3/10/2026
Drift-to-Action Controllers: Budgeted Interventions with Online Risk Certificates
Drift2Act controller for handling distribution drift in deployed ML systems with budgeted interventions and online risk certificates.
3/10/2026
DualFlexKAN: Dual-stage Kolmogorov-Arnold Networks with Independent Function Control
DualFlexKAN extends Kolmogorov-Arnold Networks with learnable dual-stage functions to address quadratic parameter scaling and architectural limitations.
3/10/2026
Towards Batch-to-Streaming Deep Reinforcement Learning for Continuous Control
Streaming deep reinforcement learning method for continuous control on resource-limited hardware using online updates without replay buffers.
3/10/2026
Don't Look Back in Anger: MAGIC Net for Streaming Continual Learning with Temporal Dependence
MAGIC Net approach for streaming continual learning that combines architectural strategies with RNNs to handle concept drift and temporal dependence.
3/10/2026
Grow, Don't Overwrite: Fine-tuning Without Forgetting
Function-preserving expansion method for fine-tuning pre-trained models without catastrophic forgetting by replicating model capacity.
3/10/2026
Divide and Predict: An Architecture for Input Space Partitioning and Enhanced Accuracy
Input space partitioning architecture using data heterogeneity measures to improve supervised learning accuracy on mixture-of-distributions data.
3/10/2026
Group Entropies and Mirror Duality: A Class of Flexible Mirror Descent Updates for Machine Learning
Theoretical framework connecting group theory and group entropies to mirror descent optimization algorithms for flexible machine learning updates.
3/10/2026
How Far Can Unsupervised RLVR Scale LLM Training?
Comprehensive analysis of unsupervised reinforcement learning with verifiable rewards for scaling LLM training without supervision bottleneck, including taxonomy and experiments.
3/10/2026
Split Federated Learning Architectures for High-Accuracy and Low-Delay Model Training
Split Federated Learning architecture optimization for improving training accuracy and reducing delay in distributed ML model training.
3/10/2026
Impermanent: A Live Benchmark for Temporal Generalization in Time Series Forecasting
Impermanent benchmark for evaluating temporal generalization in time-series forecasting models, addressing data contamination issues in foundation models.
3/10/2026
XInsight: Integrative Stage-Consistent Psychological Counseling Support Agents for Digital Well-Being
XInsight multi-agent framework for LLM-driven psychological counseling support with stage-consistent workflow aligned to therapeutic practices.
3/10/2026
Hierarchical Latent Structures in Data Generation Process Unify Mechanistic Phenomena across Scale
Research on unified understanding of phenomena in Transformer language models through hierarchical latent structures in data generation processes.
3/10/2026
Hierarchical Embedding Fusion for Retrieval-Augmented Code Generation
Hierarchical Embedding Fusion method for retrieval-augmented code generation that compresses repositories into dense vector hierarchies to reduce inference cost and context noise.
3/10/2026
Multi-Agent DRL for V2X Resource Allocation: Disentangling Challenges and Benchmarking Solutions
Multi-agent deep reinforcement learning for radio resource allocation in V2X networks, addressing challenges like non-stationarity, coordination, and partial observability.
3/10/2026
Scaling Strategy, Not Compute: A Stand-Alone, Open-Source StarCraft II Benchmark for Accessible Reinforcement Learning Research
Open-source StarCraft II benchmark for reinforcement learning research with accessible compute requirements and curriculum design capabilities.
3/10/2026
GraphSkill: Documentation-Guided Hierarchical Retrieval-Augmented Coding for Complex Graph Reasoning
GraphSkill: LLM-based approach for complex graph reasoning using retrieval-augmented code generation with documentation guidance.
3/10/2026
RECAP: Local Hebbian Prototype Learning as a Self-Organizing Readout for Reservoir Dynamics
RECAP: Reservoir computing approach using local Hebbian plasticity for image recognition, inspired by biological neural mechanisms.
3/10/2026
Roots Beneath the Cut: Uncovering the Risk of Concept Revival in Pruning-Based Unlearning for Diffusion Models
Research on risks of pruning-based unlearning in diffusion models, identifying concept revival dangers in weight pruning approaches.
3/10/2026
Quantum Deep Learning: A Comprehensive Review
Comprehensive review of quantum deep learning approaches integrating quantum/quantum-inspired resources with deep learning.
3/10/2026
How the Graph Construction Technique Shapes Performance in IoT Botnet Detection
Study evaluating how graph construction methods affect GNN performance for IoT botnet detection.
3/10/2026
Approximate Nearest Neighbor Search for Modern AI: A Projection-Augmented Graph Approach
Graph-based approximate nearest neighbor search optimized for modern AI workloads with online insertion support.
3/10/2026
HyperTokens: Controlling Token Dynamics for Continual Video-Language Understanding
HyperTokens generates task-specific prompt tokens for continual video-language understanding with multimodal LLMs.
3/10/2026
XAI and Few-shot-based Hybrid Classification Model for Plant Leaf Disease Prognosis
Hybrid few-shot learning model combining XAI and FSL for plant leaf disease classification under limited training data.
3/10/2026
Chart Deep Research in LVLMs via Parallel Relative Policy Optimization
Parallel Relative Policy Optimization for improving chart understanding in large vision-language models with deep reasoning capabilities.
3/10/2026
Soft Equivariance Regularization for Invariant Self-Supervised Learning
Soft equivariance regularization augments invariance-based self-supervised learning to preserve transformation-dependent structure for robustness.
3/10/2026
On the Generalization Capacities of MLLMs for Spatial Intelligence
Analysis of multimodal LLM generalization showing RGB-only approaches fail to generalize across cameras due to camera parameter entanglement.
3/10/2026
PolyBlocks: A Compiler Infrastructure for AI Chips and Programming Frameworks
PolyBlocks MLIR-based compiler infrastructure for AI chips and frameworks using analytical cost models for automated high-performance code generation.
3/10/2026
Best-of-Tails: Bridging Optimism and Pessimism in Inference-Time Alignment
Best-of-Tails method for inference-time alignment balancing optimism and pessimism in LLM candidate selection with imperfect reward models.
3/10/2026
CREDO: Epistemic-Aware Conformalized Credal Envelopes for Regression
CREDO combines conformal prediction with credal methods for regression with distribution-free coverage and epistemic uncertainty quantification.
3/10/2026
Symmetry-Constrained Language-Guided Program Synthesis for Discovering Governing Equations from Noisy and Partial Observations
SymLang framework uses language-guided program synthesis with symmetry constraints to discover governing equations from noisy experimental data.
3/10/2026
Fairness May Backfire: When Leveling-Down Occurs in Fair Machine Learning
Analysis of fairness constraints in ML systems showing when enforcing fairness leads to worse outcomes for affected groups.
3/10/2026
A Dynamic Self-Evolving Extraction System
Self-evolving NLP extraction system that adapts to domain-specific taxonomies and emerging terminology in specialized fields like medical and legal.
3/10/2026
How Private Are DNA Embeddings? Inverting Foundation Model Representations of Genomic Sequences
Privacy analysis of DNA foundation model embeddings showing inversion attacks can reconstruct genomic sequences from shared embeddings.
3/10/2026
Post-Training with Policy Gradients: Optimality and the Base Model Barrier
Theoretical analysis of post-training linear autoregressive models with policy gradients, proving convergence properties under margin conditions.
3/10/2026
Topology-Aware Reinforcement Learning over Graphs for Resilient Power Distribution Networks
Graph-based reinforcement learning framework for power distribution network resilience incorporating topological features for outage management.
3/10/2026
Adaptive Discovery of Interpretable Audio Attributes with Multimodal LLMs for Low-Resource Classification
Method for discovering interpretable audio attributes using multimodal LLMs for low-resource audio classification with high reliability.
3/10/2026
Can Safety Emerge from Weak Supervision? A Systematic Analysis of Small Language Models
Analysis of safety alignment in small language models using weak supervision and Self-MOA approach for reducing human annotation costs while maintaining usefulness.
3/10/2026
VLN-Cache: Enabling Token Caching for VLN Models with Visual/Semantic Dynamics Awareness
Token caching optimization for vision-language navigation models accounting for visual and semantic dynamics to reduce inference cost.
3/10/2026
StructSAM: Structure- and Spectrum-Preserving Token Merging for Segment Anything Models
Token merging optimization for Segment Anything Model to improve inference speed while preserving segmentation quality and handling SAM's attention architecture.
3/10/2026
AgrI Challenge: A Data-Centric AI Competition for Cross-Team Validation in Agricultural Vision
Agricultural vision competition focused on data-centric AI and model generalization under real-world distribution shifts rather than model design alone.
3/10/2026
Generalization in Online Reinforcement Learning for Mobile Agents
Research on generalization of RL-trained vision-language mobile agents for GUI automation. Addresses lack of standardized benchmarks and open-source RL systems for interactive task learning.
3/10/2026
Few Tokens, Big Leverage: Preserving Safety Alignment by Constraining Safety Tokens during Fine-tuning
Method for preserving LLM safety alignment during fine-tuning by constraining safety-critical tokens, addressing alignment drift.
3/10/2026
Dial: A Knowledge-Grounded Dialect-Specific NL2SQL System
Knowledge-grounded NL2SQL system handling heterogeneous SQL dialects with semantic correctness and dialect-specific syntax compliance.
3/10/2026
The Dual-Stream Transformer: Channelized Architecture for Interpretable Language Modeling
Transformer variant decomposing residual stream into token and context components for interpretable language modeling.
3/10/2026
Trusting What You Cannot See: Auditable Fine-Tuning and Inference for Proprietary AI
Framework for auditable fine-tuning and inference of proprietary LLMs on cloud platforms with cryptographic verification.
3/10/2026
Probabilistic Inference and Learning with Stein's Method
Monograph on probabilistic inference and learning theory using Stein's method with applications to variational gradient descent.
3/10/2026
Towards Lightweight Adaptation of Speech Enhancement Models in Real-World Environments
Lightweight on-device adaptation framework for speech enhancement models addressing dynamic acoustic scene changes with frozen backbone.
3/10/2026
DreamSAC: Learning Hamiltonian World Models via Symmetry Exploration
World model learning approach using symmetry exploration to capture physical invariances and conservation laws for extrapolative generalization.
3/10/2026
COOL-MC: Verifying and Explaining RL Policies for Multi-bridge Network Maintenance
Tool for verifying and explaining RL policies for multi-bridge network maintenance with formal safety guarantees and interpretability.
3/10/2026
GRD-Net: Generative-Reconstructive-Discriminative Anomaly Detection with Region of Interest Attention Module
Generative-reconstructive-discriminative network with ROI attention for industrial surface defect detection and localization.