3/20/2026
Causal Intervention Framework for Variational Auto Encoder Mechanistic Interpretability
Causal intervention framework for interpreting Variational Autoencoders mechanistically, addressing interpretability of generative models.
3/20/2026
Modality Equilibrium Matters: Minor-Modality-Aware Adaptive Alternating for Cross-Modal Memory Enhancement
Shapley Value-based alternating training framework for multimodal fusion that balances dominant and minor modalities.
3/20/2026
Size-adaptive Hypothesis Testing for Fairness
Statistical framework for fairness testing in algorithmic systems that accounts for sampling error and handles intersectional demographic analysis.
3/20/2026
On the Surprising Effectiveness of a Single Global Merging in Decentralized Learning
Analysis of communication scheduling in decentralized learning showing benefits of concentrating synchronization in later training stages.
3/20/2026
GeoReg: Weight-Constrained Few-Shot Regression for Socio-Economic Estimation using LLM
GeoReg uses LLMs with satellite imagery and geospatial data for socio-economic indicator estimation in data-scarce regions via few-shot regression.
3/20/2026
Online Convex Optimization with Heavy Tails: Old Algorithms, New Regrets, and Applications
Research on Online Convex Optimization algorithms for heavy-tailed gradient distributions, extending beyond finite variance assumptions.
3/20/2026
Physics-informed neural network for predicting fatigue life of unirradiated and irradiated austenitic and ferritic/martensitic steels under reactor-relevant conditions
Physics-informed neural network framework predicting fatigue life of steels under nuclear reactor conditions.
3/20/2026
Fourier Learning Machines: Nonharmonic Fourier-Based Neural Networks for Scientific Machine Learning
Neural network architecture using nonharmonic Fourier series for scientific machine learning applications.
3/20/2026
Pi-transformer: A prior-informed dual-attention model for multivariate time-series anomaly detection
Transformer architecture with dual attention for multivariate time-series anomaly detection using temporal invariants.
3/20/2026
Closed-form $\ell_r$ norm scaling with data for overparameterized linear regression and diagonal linear networks under $\ell_p$ bias
Theoretical analysis of parameter norm scaling in overparameterized linear regression and diagonal networks.
3/20/2026
Investigating Faithfulness in Large Audio Language Models
Framework evaluating faithfulness of chain-of-thought reasoning in large audio language models for multimodal tasks.
3/20/2026
OT-MeanFlow3D: Bridging Optimal Transport and Meanflow for Efficient 3D Point Cloud Generation
Flow-matching models for 3D point cloud generation using optimal transport and meanflow for single-step inference acceleration.
3/20/2026
Splines-Based Feature Importance in Kolmogorov-Arnold Networks: A Framework for Supervised Tabular Data Dimensionality Reduction
KAN-based feature selection framework for tabular data via spline-based importance scoring. Specialized ML technique.
3/20/2026
Support Basis: Fast Attention Beyond Bounded Entries
Sub-quadratic attention algorithm removing bounded-entry restrictions for LLM inference speedup. Foundational LLM efficiency research.
3/20/2026
Activation Quantization of Vision Encoders Needs Prefixing Registers
Quantization technique for vision encoders using prefix registers to handle outliers. Optimization research for multimodal models.
3/20/2026
An Improved Model-Free Decision-Estimation Coefficient with Applications in Adversarial MDPs
Theoretical reinforcement learning on decision-estimation coefficients for adversarial MDPs. Pure RL theory.
3/20/2026
FlowCast: Advancing Precipitation Nowcasting with Conditional Flow Matching
Conditional flow matching for precipitation forecasting. Weather prediction ML, not core AI interests.
3/20/2026
Image2Gcode: Image-to-G-code Generation for Additive Manufacturing Using Diffusion-Transformer Model
Diffusion-Transformer model converting images directly to G-code for 3D printing. Applied ML, domain-specific.
3/20/2026
Evolved Sample Weights for Bias Mitigation: Effectiveness Depends on the Fairness Objective
Genetic algorithm for sample reweighting to mitigate ML bias. Fairness-focused, not primary tech interests.
3/20/2026
Heads collapse, features stay: Why Replay needs big buffers
Continual learning research on replay buffer size impact on feature retention vs. classifier forgetting. Specialized ML theory.
3/20/2026
Capturing reduced-order quantum many-body dynamics out of equilibrium via neural ordinary differential equations
Neural ODEs for quantum many-body dynamics simulation. Physics-focused ML, not core AI interests.
3/20/2026
Weights to Code: Extracting Interpretable Algorithms from the Discrete Transformer
Algorithm extraction from Discrete Transformers via symbolic program synthesis. Addresses representation entanglement in interpretability.
3/20/2026
DeeperBrain: A Neuro-Grounded EEG Foundation Model Towards Universal BCI
EEG foundation model for brain-computer interfaces with biophysical grounding. Neuroscience domain, not AI/tech stack focused.
3/20/2026
Mechanism Shift During Post-training from Autoregressive to Masked Diffusion Language Models
Research analyzing mechanistic changes when post-training autoregressive models into masked diffusion models. Studies model internals via circuit analysis.
3/20/2026
Multimodal Machine Learning for Soft High-k Elastomers under Data Scarcity
Machine learning for materials science: multimodal models predict dielectric elastomer properties under limited data. Domain-specific ML, not AI-focused.
3/20/2026
A Unified Generalization Framework for Model Merging: Trade-offs, Non-Linearity, and Scaling Laws
Unified theoretical framework for model merging explaining effectiveness across heterogeneous fine-tuning hyperparameters with scaling laws.
3/20/2026
Mixed-Precision Training and Compilation for RRAM-based Computing-in-Memory Accelerators
Mixed-precision training and compilation techniques for RRAM-based computing-in-memory ML accelerators with low bit-width constraints.
3/20/2026
Sheaf Neural Networks and biomedical applications
Application of sheaf neural networks to biomedical problems comparing performance against GCNs, GATs, and GraphSage.
3/20/2026
Koopman Autoencoders with Continuous-Time Latent Dynamics for Fluid Dynamics Forecasting
Continuous-time Koopman autoencoder for surrogate modeling of time-dependent PDEs in fluid dynamics.
3/20/2026
Krause Synchronization Transformers
Krause Attention: principled attention mechanism addressing representation collapse and attention sink issues in transformers.
3/20/2026
TS-Haystack: A Multi-Scale Retrieval Benchmark for Time Series Language Models
Multi-scale retrieval benchmark for time series language models addressing long-context temporal localization under computational constraints.
3/20/2026
Causality is Key for Interpretability Claims to Generalise
Position paper on causal inference requirements for valid and generalizable interpretability claims in LLM research.
3/20/2026
Stable Deep Reinforcement Learning via Isotropic Gaussian Representations
Deep reinforcement learning stability improvement through isotropic Gaussian embeddings under non-stationary training dynamics.
3/20/2026
Benchmarking State Space Models, Transformers, and Recurrent Networks for US Grid Forecasting
Benchmark comparing state space models, transformers, and RNNs for US power grid electricity demand forecasting.
3/20/2026
Improving Spatial Allocation for Energy System Coupling with Graph Neural Networks
Graph neural network approach for spatial allocation in energy system coupling with mismatched resolutions.
3/20/2026
CeRA: Breaking the Linear Ceiling of Low-Rank Adaptation via Manifold Expansion
CeRA: improved parameter-efficient fine-tuning method that surpasses LoRA's linear constraints via manifold expansion with gating and dropout.
3/20/2026
Optimizer-Induced Low-Dimensional Drift and Transverse Dynamics in Transformer Training
Analysis of transformer training trajectories under AdamW showing low-dimensional drift directions and batch-gradient alignment patterns.
3/20/2026
What You Read is What You Classify: Highlighting Attributions to Text and Text-Like Inputs
Explainable AI method for highlighting token attributions in text classification using transformers.
3/20/2026
AutoResearch-RL: Perpetual Self-Evaluating Reinforcement Learning Agents for Autonomous Neural Architecture Discovery
Framework for autonomous neural architecture and hyperparameter search using self-evaluating RL agents without human supervision.
3/20/2026
Adversarial Latent-State Training for Robust Policies in Partially Observable Domains
Research on robust policy training in partially observable reinforcement learning under adversarial latent state distribution shifts.
3/20/2026
A Unified View of Drifting and Score-Based Models
Theoretical analysis connecting drifting models and score-based generative models through kernel-based transport discrepancy.
3/20/2026
Systematic Scaling Analysis of Jailbreak Attacks in Large Language Models
Systematic study of jailbreak attack scaling laws across LLM methods and model families using compute-bounded optimization framework.
3/20/2026
Representation Finetuning for Continual Learning
Research on parameter-efficient fine-tuning for continual learning using representation-level optimization instead of weight-level black-box methods.
3/20/2026
PREBA: Surgical Duration Prediction via PCA-Weighted Retrieval-Augmented LLMs and Bayesian Averaging Aggregation
Zero-shot surgical duration prediction combining retrieval-augmented LLMs with Bayesian averaging for resource management.
3/20/2026
A Stability-Aware Frozen Euler Autoencoder for Physics-Informed Tracking in Continuum Mechanics (SAFE-PIT-CM)
Physics-informed autoencoder with frozen PDE solver for tracking continuum mechanics dynamics in video.
3/20/2026
Privacy-Preserving Machine Learning for IoT: A Cross-Paradigm Survey and Future Roadmap
Survey of privacy-preserving machine learning mechanisms for IoT devices covering federated learning and edge computing approaches.
3/20/2026
Spectral Edge Dynamics of Training Trajectories: Signal--Noise Geometry Across Scales
Analysis of transformer training dynamics via Spectral Edge Dynamics, identifying coherent optimization directions vs stochastic noise.
3/20/2026
SCALE:Scalable Conditional Atlas-Level Endpoint transport for virtual cell perturbation prediction
Virtual cell perturbation prediction model using optimal transport for in silico experimentation on genetic/chemical perturbations.
3/20/2026
Flow Matching Policy with Entropy Regularization
Diffusion-based reinforcement learning policy using flow matching with direct entropy regularization and efficient gradient computation.
3/20/2026
Exploring AI in Fashion: A Review of Aesthetics, Personalization, Virtual Try-On, and Forecasting
Comprehensive review of AI methods in fashion including aesthetics, personalization, virtual try-on, and forecasting.