4/6/2026
VALOR: Value-Aware Revenue Uplift Modeling with Treatment-Gated Representation for B2B Sales
VALOR framework for B2B sales revenue uplift modeling handling zero-inflated distributions with treatment-gated representation learning.
4/6/2026
Time-Warping Recurrent Neural Networks for Transfer Learning
Transfer learning method for RNNs using time-warping rescaling, with theoretical analysis for linear differential equation models.
4/6/2026
SEDGE: Structural Extrapolated Data Generation
Framework for generating synthetic data under specified conditions with approximate identifiability guarantees for data distribution extrapolation.
4/6/2026
Causal-Audit: A Framework for Risk Assessment of Assumption Violations in Time-Series Causal Discovery
Framework for validating assumptions in time-series causal discovery through calibrated risk assessment and effect-size diagnostics.
4/6/2026
Re-analysis of the Human Transcription Factor Atlas Recovers TF-Specific Signatures from Pooled Single-Cell Screens with Missing Controls
Re-analysis of transcription factor atlas single-cell perturbation screen with improved quality control pipeline and MORF barcode demultiplexing.
4/6/2026
AdaHOP: Fast and Accurate Low-Precision Training via Outlier-Pattern-Aware Rotation
Low-precision training method for LLMs using adaptive Hadamard transforms based on outlier patterns in weights, activations, and gradients.
4/6/2026
Jump Start or False Start? A Theoretical and Empirical Evaluation of LLM-initialized Bandits
Research on using LLM-generated synthetic data to warm-start contextual bandits, examining alignment between LLM choices and actual user preferences.
4/6/2026
A Spectral Framework for Multi-Scale Nonlinear Dimensionality Reduction
Spectral framework for multi-scale nonlinear dimensionality reduction balancing global-local structure preservation and expressiveness-transparency.
4/6/2026
Fast NF4 Dequantization Kernels for Large Language Model Inference
Optimized NF4 dequantization kernels for fast LLM inference on NVIDIA GPUs, addressing FP16 conversion bottleneck.
4/6/2026
Communication-Efficient Distributed Learning with Differential Privacy
Communication-efficient distributed learning algorithm with differential privacy using local training and gradient clipping.
4/6/2026
ROMAN: A Multiscale Routing Operator for Convolutional Time Series Models
ROMAN operator for time series that creates multiscale representations by building antialiased pyramids for convolutional classifiers.
4/6/2026
VoxelCodeBench: Benchmarking 3D World Modeling Through Code Generation
VoxelCodeBench platform benchmarking code generation models for 3D spatial reasoning with execution in Unreal Engine.
4/6/2026
Steerable but Not Decodable: Function Vectors Operate Beyond the Logit Lens
Analysis of function vectors in LLMs showing they steer behavior beyond logit lens interpretability across 4,032 cross-template transfer pairs.
4/6/2026
Complex-Valued GNNs for Distributed Basis-Invariant Control of Planar Systems
Complex-valued GNNs for distributed control of networked systems with basis-invariance for GPS and compass-denied environments.
4/6/2026
Analytic Drift Resister for Non-Exemplar Continual Graph Learning
Continual graph learning without storing exemplars, using class-level prototypes and analytic continual learning to address catastrophic forgetting.
4/6/2026
AXELRAM: Quantize Once, Never Dequantize
AXELRAM smart SRAM architecture computing attention scores from quantized KV cache without dequantization using orthogonal-transform quantization.
4/6/2026
Communication-free Sampling and 4D Hybrid Parallelism for Scalable Mini-batch GNN Training
Distributed GNN training with communication-free sampling and 4D hybrid parallelism for scaling mini-batch learning on large graphs.
4/6/2026
Generalization Limits of Reinforcement Learning Alignment
Study of generalization limits in RLHF alignment, proposing compound jailbreaks targeting LLM safety through redistribution of existing capabilities.
4/6/2026
Product-Stability: Provable Convergence for Gradient Descent on the Edge of Stability
Theoretical analysis of gradient descent training at edge of stability with product-stability property for convergence guarantees.
4/6/2026
Low-Rank Compression of Pretrained Models via Randomized Subspace Iteration
Low-rank compression of pretrained models using randomized subspace iteration for efficient SVD-based model reduction.
4/6/2026
A Numerical Method for Coupling Parameterized Physics-Informed Neural Networks and FDM for Advanced Thermal-Hydraulic System Simulation
Physics-informed neural networks coupled with finite difference methods for thermal-hydraulic system simulation.
4/6/2026
Cross-subject Muscle Fatigue Detection via Adversarial and Supervised Contrastive Learning with Inception-Attention Network
Muscle fatigue detection from sEMG signals using adversarial and contrastive learning with neural networks.
4/6/2026
Finding Belief Geometries with Sparse Autoencoders
Mechanistic interpretability research on whether LLMs encode belief geometries like transformers trained on hidden Markov models.
4/6/2026
Beyond Semantic Manipulation: Token-Space Attacks on Reward Models
Token-space attacks on reward models used in RLHF, introducing TOMPA framework for adversarial optimization beyond semantic manipulation.
4/6/2026
Adaptive Semantic Communication for Wireless Image Transmission Leveraging Mixture-of-Experts Mechanism
Semantic communication for wireless image transmission using mixture-of-experts to adapt to diverse image contents and channel conditions.
4/6/2026
LieTrunc-QNN: Lie Algebra Truncation and Quantum Expressivity Phase Transition from LiePrune to Provably Stable Quantum Neural Networks
Algebraic-geometric framework for quantum neural networks addressing barren plateaus and noise robustness.
4/6/2026
FluxMoE: Decoupling Expert Residency for High-Performance MoE Serving
FluxMoE system decouples expert residency to improve inference serving throughput in Mixture-of-Experts LLMs.
4/6/2026
Generative Frontiers: Why Evaluation Matters for Diffusion Language Models
Technical analysis of evaluation methodology challenges for diffusion language models at scale.
4/6/2026
Understanding Latent Diffusability via Fisher Geometry
Theoretical analysis of diffusion model degradation in latent spaces using Fisher geometry framework.
4/6/2026
STDDN: A Physics-Guided Deep Learning Framework for Crowd Simulation
Physics-guided deep learning framework combining microscopic and macroscopic approaches for crowd simulation.
4/6/2026
Towards Realistic Class-Incremental Learning with Free-Flow Increments
Free-flow class-incremental learning framework handling realistic variable-sized task streams without fixed task schedules.
4/6/2026
Random Is Hard to Beat: Active Selection in online DPO with Modern LLMs
Study comparing active preference learning vs random sampling for online DPO data selection in modern LLMs.
4/6/2026
Structure-Aware Commitment Reduction for Network-Constrained Unit Commitment with Solver-Preserving Guarantees
Learning-guided approach for reducing computational burden in network-constrained unit commitment optimization.
4/6/2026
Toward an Operational GNN-Based Multimesh Surrogate for Fast Flood Forecasting
GNN-based surrogate model for accelerating hydraulic flood forecasting simulations.
4/6/2026
Extracting Money Laundering Transactions from Quasi-Temporal Graph Representation
Graph-based ML approach for detecting money laundering transactions in financial networks.
4/6/2026
Efficient Logistic Regression with Mixture of Sigmoids
Computational analysis of exponential weights algorithm for online logistic regression with improved complexity bounds.
4/6/2026
Towards Near-Real-Time Telemetry-Aware Routing with Neural Routing Algorithms
Neural routing algorithms for network traffic optimization using live telemetry data with near-real-time latency.
4/6/2026
Explainable Machine Learning Reveals 12-Fold Ucp1 Upregulation and Thermogenic Reprogramming in Female Mouse White Adipose Tissue After 37 Days of Microgravity: First AI/ML Analysis of NASA OSD-970
ML analysis of NASA space biology dataset revealing thermogenic reprogramming in female mouse adipose tissue.
4/6/2026
Mitigating Reward Hacking in RLHF via Advantage Sign Robustness
Addresses reward hacking in RLHF by using advantage sign robustness to prevent policy degradation.
4/6/2026
FedSQ: Optimized Weight Averaging via Fixed Gating
Federated learning optimization via fixed gating for weight averaging under statistical heterogeneity.
4/6/2026
Co-Evolution of Policy and Internal Reward for Language Agents
Self-Guide framework for LLM agents using co-evolved internal rewards to address sparse reward problem in long-horizon tasks.
4/6/2026
Self-Distilled RLVR
On-policy self-distillation training paradigm for LLMs combining dense signals from larger teacher models.
4/6/2026
DSBD: Dual-Aligned Structural Basis Distillation for Graph Domain Adaptation
Graph domain adaptation method addressing structural discrepancies in graph neural networks under topology shifts.
4/6/2026
Understanding the Role of Hallucination in Reinforcement Post-Training of Multimodal Reasoning Models
arXiv paper analyzes hallucination's role in RL post-training of multimodal LLMs, investigating whether models genuinely learn visual information under RL.
4/6/2026
PRISM: LLM-Guided Semantic Clustering for High-Precision Topics
arXiv paper proposes PRISM, combining LLM-guided labeling with semantic clustering for interpretable topic modeling with low computational cost.
4/6/2026
Reflective Context Learning: Studying the Optimization Primitives of Context Space
arXiv paper studies context space optimization for generally capable agents, examining credit assignment, forgetting, and overfitting in context learning.
4/6/2026
Real-Time Surrogate Modeling for Personalized Blood Flow Prediction and Hemodynamic Analysis
arXiv paper on surrogate modeling for real-time blood flow prediction and hemodynamic cardiovascular analysis.
4/6/2026
Enhancing Robustness of Federated Learning via Server Learning
arXiv paper exploring server learning to enhance federated learning robustness against malicious attacks with non-IID client data.
4/6/2026
MLFCIL: A Multi-Level Forgetting Mitigation Framework for Federated Class-Incremental Learning in LEO Satellites
arXiv paper on federated class-incremental learning for LEO satellites addressing non-IID data, memory, and communication constraints.
4/6/2026
Fighting AI with AI: AI-Agent Augmented DNS Blocking of LLM Services during Student Evaluations
arXiv paper proposes AI-agent-augmented DNS blocking to prevent LLM access during student evaluations, addressing academic integrity concerns.