3/11/2026
IMSE: Intrinsic Mixture of Spectral Experts Fine-tuning for Test-Time Adaptation
Test-time adaptation method using spectral experts in Vision Transformers to handle distribution shift with minimal parameter updates.
3/11/2026
A prospective clinical feasibility study of a conversational diagnostic AI in an ambulatory primary care clinic
Clinical feasibility study of LLM-based conversational AI (AMIE) for patient diagnostic history-taking in real-world primary care workflows with safety assessment.
3/11/2026
PostTrainBench: Can LLM Agents Automate LLM Post-Training?
PostTrainBench benchmark evaluating whether LLM agents can automate post-training of base LLMs into assistants.
3/11/2026
Equitable Multi-Task Learning for AI-RANs
OWO-FMTL framework for fair multi-task learning in AI-enabled radio access networks with equitable user performance.
3/11/2026
Hindsight Credit Assignment for Long-Horizon LLM Agents
HCAPO framework addressing credit assignment in long-horizon LLM agent tasks using hindsight and value baseline alignment.
3/11/2026
SPREAD: Subspace Representation Distillation for Lifelong Imitation Learning
SPREAD framework for lifelong imitation learning preserving task representation manifolds across sequential skill acquisition without catastrophic forgetting.
3/11/2026
Multi-level meta-reinforcement learning with skill-based curriculum
Multi-level meta-reinforcement learning with skill-based curriculum for hierarchical sequential decision-making through MDP compression.
3/11/2026
The Temporal Markov Transition Field
Temporal Markov Transition Field extension handling non-stationary time series by tracking regime changes instead of using global transition matrix.
3/11/2026
SoftJAX & SoftTorch: Empowering Automatic Differentiation Libraries with Informative Gradients
SoftJAX and SoftTorch extensions enabling informative gradients for hard primitives like thresholding and discrete operations in automatic differentiation frameworks.
3/11/2026
Are Expressive Encoders Necessary for Discrete Graph Generation?
GenGNN modular framework for discrete graph generation achieving competitive validity with graph Transformers at 2-5x faster inference speed.
3/11/2026
Expressivity-Efficiency Tradeoffs for Hybrid Sequence Models
Study of hybrid sequence models combining Transformers and state-space models, analyzing expressivity-efficiency tradeoffs and mechanisms for performance benefits.
3/11/2026
A New Modeling to Feature Selection Based on the Fuzzy Rough Set Theory in Normal and Optimistic States on Hybrid Information Systems
Feature selection method for hybrid information systems using fuzzy rough set theory to reduce dimensionality in big data scenarios.
3/11/2026
Cross-Domain Uncertainty Quantification for Selective Prediction: A Comprehensive Bound Ablation with Transfer-Informed Betting
Comprehensive ablation of confidence bounds for selective prediction with risk control, introducing Transfer-Informed Betting for cross-domain uncertainty quantification.
3/11/2026
Quantifying Memorization and Privacy Risks in Genomic Language Models
Study of memorization and privacy risks in genomic language models trained on sensitive DNA sequence data, assessing data leakage concerns.
3/11/2026
Uncovering a Winning Lottery Ticket with Continuously Relaxed Bernoulli Gates
Strong Lottery Ticket method using continuously relaxed Bernoulli gates to find sparse subnetworks in over-parameterized networks without weight training.
3/11/2026
The $qs$ Inequality: Quantifying the Double Penalty of Mixture-of-Experts at Inference
Analysis of Mixture-of-Experts inference inefficiency identifying double penalty from microbatch fragmentation and reduced KV cache headroom during decoding.
3/11/2026
Semantic Level of Detail: Multi-Scale Knowledge Representation via Heat Kernel Diffusion on Hyperbolic Manifolds
Semantic Level of Detail introduces continuous resolution control for knowledge graphs via heat kernel diffusion, enabling agents to navigate abstraction levels.
3/11/2026
MAcPNN: Mutual Assisted Learning on Data Streams with Temporal Dependence
MAcPNN proposes mutual assisted learning for IoT edge devices handling streaming data with temporal dependencies and concept drift without catastrophic forgetting.
3/11/2026
MAPLE: Elevating Medical Reasoning from Statistical Consensus to Process-Led Alignment
MAPLE framework improves medical LLM reasoning by replacing majority voting with process-led alignment in test-time reinforcement learning for clinical decision-making.
3/11/2026
An accurate flatness measure to estimate the generalization performance of CNN models
Flatness measure for CNN generalization based on Hessian spectrum accounting for convolutional architecture-specific geometric structure.
3/11/2026
When to Retrain after Drift: A Data-Only Test of Post-Drift Data Size Sufficiency
CALIPER: data-only detector estimating post-drift data size sufficiency for stable model retraining after concept drift in data streams.
3/11/2026
Two Teachers Better Than One: Hardware-Physics Co-Guided Distributed Scientific Machine Learning
Distributed scientific ML approach co-guiding models with hardware and physics constraints for edge processing without central data aggregation.
3/11/2026
SCALAR: Learning and Composing Skills through LLM Guided Symbolic Planning and Deep RL Grounding
SCALAR framework coupling LLM planning with deep RL through learned skill libraries, enabling agents to ground language into low-level control with iterative correction.
3/11/2026
Sim2Act: Robust Simulation-to-Decision Learning via Adversarial Calibration and Group-Relative Perturbation
Simulation-to-decision learning framework addressing prediction errors in simulators through adversarial calibration for reliable policy training in industrial domains.
3/11/2026
Dynamic Multi-period Experts for Online Time Series Forecasting
Dynamic multi-period experts framework for online time series forecasting handling recurring and emergent concept drift.
3/11/2026
Learning Adaptive LLM Decoding
Learning adaptive decoding policies for LLMs that dynamically select sampling strategies based on prompt difficulty and compute.
3/11/2026
Exclusive Self Attention
Exclusive self-attention mechanism constraining attention to orthogonal information for improved Transformer language modeling.
3/11/2026
Not All News Is Equal: Topic- and Event-Conditional Sentiment from Finetuned LLMs for Aluminum Price Forecasting
Finetuned LLM sentiment analysis from news for aluminum price forecasting under different market conditions.
3/11/2026
Decoupling Reasoning and Confidence: Resurrecting Calibration in Reinforcement Learning from Verifiable Rewards
Method to decouple reasoning from confidence in LLM RL training, addressing over-confidence calibration issues.
3/11/2026
Causally Sufficient and Necessary Feature Expansion for Class-Incremental Learning
Causal feature expansion approach for class-incremental learning addressing catastrophic forgetting and feature collisions.
3/11/2026
Wrong Code, Right Structure: Learning Netlist Representations from Imperfect LLM-Generated RTL
Learning netlist representations from imperfect LLM-generated RTL code for hardware design without large labeled datasets.
3/11/2026
Latent-DARM: Bridging Discrete Diffusion And Autoregressive Models For Reasoning
Hybrid model combining discrete diffusion and autoregressive language models for improved multi-agent reasoning and planning.
3/11/2026
$P^2$GNN: Two Prototype Sets to boost GNN Performance
Graph neural network improvement using dual prototype sets to handle global context and noisy local neighborhoods.
3/11/2026
The Radio-Frequency Transformer for Signal Separation
Transformer-based signal separator for isolating signals from non-Gaussian interference using learned tokenization.
3/11/2026
Strategically Robust Multi-Agent Reinforcement Learning with Linear Function Approximation
Game-theoretic approach to multi-agent RL using risk-sensitive equilibrium for robust and efficient agent coordination.
3/11/2026
Beyond Test-Time Training: Learning to Reason via Hardware-Efficient Optimal Control
Optimal control formulation for reasoning in language models to enable planning and goal-directed action selection.
3/11/2026
Efficient Reasoning at Fixed Test-Time Cost via Length-Aware Attention Priors and Gain-Aware Training
Methods for efficient reasoning in Transformers at fixed test-time cost using attention priors and training techniques.
3/11/2026
DendroNN: Dendrocentric Neural Networks for Energy-Efficient Classification of Event-Based Data
Spiking neural networks for spatiotemporal event-based data classification with improved energy efficiency and temporal decoding.
3/11/2026
A Gaussian Comparison Theorem for Training Dynamics in Machine Learning
Theoretical analysis connecting training dynamics in Gaussian mixture models to surrogate systems using Gordon comparison theorem.
3/11/2026
Reward-Zero: Language Embedding Driven Implicit Reward Mechanisms for Reinforcement Learning
Reward-Zero: implicit reward mechanism using language embeddings to derive progress signals for reinforcement learning without explicit reward functions.
3/11/2026
TA-GGAD: Testing-time Adaptive Graph Model for Generalist Graph Anomaly Detection
Graph neural network model for detecting anomalies across multiple domains with adaptive testing-time mechanisms to handle domain shift.
3/11/2026
Democratising Clinical AI through Dataset Condensation for Classical Clinical Models
Dataset condensation method for clinical ML models using synthetic data and differential privacy to democratize healthcare AI while protecting patient privacy.
3/11/2026
From Representation to Clusters: A Contrastive Learning Approach for Attributed Hypergraph Clustering
Contrastive learning approach for attributed hypergraph clustering with direct clustering supervision integration.
3/11/2026
SPAARS: Safer RL Policy Alignment through Abstract Exploration and Refined Exploitation of Action Space
SPAARS: offline-to-online RL safety method for robotics using abstract exploration and refined action space exploitation.
3/11/2026
Impact of Markov Decision Process Design on Sim-to-Real Reinforcement Learning
Analysis of MDP design choices impact on sim-to-real transfer in reinforcement learning for industrial process control.
3/11/2026
From Weighting to Modeling: A Nonparametric Estimator for Off-Policy Evaluation
Nonparametric off-policy evaluation method for contextual bandits addressing limitations of inverse probability weighting.
3/11/2026
Temporal-Conditioned Normalizing Flows for Multivariate Time Series Anomaly Detection
Temporal-conditioned normalizing flows framework for multivariate time series anomaly detection with uncertainty modeling.
3/11/2026
Compiler-First State Space Duality and Portable $O(1)$ Autoregressive Caching for Inference
XLA-compatible state space model inference implementation enabling O(1) autoregressive caching without NVIDIA hardware dependency.
3/11/2026
Learning Bayesian and Markov Networks with an Unreliable Oracle
Constraint-based structure learning for Markov and Bayesian networks with unreliable conditional independence oracles.
3/11/2026
An Optimal Control Approach To Transformer Training
Optimal control-theoretic framework for transformer training with structured constraints and McKean-Vlasov dynamics.