4/2/2026
Exploring Silent Data Corruption as a Reliability Challenge in LLM Training
Analysis of silent data corruption during LLM training on hardware, studying gradient corruption impacts and detection mechanisms.
4/2/2026
Spectral Compact Training: Pre-Training Large Language Models via Permanent Truncated SVD and Stiefel QR Retraction
Spectral Compact Training method reduces LLM training memory footprint by replacing dense weight matrices with truncated SVD factors.
4/2/2026
BioCOMPASS: Integrating Biomarkers into Transformer-Based Immunotherapy Response Prediction
Transformer-based model with biomarkers for immunotherapy response prediction, improving generalization across diverse cancer datasets.
4/2/2026
ActivityNarrated: An Open-Ended Narrative Paradigm for Wearable Human Activity Understanding
Open-ended narrative framework for wearable human activity recognition using compositional, unscripted activities instead of closed-set classification.
4/2/2026
Thinking Wrong in Silence: Backdoor Attacks on Continuous Latent Reasoning
ThoughtSteer backdoor attack exploiting continuous reasoning in language models that operate silently in hidden states without token output.
4/2/2026
Using predefined vector systems to speed up neural network multimillion class classification
Method to reduce neural network multi-class classification complexity from O(n) to O(1) by leveraging known latent space geometry properties.
4/2/2026
Scalable Pretraining of Large Mixture of Experts Language Models on Aurora Super Computer
Optimus training library for pretraining mixture-of-experts LLMs at exascale on Aurora supercomputer, demonstrating 1000s GPU tile scaling.
4/2/2026
MIRANDA: MId-feature RANk-adversarial Domain Adaptation toward climate change-robust ecological forecasting with deep learning
Deep learning method for plant phenology prediction using domain adaptation to improve climate change forecasting in ecological systems.
4/2/2026
Cost-Penalized Fitness in FMA-Orchestrated Mixture of Experts: Experimental Evidence for Molecular Memory in Domain Adaptation
Experimental evaluation of Free-Market Algorithm orchestrated Mixture-of-Experts with cost-penalized fitness for domain adaptation.
4/2/2026
Optimal Brain Decomposition for Accurate LLM Low-Rank Approximation
Optimal decomposition technique for low-rank approximation of LLM weights enabling efficient fine-tuning and inference.
4/2/2026
Learning to Learn-at-Test-Time: Language Agents with Learnable Adaptation Policies
Method for language agents to optimize test-time adaptation policies through iterative refinement during inference.
4/2/2026
Policy Improvement Reinforcement Learning
Reinforcement learning approach with verification for iteratively improving LLM policies based on actual performance gains.
4/2/2026
Fatigue-Aware Learning to Defer via Constrained Optimisation
Framework for human-AI cooperation that models fatigue-induced performance degradation in learning-to-defer systems.
4/2/2026
Event Embedding of Protein Networks : Compositional Learning of Biological Function
Compositional embedding method for protein networks using additive sequence models on biological interaction data.
4/2/2026
Orthogonal Learner for Estimating Heterogeneous Long-Term Treatment Effects
Orthogonal learning approach for estimating heterogeneous long-term treatment effects combining experiments and observational data.
4/2/2026
WARP: Guaranteed Inner-Layer Repair of NLP Transformers
Method for verifiable repair of transformer vulnerabilities to adversarial perturbations with inner-layer guarantees.
4/2/2026
Flow-based Policy With Distributional Reinforcement Learning in Trajectory Optimization
Flow-based reinforcement learning policy with distributional approach for capturing multimodal solutions in trajectory optimization.
4/2/2026
EmbedPart: Embedding-Driven Graph Partitioning for Scalable Graph Neural Network Training
Graph partitioning technique using embeddings to enable scalable distributed training of graph neural networks.
4/2/2026
Transfer learning for nonparametric Bayesian networks
Transfer learning methodologies for Bayesian network structure learning with scarce data.
4/2/2026
Model-Based Learning of Near-Optimal Finite-Window Policies in POMDPs
Model-based learning approach for finite-window policies in partially observable Markov decision processes.
4/2/2026
Fast and Accurate Probing of In-Training LLMs' Downstream Performances
Method for efficiently evaluating LLM downstream performance during training without expensive full inference.
4/2/2026
Approximating Pareto Frontiers in Stochastic Multi-Objective Optimization via Hashing and Randomization
Algorithmic approach to multi-objective optimization via hashing and randomization for identifying Pareto frontiers.
4/2/2026
Reconsidering Dependency Networks from an Information Geometry Perspective
Theoretical analysis of dependency networks using information geometry perspective for modeling complex systems.
4/2/2026
Toward Personalized Darts Training: A Data-Driven Framework Based on Skeleton-Based Biomechanical Analysis and Motion Modeling
Data-driven sports training framework using skeleton-based biomechanical analysis and motion modeling for dart throwing.
4/2/2026
Property-Level Flood Risk Assessment Using AI-Enabled Street-View Lowest Floor Elevation Extraction and ML Imputation Across Texas
AI pipeline extracting building elevation data from street-view imagery with ML imputation for flood risk assessment.
4/2/2026
Reasoning Shift: How Context Silently Shortens LLM Reasoning
Analysis showing how irrelevant context degrades LLM reasoning performance despite test-time scaling capabilities.
4/2/2026
Bridging the Simulation-to-Experiment Gap with Generative Models using Adversarial Distribution Alignment
Generative model approach using adversarial distribution alignment to bridge simulation-to-experiment gap in scientific domains.
4/2/2026
Online Reasoning Calibration: Test-Time Training Enables Generalizable Conformal LLM Reasoning
ORCA framework calibrating LLM sampling through conformal prediction to improve test-time reasoning efficiency and generalization.
4/2/2026
NeuroDDAF: Neural Dynamic Diffusion-Advection Fields with Evidential Fusion for Air Quality Forecasting
Physics-informed neural network combining diffusion-advection with evidential fusion for air quality forecasting.
4/2/2026
Screening Is Enough
Multiscreen mechanism for language models enabling absolute query-key relevance assessment beyond relative attention redistribution.
4/2/2026
CliffSearch: Structured Agentic Co-Evolution over Theory and Code for Scientific Algorithm Discovery
CliffSearch agent framework for scientific algorithm discovery combining LLM-guided search with structured evolution of theory and code.
4/2/2026
The Recipe Matters More Than the Kitchen:Mathematical Foundations of the AI Weather Prediction Pipeline
Mathematical framework analyzing what determines forecast skill in AI weather prediction, emphasizing training methodology over architecture.
4/2/2026
LAtent Phase Inference from Short time sequences using SHallow REcurrent Decoders (LAPIS-SHRED)
LAPIS-SHRED method for reconstructing spatio-temporal dynamics from sparse observations using shallow recurrent decoders.
4/2/2026
An Empirical Recipe for Universal Phone Recognition
PhoneticXEUS model for robust multilingual phone recognition trained on large-scale data with pretrained representations.
4/2/2026
Scalable Identification and Prioritization of Requisition-Specific Personal Competencies Using Large Language Models
LLM-based recruitment tool identifying requisition-specific competencies through dynamic few-shot prompting and reflection.
4/2/2026
Multi-lingual Multi-institutional Electronic Health Record based Predictive Model
Text-based harmonization approach using LLMs to unify multi-institutional EHR data without explicit schema standardization.
4/2/2026
Decomposable Reward Modeling and Realistic Environment Design for Reinforcement Learning-Based Forex Trading
Modular RL framework with decomposable reward modeling and realistic environment design for Forex trading applications.
4/2/2026
Isomorphic Functionalities between Ant Colony and Ensemble Learning: Part II-On the Strength of Weak Learnability and the Boosting Paradigm
Mathematical analysis establishing isomorphism between ant colony behavior and ensemble learning methods like boosting.
4/2/2026
Large Language Models for Analyzing Enterprise Architecture Debt in Unstructured Documentation
LLM-based approach to identify enterprise architecture debt indicators from unstructured documentation in organizations.
4/2/2026
Generalizable Dense Reward for Long-Horizon Robotic Tasks
Framework combining vision language models with RL for dense reward generation in long-horizon robotic tasks to reduce manual reward engineering.
4/2/2026
GenoBERT: A Language Model for Accurate Genotype Imputation
GenoBERT uses transformers for reference-free genotype imputation without ancestry bias.
4/2/2026
Scaled Gradient Descent for Ill-Conditioned Low-Rank Matrix Recovery with Optimal Sampling Complexity
Theoretical analysis of scaled gradient descent for low-rank matrix recovery with optimal sampling complexity.
4/2/2026
Forecast collapse of transformer-based models under squared loss in financial time series
Analysis of transformer forecast collapse under squared loss for financial time series with weak conditional structure.
4/2/2026
Genetic algorithms for multi-omic feature selection: a comparative study in cancer survival analysis
Genetic algorithms for multi-objective feature selection in cancer biomarker discovery from omics data.
4/2/2026
Hierarchical Pre-Training of Vision Encoders with Large Language Models
HIVE framework for hierarchical pre-training of vision encoders integrated with large language models for vision-language alignment.
4/2/2026
Efficient Software Vulnerability Detection Using Transformer-based Models
Transformer-based models for detecting software vulnerabilities in C/C++ using program slices.
4/2/2026
Finite-Time Analysis of Projected Two-Time-Scale Stochastic Approximation
Finite-time convergence analysis of two-time-scale stochastic approximation algorithms.
4/2/2026
Risk-Aware Batch Testing for Performance Regression Detection
Performance regression detection for CI systems using risk-aware batch testing and predictive models.
4/2/2026
Hybrid Energy-Based Models for Physical AI: Provably Stable Identification of Port-Hamiltonian Dynamics
Energy-based models for stable system identification in physical AI using port-Hamiltonian dynamics.
4/2/2026
Data-Driven Reachability Analysis via Diffusion Models with PAC Guarantees
Data-driven reachability analysis for dynamical systems using diffusion models with PAC theoretical guarantees.