2/25/2026
Controllable Exploration in Hybrid-Policy RLVR for Multi-Modal Reasoning
Hybrid-policy reinforcement learning framework for multi-modal LLMs with exploration strategy to prevent entropy collapse during RL training.
2/25/2026
IMOVNO+: A Regional Partitioning and Meta-Heuristic Ensemble Framework for Imbalanced Multi-Class Learning
Framework addressing class imbalance, overlap, and noise in multi-class learning using regional partitioning and meta-heuristic ensembles.
2/25/2026
Golden Layers and Where to Find Them: Improved Knowledge Editing for Large Language Models Via Layer Gradient Analysis
Layer gradient analysis method for identifying optimal layers for knowledge editing in LLMs while preserving model behavior.
2/25/2026
Model Merging in the Essential Subspace
ESM framework for merging multiple task-specific fine-tuned models using principal component analysis to reduce task interference.
2/25/2026
Multimodal Crystal Flow: Any-to-Any Modality Generation for Unified Crystal Modeling
Unified multimodal generative framework for crystal structure prediction and de novo generation across different modalities.
2/25/2026
KnapSpec: Self-Speculative Decoding via Adaptive Layer Selection as a Knapsack Problem
KnapSpec framework reformulates self-speculative decoding as knapsack problem to optimize LLM inference throughput through adaptive layer selection.
2/25/2026
MultiModalPFN: Extending Prior-Data Fitted Networks for Multimodal Tabular Learning
Extension of TabPFN foundation model to handle multimodal tabular data integrating images, text, and tables in unified framework.
2/25/2026
Exploring Anti-Aging Literature via ConvexTopics and Large Language Models
Convex optimization-based clustering algorithm with LLM integration for analyzing biomedical literature and detecting trends in anti-aging research.
2/25/2026
Coupled Cluster con M\=oLe: Molecular Orbital Learning for Neural Wavefunctions
Neural wavefunction approach combining coupled-cluster theory with learnable molecular orbitals for quantum chemistry calculations.
2/25/2026
Uncertainty-Aware Delivery Delay Duration Prediction via Multi-Task Deep Learning
Multi-task deep learning model for delivery delay prediction in complex logistics networks with uncertainty quantification.
2/25/2026
The Truthfulness Spectrum Hypothesis
Study of LLM truthfulness representations across domain-general and domain-specific directions using probe generalization across five truth types.
2/25/2026
Discrete Diffusion with Sample-Efficient Estimators for Conditionals
Discrete diffusion framework using sample-efficient estimators for generative modeling over discrete state spaces with conditional probabilities.
2/25/2026
Learning to Solve Complex Problems via Dataset Decomposition
Curriculum learning approach that recursively decomposes complex datasets into simpler components using teacher-student framework with step-by-step reasoning.
2/25/2026
Shape-informed cardiac mechanics surrogates in data-scarce regimes via geometric encoding and generative augmentation
Surrogate models for cardiac mechanics using geometric encoding and generative augmentation in data-scarce clinical settings.
2/25/2026
In-context Pre-trained Time-Series Foundation Models adapt to Unseen Tasks
Time-series foundation models augmented with in-context learning to adapt to unseen tasks without fine-tuning.
2/25/2026
QuantVLA: Scale-Calibrated Post-Training Quantization for Vision-Language-Action Models
QuantVLA: post-training quantization framework for Vision-Language-Action models to reduce compute and memory demands for embodied AI agents.
2/25/2026
CaDrift: A Time-dependent Causal Generator of Drifting Data Streams
CaDrift: synthetic data generator using Structural Causal Models to create data streams with controlled distributional and covariate shifts for evaluating ML methods.
2/25/2026
Emergent Manifold Separability during Reasoning in Large Language Models
Analysis of representation geometry dynamics during chain-of-thought reasoning in LLMs using manifold capacity theory.
2/25/2026
Hierarchical Molecular Representation Learning via Fragment-Based Self-Supervised Embedding Prediction
Self-supervised graph learning method incorporating fragment-level information for molecular representation learning.
2/25/2026
Momentum Guidance: Plug-and-Play Guidance for Flow Models
Plug-and-play guidance method for flow-based generative models improving sample fidelity without doubling inference cost.
2/25/2026
Quantitative Approximation Rates for Group Equivariant Learning
Quantitative approximation rates for neural networks with group equivariance constraints.
2/25/2026
cc-Shapley: Measuring Multivariate Feature Importance Needs Causal Context
Method incorporating causal context into Shapley values for accurate multivariate feature importance measurement.
2/25/2026
GeoPT: Scaling Physics Simulation via Lifted Geometric Pre-Training
Pre-training framework leveraging geometric data for efficient neural physics simulation with better transfer.
2/25/2026
Three Concrete Challenges and Two Hopes for the Safety of Unsupervised Elicitation
Analysis of safety challenges in unsupervised elicitation techniques for steering language models toward truthful outputs.
2/25/2026
Wasserstein Distributionally Robust Online Learning
Online learning algorithm with Wasserstein distributionally robust optimization for risk-averse sequential decisions.
2/25/2026
$\kappa$-Explorer: A Unified Framework for Active Model Estimation in MDPs
Framework for active exploration and model estimation in tabular MDPs based on coverage-based complexity.
2/25/2026
CREDIT: Certified Ownership Verification of Deep Neural Networks Against Model Extraction Attacks
Certification method for verifying DNN ownership against model extraction attacks in MLaaS systems.
2/25/2026
GauS: Differentiable Scheduling Optimization via Gaussian Reparameterization
Differentiable framework using Gaussian reparameterization for scheduling optimization in compilation and synthesis.
2/25/2026
Protein Language Models Diverge from Natural Language: Comparative Analysis and Improved Inference
Analysis of how protein language models diverge from natural language transformers with improved inference methods.
2/25/2026
Oracle-Robust Online Alignment for Large Language Models
Online alignment method for LLMs under misspecified preference feedback, extending SAIL framework.
2/25/2026
Nonparametric Teaching of Attention Learners
Attention Neural Teaching paradigm to reduce training costs for transformer-based attention learners.
2/25/2026
A Long-Short Flow-Map Perspective for Drifting Models
Theoretical analysis of drifting models via flow-map decomposition for generative modeling.
2/25/2026
Elimination-compensation pruning for fully-connected neural networks
Neural network pruning technique balancing compression and information preservation in fully-connected networks.
2/25/2026
CGSTA: Cross-Scale Graph Contrast with Stability-Aware Alignment for Multivariate Time-Series Anomaly Detection
Graph neural network approach for detecting anomalies in multivariate time-series data with noise robustness.
2/25/2026
VINA: Variational Invertible Neural Architectures
Research on normalizing flows and invertible neural networks for generative modeling and inverse problems.
2/25/2026
Wireless Federated Multi-Task LLM Fine-Tuning via Sparse-and-Orthogonal LoRA
Decentralized federated learning approach for multi-task LLM fine-tuning using sparse-orthogonal LoRA over wireless connections.
2/25/2026
A Generalized Apprenticeship Learning Framework for Capturing Evolving Student Pedagogical Strategies
Apprenticeship learning framework for intelligent tutoring systems addressing sample efficiency and reward function design in educational RL.
2/25/2026
Memory-guided Prototypical Co-occurrence Learning for Mixed Emotion Recognition
Memory-guided prototypical learning approach for mixed emotion recognition from multi-modal physiological and behavioral signals.
2/25/2026
Actor-Curator: Co-adaptive Curriculum Learning via Policy-Improvement Bandits for RL Post-Training
ACTOR-CURATOR framework for automated curriculum learning in LLM reinforcement learning post-training via policy-improvement bandits.
2/25/2026
Sample-efficient evidence estimation of score based priors for model selection
Sample-efficient model evidence estimation for prior selection in Bayesian inverse problems using diffusion models.
2/25/2026
GENSR: Symbolic Regression Based in Equation Generative Space
GenSR framework for symbolic regression using generative latent space to improve equation discovery from data.
2/25/2026
Stability and Generalization of Push-Sum Based Decentralized Optimization over Directed Graphs
Theoretical analysis of Push-Sum decentralized optimization over directed graphs with stability and generalization guarantees.
2/25/2026
Benchmarking GNN Models on Molecular Regression Tasks with CKA-Based Representation Analysis
Benchmarks GNN models on molecular property prediction using CKA-based representation analysis of SMILES fingerprints.
2/25/2026
GATES: Self-Distillation under Privileged Context with Consensus Gating
Proposes GATES, a self-distillation method with consensus gating for document-grounded QA without ground truth labels.
2/25/2026
Upper-Linearizability of Online Non-Monotone DR-Submodular Maximization over Down-Closed Convex Sets
Studies online maximization of non-monotone DR-submodular functions over convex sets with improved regret bounds.
2/25/2026
Is the Trigger Essential? A Feature-Based Triggerless Backdoor Attack in Vertical Federated Learning
Demonstrates triggerless backdoor attacks in vertical federated learning exploiting feature manipulations without visible triggers.
2/25/2026
QEDBENCH: Quantifying the Alignment Gap in Automated Evaluation of University-Level Mathematical Proofs
Introduces QEDBench benchmark quantifying alignment gaps in LLM-as-judge evaluation of university-level mathematical proofs.
2/25/2026
TrajGPT-R: Generating Urban Mobility Trajectory with Reinforcement Learning-Enhanced Generative Pre-trained Transformer
Proposes TrajGPT-R, a transformer with reinforcement learning for generating privacy-preserving urban mobility trajectories at scale.
2/25/2026
Sparse Bayesian Deep Functional Learning with Structured Region Selection
Develops Bayesian deep functional learning with structured region selection for sparse effects in complex continuous data.
2/25/2026
UrbanFM: Scaling Urban Spatio-Temporal Foundation Models
Proposes UrbanFM, a spatio-temporal foundation model for urban systems that generalizes across regions and tasks.