4/2/2026
MF-QAT: Multi-Format Quantization-Aware Training for Elastic Inference
arXiv: Multi-format quantization-aware training enables single model robustness across multiple numeric precisions for elastic inference.
4/2/2026
Learning Shared Representations for Multi-Task Linear Bandits
arXiv: Multi-task representation learning in linear bandits with shared latent representations for knowledge transfer.
4/2/2026
Learning from Many and Adapting to the Unknown in Open-set Test Streams
arXiv: Test-time adaptation for LLMs under continual distribution shift and open-set tasks, preserving source knowledge.
4/2/2026
HabitatAgent: An End-to-End Multi-Agent System for Housing Consultation
arXiv: HabitatAgent multi-agent LLM system for housing consultation with transparent reasoning and factuality guarantees.
4/2/2026
Representation choice shapes the interpretation of protein conformational dynamics
arXiv: Study on how representation choice affects interpretation of protein conformational dynamics from molecular dynamics simulations.
4/2/2026
Predicting Dynamics of Ultra-Large Complex Systems by Inferring Governing Equations
arXiv: Sparse Identification Graph Neural Network for discovering interpretable governing equations in ultra-large complex systems.
4/2/2026
A Survey of On-Policy Distillation for Large Language Models
arXiv survey: On-policy distillation transfers reasoning from frontier LLMs to smaller models, addressing exposure bias in knowledge distillation.
4/2/2026
Chameleons do not Forget: Prompt-Based Online Continual Learning for Next Activity Prediction
arXiv: Prompt-based online continual learning for next activity prediction in dynamic processes using catastrophic forgetting mitigation.
4/2/2026
Embedded Variational Neural Stochastic Differential Equations for Learning Heterogeneous Dynamics
arXiv: Variational Neural Stochastic Differential Equations model complex socioeconomic time-series data with heterogeneous dynamics.
4/2/2026
Full-Gradient Successor Feature Representations
arXiv: Full-gradient successor feature representations improve convergence guarantees for transfer learning in RL with non-linear function approximation.
4/2/2026
Performance of Neural and Polynomial Operator Surrogates
arXiv: Empirical comparison of neural operator surrogates including Fourier neural operators vs polynomial methods for parametric PDEs.
4/2/2026
Learning to Hint for Reinforcement Learning
arXiv: Group Relative Policy Optimization for RL addresses advantage collapse in reinforcement learning with verifiable rewards using hints.
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.