXiv:2608.03705v1 Announce Type: cross Abstract: Real-time bidding (RTB) ad exchanges typically forward nearly all incoming requests to demand-side platforms (DSPs), even though only a small fraction…
Measuring Explainer Stability via Attribution Separability
arXiv:2608.02697v1 Announce Type: new Abstract: Attribution methods (AMs) assign an importance score to each feature and are widely adopted to explain black-box models. However, most methods…
When Correct Solutions Repeat: Rarity-Aware Credit Redistribution for GRPO
arXiv:2608.03467v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) com- monly optimizes each correct completion as an independent learning signal. In GRPO, this completion-level…
PatTree: a novel approach for automated creation of multimodal, graph-based patient representations for medical classification tasks
arXiv:2608.02692v1 Announce Type: new Abstract: Access to holistic, multimodal data improves the performance of Artificial Intelligence (AI) in medical classification tasks compared to utilizing single modalities…
Algorithms with Polynomially-Improved Approximation Factors for the $2 rightarrow q$ Norm, and Applications
arXiv:2605.25303v3 Announce Type: replace-cross Abstract: The $2 rightarrow q$ norm of a matrix $X in mathbb{R}^{n times d}$ is defined as $lVert X rVert_{2 rightarrow q}…
Output-Aware Rotation for INT2 KV-Cache Quantization
arXiv:2608.02691v1 Announce Type: new Abstract: The key-value (KV) cache has become a major memory and bandwidth bottleneck in long-context large language model inference, making ultra-low-bit quantization…
Prescribed-Basis Coefficient-to-Coefficient Neural Operator for Partial Differential Equations
arXiv:2510.10350v3 Announce Type: replace-cross Abstract: Operator learning provides a data-driven approach to approximating solution operators of partial differential equations, but its effectiveness depends strongly on how…