3/30/2026
Nonmyopic Global Optimisation via Approximate Dynamic Programming
Approximate dynamic programming approach for global optimization of expensive black-box functions as alternative to Gaussian process Bayesian optimization.
3/30/2026
Projection-free Algorithms for Online Convex Optimization with Adversarial Constraints
Projection-free algorithms for online convex optimization with time-varying adversarial constraints and regret bounds.
3/30/2026
How iteration order influences convergence and stability in deep learning
Theoretical analysis of how iteration order affects convergence and stability in deep neural network training without learning rate schedules.
3/30/2026
Robust Predictive Modeling Under Unseen Data Distribution Shifts: A Methodological Commentary
Methodological commentary on robust predictive modeling under distribution shifts in real-world deployment scenarios.
3/30/2026
Task Tokens: A Flexible Approach to Adapting Behavior Foundation Models
Task Tokens method adapts behavior foundation models to specific tasks via learnable tokens while preserving zero-shot generalization capabilities.
3/30/2026
FastCache: Fast Caching for Diffusion Transformer Through Learnable Linear Approximation
FastCache accelerates Diffusion Transformer inference through learnable linear approximation and spatial-aware token selection for hidden-state caching.
3/30/2026
Defending Against Knowledge Poisoning Attacks During Retrieval-Augmented Generation
Defends RAG systems against knowledge poisoning attacks by detecting and mitigating adversarial text injections in external knowledge sources.
3/30/2026
Masked Training for Robust Arrhythmia Detection from Digitalized Multiple Layout ECG Images
Masked training approach for robust arrhythmia detection from digitalized ECG images with temporal asynchrony and missing signal segments.
3/30/2026
PepThink-R1: LLM for Interpretable Cyclic Peptide Optimization with CoT SFT and Reinforcement Learning
PepThink-R1 integrates LLMs with chain-of-thought supervised fine-tuning and reinforcement learning for interpretable cyclic peptide design optimization.
3/30/2026
MarS-FM: Generative Modeling of Molecular Dynamics via Markov State Models
Generative model for molecular dynamics trajectories using Markov State Models to accelerate computational protein simulations.
3/30/2026
Large Language Models Can Perform Automatic Modulation Classification via Discretized Self-supervised Candidate Retrieval
LLMs perform automatic wireless modulation classification via discretized self-supervised candidate retrieval, avoiding distribution shift issues of supervised models.
3/30/2026
Activation Steering with a Feedback Controller
Control-theoretic framework for LLM activation steering with feedback controllers, connecting empirical steering methods to proportional control theory for safety alignment.
3/30/2026
NeST-BO: Fast Local Bayesian Optimization via Newton-Step Targeting of Gradient and Hessian Information
NeST-BO proposes Newton-step targeting Bayesian optimization using Gaussian processes to learn gradient and Hessian information for expensive black-box problems.
3/30/2026
Is the Hard-Label Cryptanalytic Model Extraction Really Polynomial?
Analyzes cryptanalytic model extraction attacks on ReLU-based DNNs with hard-label oracle access and polynomial-time complexity.
3/30/2026
Route Experts by Sequence, not by Token
Sequence-level TopK (SeqTopK) improves Mixture-of-Experts routing in LLMs by adapting expert assignment per sequence rather than per token without retraining.
3/30/2026
Cascading Bandits With Feedback
Cascading Bandits analyzes decision-making policies for edge inference with multiple models, providing theoretical regret guarantees for Explore-then-Commit and Thompson Sampling approaches.
3/30/2026
LiteCache: A Query Similarity-Driven, GPU-Centric KVCache Subsystem for Efficient LLM Inference
LiteCache optimizes KVCache memory management for LLM inference using GPU-centric query similarity-driven approach to reduce memory overhead and improve CUDA Graph execution.
3/30/2026
ReBaPL: Repulsive Bayesian Prompt Learning
Repulsive Bayesian Prompt Learning addresses overfitting in prompt learning for foundation models using Bayesian inference framework for improved out-of-distribution generalization.
3/30/2026
Aligning LLMs with Biomedical Knowledge using Balanced Fine-Tuning
Balanced Fine-Tuning aligns LLMs with biomedical knowledge through confidence-weighted token-level optimization and adaptive reward mechanisms.
3/30/2026
FedRE: A Representation Entanglement Framework for Model-Heterogeneous Federated Learning
FedRE proposes a representation entanglement framework enabling federated learning across clients with heterogeneous model architectures and data.
3/30/2026
SonicMoE: Accelerating MoE with IO and Tile-aware Optimizations
SonicMoE optimizes Mixture of Experts inference through IO-aware and tile-aware techniques for high-granularity, sparse MoE language models.
3/30/2026
PathFinder: Advancing Path Loss Prediction for Single-to-Multi-Transmitter Scenario
Deep learning approach for radio path loss prediction in 5G networks with improved generalization across multi-transmitter scenarios and distribution shifts.
3/30/2026
Concurrent training methods for Kolmogorov-Arnold networks: Disjoint datasets and FPGA implementation
Concurrent training enhancements for Kolmogorov-Arnold networks using Newton-Kaczmarz method with FPGA implementation for improved efficiency.
3/30/2026
The Dual-State Architecture for Reliable LLM Agents
Dual-State Action Pair (DSAP) primitive couples stochastic LLM generation with deterministic verification for reliable code generation agents.
3/30/2026
Mobility-Assisted Decentralized Federated Learning: Convergence Analysis and A Data-Driven Approach
Analyzes decentralized federated learning convergence with user mobility and data heterogeneity in next-gen wireless networks.
3/30/2026
Revisiting Diffusion Model Predictions Through Dimensionality
Provides theoretical framework explaining why diffusion models prefer direct data prediction over noise/velocity prediction in high-dimensional settings.
3/30/2026
Extending Puzzle for Mixture-of-Experts Reasoning Models with Application to GPT-OSS Acceleration
Extends Puzzle neural architecture search to reasoning LLMs, producing gpt-oss-puzzle-88B through MoE expert pruning and inference optimization.
3/30/2026
Quantization-Robust LLM Unlearning via Low-Rank Adaptation
Combines low-rank adaptation with quantization-aware unlearning to ensure LLM knowledge removal survives post-training 4-bit quantization.
3/30/2026
Golden Layers and Where to Find Them: Improved Knowledge Editing for Large Language Models Via Layer Gradient Analysis
Golden Layers method improves LLM knowledge editing via layer gradient analysis to identify optimal depth for updating model predictions per query.
3/30/2026
cc-Shapley: Measuring Multivariate Feature Importance Needs Causal Context
cc-Shapley extends Shapley values for multivariate feature importance by incorporating causal context to address spurious associations.
3/30/2026
Efficient Continual Learning in Language Models via Thalamically Routed Cortical Columns
TRC² architecture for continual learning in LLMs preventing catastrophic forgetting through decoder-only thalamic routing of cortical columns.
3/30/2026
Coverage-Aware Web Crawling for Domain-Specific Supplier Discovery via a Web--Knowledge--Web Pipeline
Web-Knowledge-Web pipeline iteratively crawls domain sources and knowledge graphs to discover small/medium enterprise suppliers with improved database coverage.
3/30/2026
Sinkhorn-Drifting Generative Models
Establishes theoretical connection between drifting generative dynamics and Sinkhorn divergence-induced gradient flows with cross-minus-self decomposition.
3/30/2026
AgentTrace: Causal Graph Tracing for Root Cause Analysis in Deployed Multi-Agent Systems
AgentTrace framework for post-hoc root cause analysis in deployed multi-agent systems via causal graph reconstruction from execution logs.
3/30/2026
Massive Redundancy in Gradient Transport Enables Sparse Online Learning
Exploits massive redundancy in gradient transport to reduce real-time recurrent learning computational cost from O(n^4) via random sparsity patterns.
3/30/2026
Neural Uncertainty Principle: A Unified View of Adversarial Fragility and LLM Hallucination
Connects adversarial robustness and LLM hallucinations through shared geometric principle formalized as Neural Uncertainty Principle with irreducible uncertainty bounds.
3/30/2026
Benchmarking Scientific Machine Learning Models for Air Quality Data
Benchmarks physics-guided and deep learning models for air quality index forecasting on region-specific datasets.
3/30/2026
mSFT: Addressing Dataset Mixtures Overfitting Heterogeneously in Multi-task SFT
mSFT algorithm addresses overfitting in multi-task supervised fine-tuning by dynamically adjusting data mixture ratios based on task-specific learning dynamics.
3/30/2026
Decoupling Exploration and Policy Optimization: Uncertainty Guided Tree Search for Hard Exploration
Decouples exploration from policy optimization in RL using uncertainty-guided tree search for efficient autonomous exploration without intrinsic motivation.
3/30/2026
COMPASS-Hedge: Learning Safely Without Knowing the World
Online learning algorithm balancing regret guarantees in adversarial/stochastic settings with safety constraints via COMPASS-Hedge method.
3/30/2026
A Heterogeneous Long-Micro Scale Cascading Architecture for General Aviation Health Management
Architecture for aircraft health monitoring balancing accuracy and computational constraints under class imbalance and environmental uncertainty.
3/30/2026
AI Generalisation Gap In Comorbid Sleep Disorder Staging
Deep learning approach for automated sleep staging in stroke patients with analysis of generalization gaps in clinical populations using Grad-CAM interpretations.
3/30/2026
Steering Code LLMs with Activation Directions for Language and Library Control
Method for steering code LLMs toward specific programming languages and libraries by manipulating activation space directions at inference time, tested on five language/library pairs across three open-weight models.
3/30/2026
The Alignment Tax: Response Homogenization in Aligned LLMs and Its Implications for Uncertainty Estimation
Analysis of response homogenization in RLHF-aligned LLMs showing reduced uncertainty estimation and implications for sampling.
3/30/2026
Missing-Aware Multimodal Fusion for Unified Microservice Incident Management
Multimodal fusion approach for microservice incident detection handling missing modalities without static imputation.
3/30/2026
Uncertainty-Guided Label Rebalancing for CPS Safety Monitoring
Uncertainty-guided rebalancing technique for safety monitoring in cyber-physical systems with imbalanced time-series data.
3/30/2026
Does Audio Deepfake Detection Generalize?
Analysis of generalization in audio deepfake detection across datasets and model architectures.
3/30/2026
CACTO-SL: Using Sobolev Learning to improve Continuous Actor-Critic with Trajectory Optimization
Actor-critic reinforcement learning approach combining trajectory optimization with Sobolev learning for optimal control.
3/30/2026
Towards Knowledge Guided Pretraining Approaches for Multimodal Foundation Models: Applications in Remote Sensing
Knowledge-guided pretraining framework for multimodal foundation models applied to remote sensing applications.
3/30/2026
Reproducibility and Artifact Consistency of the SIGIR 2022 Recommender Systems Papers Based on Message Passing
Reproducibility analysis of 10 graph-based neural recommender papers from SIGIR 2022 assessing methodology and impact.