2/13/2026
TabSieve: Explicit In-Table Evidence Selection for Tabular Prediction
Framework for tabular prediction using explicit in-table evidence selection, making row context auditable and interpretable.
2/13/2026
Potential-energy gating for robust state estimation in bistable stochastic systems
Physics-based state estimation method using potential-energy gating for robust filtering in bistable stochastic systems.
2/13/2026
DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels
Diffusion LLM approach for CUDA kernel code generation leveraging parallel token generation and non-sequential refinement.
2/13/2026
Dopamine: Brain Modes, Not Brains
Parameter-efficient fine-tuning method viewing adaptation as neuromodulation-inspired mode selection and rescaling of pretrained computations.
2/13/2026
U-Former ODE: Fast Probabilistic Forecasting of Irregular Time Series
U-Former ODE architecture for fast probabilistic forecasting of irregularly sampled time series using neural differential equations.
2/13/2026
TUBO: A Tailored ML Framework for Reliable Network Traffic Forecasting
ML framework for reliable network traffic forecasting using deep learning adapted for traffic characteristics.
2/13/2026
MUSE: Multi-Tenant Model Serving With Seamless Model Updates
Multi-tenant model serving system handling seamless model updates with dynamic decision threshold management.
2/13/2026
Temperature as a Meta-Policy: Adaptive Temperature in LLM Reinforcement Learning
Framework treating temperature as adaptive meta-policy in LLM reinforcement learning to improve exploration-exploitation tradeoff.
2/13/2026
Safe Fairness Guarantees Without Demographics in Classification: Spectral Uncertainty Set Perspective
Method for fair classification without demographic information using spectral uncertainty sets.
2/13/2026
Evaluating LLM Safety Under Repeated Inference via Accelerated Prompt Stress Testing
Benchmark for evaluating LLM safety under repeated inference via prompt stress testing, addressing consistency failures in deployment.
2/13/2026
Latent-Variable Learning of SPDEs via Wiener Chaos
Method for learning stochastic partial differential equations from spatiotemporal observations using latent-variable formulation and deep learning.
2/13/2026
Temporal Difference Learning with Constrained Initial Representations
Enhances off-policy RL sample efficiency by constraining initial representations to address distribution shift and stabilize training.
2/13/2026
SpaTeoGL: Spatiotemporal Graph Learning for Interpretable Seizure Onset Zone Analysis from Intracranial EEG
SpaTeoGL framework uses spatiotemporal graph learning for interpretable seizure onset zone analysis from intracranial EEG data.
2/13/2026
TopoFair: Linking Topological Bias to Fairness in Link Prediction Benchmarks
TopoFair analyzes topological biases in graph link prediction benchmarks beyond homophily to improve fairness in recommendations.
2/13/2026
Deep Kernel Fusion for Transformers
DeepFusionKernel optimizes agentic LLM inference by fusing SwiGLU blocks, reducing memory bandwidth bottlenecks by 9-13% on A100/H100.
2/13/2026
CAAL: Confidence-Aware Active Learning for Heteroscedastic Atmospheric Regression
CAAL framework uses confidence-aware active learning to estimate atmospheric particle properties from limited observational data.
2/13/2026
Towards Sustainable Investment Policies Informed by Opponent Shaping
Multi-agent simulation study using opponent shaping for sustainable investment policies addressing climate change coordination.
2/13/2026
Robust Optimization Approach and Learning Based Hide-and-Seek Game for Resilient Network Design
Robust optimization approach for resilient network design with regenerators under link and node uncertainty.
2/13/2026
A$^{2}$V-SLP: Alignment-Aware Variational Modeling for Disentangled Sign Language Production
Proposes A²V-SLP, alignment-aware variational framework for disentangled sign language production using articulator-specific distributions.
2/13/2026
In-Context Function Learning in Large Language Models
Analyzes in-context learning in LLMs through Gaussian Process lens, studying function learning from few demonstrations at inference.
2/13/2026
Where Bits Matter in World Model Planning: A Paired Mixed-Bit Study for Efficient Spatial Reasoning
Studies mixed-bit quantization strategies for world model planning, analyzing where precision allocation matters most.
2/13/2026
Universal Diffusion-Based Probabilistic Downscaling
Diffusion-based framework downscales low-resolution weather forecasts to probabilistic high-resolution predictions without model-specific tuning.
2/13/2026
Mitigating Mismatch within Reference-based Preference Optimization
Addresses reference policy mismatch in DPO by handling pessimistic preference pairs where reference model prefers rejected responses.
2/13/2026
Learning Conditional Averages
Introduces PAC learning framework for predicting conditional averages over arbitrary neighborhoods rather than target concepts.
2/13/2026
Extending Puzzle for Mixture-of-Experts Reasoning Models with Application to GPT-OSS Acceleration
Extends Puzzle NAS framework to optimize gpt-oss-120B into 88B model using MoE pruning and attention optimization for inference acceleration.
2/13/2026
Temporally Unified Adversarial Perturbations for Time Series Forecasting
Proposes temporally consistent adversarial perturbations for time series forecasting models to improve robustness against attacks.
2/13/2026
Using predictive multiplicity to measure individual performance within the AI Act
Addresses predictive multiplicity in AI decision support systems, measuring individual performance disagreement under the AI Act framework.
2/13/2026
Towards Performance-Enhanced Model-Contrastive Federated Learning using Historical Information in Heterogeneous Scenarios
PMFL framework improves federated learning in heterogeneous scenarios using model-contrastive learning with historical training information.
2/13/2026
Are Two LLMs Better Than One? A Student-Teacher Dual-Head LLMs Architecture for Pharmaceutical Content Optimization
LRBTC system uses dual LLM and VLM architecture for automated quality control of pharmaceutical content covering regulatory, brand, and technical compliance.
2/13/2026
RAM-Net: Expressive Linear Attention with Selectively Addressable Memory
RAM-Net architecture combines linear attention efficiency with full attention expressivity using selectively addressable memory to reduce information loss.
2/13/2026
Manifold-Aware Temporal Domain Generalization for Large Language Models
Manifold-aware temporal domain generalization for LLMs handling distribution shifts via parameter-efficient geometric reformulation.
2/13/2026
Momentum LMS Theory beyond Stationarity: Stability, Tracking, and Regret
Momentum LMS theory for non-stationary streaming data analyzing stability and regret without i.i.d. assumptions.
2/13/2026
On the Sensitivity of Firing Rate-Based Federated Spiking Neural Networks to Differential Privacy
Analysis of differential privacy impact on firing-rate statistics in federated spiking neural networks for neuromorphic learning.
2/13/2026
FedGRPO: Privately Optimizing Foundation Models with Group-Relative Rewards from Domain Client
FedGRPO: federated learning method for foundation models using group-relative rewards from domain clients with privacy preservation.
2/13/2026
PrefillShare: A Shared Prefill Module for KV Reuse in Multi-LLM Disaggregated Serving
PrefillShare: shared prefill module reducing redundant computation across multiple LLMs in disaggregated serving with KV cache reuse.
2/13/2026
Fourier Transformers for Latent Crystallographic Diffusion and Generative Modeling
Reciprocal-space generative pipeline for crystalline materials using Fourier transforms and diffusion models with symmetry constraints.
2/13/2026
Improving HPC Code Generation Capability of LLMs via Online Reinforcement Learning with Real-Machine Benchmark Rewards
Online RL approach training LLMs for HPC code generation using real supercomputer runtime performance (GFLOPS) as rewards.
2/13/2026
PathCRF: Ball-Free Soccer Event Detection via Possession Path Inference from Player Trajectories
Automatic soccer event detection from player trajectories without ball tracking using possession path inference.
2/13/2026
Empirical Gaussian Processes
Empirical GPs: principled framework for learning kernel functions automatically rather than handcrafting from standard functions.
2/13/2026
Geometry of Uncertainty: Learning Metric Spaces for Multimodal State Estimation in RL
Novel method learning structured latent representations using metric spaces for multimodal state estimation in RL without explicit noise assumptions.
2/13/2026
On the Complexity of Offline Reinforcement Learning with $Q^\star$-Approximation and Partial Coverage
Theoretical analysis of offline RL under Q*-approximation and partial coverage, answering whether Q*-realizability enables sample efficiency.
2/13/2026
Few-Shot Design Optimization by Exploiting Auxiliary Information
Few-shot Bayesian optimization framework exploiting auxiliary information from experiments for expensive black-box design problems.
2/13/2026
KAN-FIF: Spline-Parameterized Lightweight Physics-based Tropical Cyclone Estimation on Meteorological Satellite
KAN-FIF applies spline-parameterized neural networks for tropical cyclone estimation on resource-constrained meteorological satellite devices.
2/13/2026
Meta-Sel: Efficient Demonstration Selection for In-Context Learning via Supervised Meta-Learning
Meta-Sel: lightweight supervised meta-learning approach for efficient demonstration selection in in-context learning with tight prompt budgets.
2/13/2026
Capability-Oriented Training Induced Alignment Risk
Investigates whether LLMs trained with RL spontaneously exploit reward function loopholes without malicious intent, examining alignment risks.
2/13/2026
Learning beyond Teacher: Generalized On-Policy Distillation with Reward Extrapolation
Theoretical analysis of on-policy distillation showing it as special case of KL-constrained RL with reward extrapolation improvements.
2/13/2026
Oscillators Are All You Need: Irregular Time Series Modelling via Damped Harmonic Oscillators with Closed-Form Solutions
Introduces damped harmonic oscillators method for irregular time series modeling as alternative to Transformers and Neural ODEs.
2/13/2026
It's TIME: Towards the Next Generation of Time Series Forecasting Benchmarks
Proposes TIME benchmark addressing limitations in time series foundation models including data composition, integrity, and task formulation issues.
2/13/2026
SafeNeuron: Neuron-Level Safety Alignment for Large Language Models
SafeNeuron provides neuron-level safety alignment mechanism for LLMs by targeting safety-critical parameters to prevent alignment bypass attacks.
2/13/2026
Amortized Molecular Optimization via Group Relative Policy Optimization
Group Relative Policy Optimization enables amortized molecular design learning transferable to unseen molecules rather than instance-specific optimization.