3/2/2026
Memory Caching: RNNs with Growing Memory
Memory caching architecture enabling RNNs with growing memory capacity and subquadratic complexity as alternative to Transformers for sequence modeling.
3/2/2026
Taming Momentum: Rethinking Optimizer States Through Low-Rank Approximation
Low-rank approximation method (LoRA-Pre) for optimizer memory efficiency in Adam and Muon, reducing overhead for large language model training.
3/2/2026
CUDA Agent: Large-Scale Agentic RL for High-Performance CUDA Kernel Generation
Agentic RL system using LLMs for high-performance CUDA kernel generation at scale, outcompeting traditional compiler-based approaches.
3/2/2026
Pacing Opinion Polarization via Graph Reinforcement Learning
Graph reinforcement learning approach to moderate opinion polarization in social networks under Friedkin-Johnsen model with improved scalability.
3/2/2026
On De-Individuated Neurons: Continuous Symmetries Enable Dynamic Topologies
Methodology for dynamic neural networks using isotropic activation functions enabling real-time architectural growth and shrinkage via symmetry-principled primitives.
3/2/2026
Lap2: Revisiting Laplace DP-SGD for High Dimensions via Majorization Theory
Improves Laplace mechanism for differentially private SGD in high-dimensional models using majorization theory, applicable to LLM fine-tuning.
3/2/2026
Few-Shot Continual Learning for 3D Brain MRI with Frozen Foundation Models
Few-shot continual learning approach for 3D brain MRI using frozen foundation models with task-specific LoRA modules for tumor segmentation and brain age estimation.
3/2/2026
Causal Identification from Counterfactual Data: Completeness and Bounding Results
Completeness and bounding results for causal identification using counterfactual data from Layer 3 of Pearl's Causal Hierarchy.
3/2/2026
VaSST: Variational Inference for Symbolic Regression using Soft Symbolic Trees
Probabilistic framework for symbolic regression using variational inference over soft symbolic trees for scientific discovery with uncertainty quantification.
3/2/2026
Construct, Merge, Solve & Adapt with Reinforcement Learning for the min-max Multiple Traveling Salesman Problem
Hybrid reinforcement learning approach (RL-CMSA) for solving min-max multiple traveling salesman problems with iterative construction and adaptation.
3/2/2026
Hyperdimensional Cross-Modal Alignment of Frozen Language and Image Models for Efficient Image Captioning
Efficient image captioning via hyperdimensional cross-modal alignment of frozen language and vision models without multimodal fine-tuning.
3/2/2026
Moment Matters: Mean and Variance Causal Graph Discovery from Heteroscedastic Observational Data
Causal discovery method distinguishing whether variables influence the mean versus variance of other variables in heteroscedastic data.
3/2/2026
Geodesic Semantic Search: Learning Local Riemannian Metrics for Citation Graph Retrieval
Retrieval system learning node-specific Riemannian metrics for geometry-aware semantic search on citation graphs.
3/2/2026
General Bayesian Policy Learning
General Bayes framework for policy learning where decision rules are the target rather than outcome prediction.
3/2/2026
Any Model, Any Place, Any Time: Get Remote Sensing Foundation Model Embeddings On Demand
Platform for standardized access to remote sensing foundation model embeddings across heterogeneous model formats and interfaces.
3/2/2026
From Static Benchmarks to Dynamic Protocol: Agent-Centric Text Anomaly Detection for Evaluating LLM Reasoning
Dynamic benchmarking protocol where AI agents autonomously generate, validate, and solve problems to evaluate LLM reasoning capabilities beyond static datasets.
3/2/2026
GLUScope: A Tool for Analyzing GLU Neurons in Transformer Language Models
Open-source interpretability tool for analyzing gated activation functions (SwiGLU) in transformer neurons across recent language models.
3/2/2026
Enhancing Continual Learning for Software Vulnerability Prediction: Addressing Catastrophic Forgetting via Hybrid-Confidence-Aware Selective Replay for Temporal LLM Fine-Tuning
Addresses catastrophic forgetting in continual fine-tuning of LLMs for vulnerability detection in source code, using selective replay with LoRA on temporal distribution shifts.
3/2/2026
MI$^2$DAS: A Multi-Layer Intrusion Detection Framework with Incremental Learning for Securing Industrial IoT Networks
MI²DAS: multi-layer intrusion detection framework for IIoT with incremental learning to detect novel attacks in dynamic environments.
3/2/2026
Exploring Robust Intrusion Detection: A Benchmark Study of Feature Transferability in IoT Botnet Attack Detection
Benchmark study evaluating cross-domain transferability of flow-based feature sets across IoT and IIoT datasets for intrusion detection.
3/2/2026
RF-Agent: Automated Reward Function Design via Language Agent Tree Search
RF-Agent: automated reward function design for reinforcement learning using LLM-based tree search to optimize low-level control tasks.
3/2/2026
Experience-Guided Self-Adaptive Cascaded Agents for Breast Cancer Screening and Diagnosis with Reduced Biopsy Referrals
BUSD-Agent: cascaded multi-agent framework for breast ultrasound screening and diagnosis reducing biopsy referrals through selective decision-making.
3/2/2026
Learning to Build: Autonomous Robotic Assembly of Stable Structures Without Predefined Plans
Autonomous robotic assembly framework using reinforcement learning for constructing stable structures without predefined plans.
3/2/2026
Benchmarking BERT-based Models for Sentence-level Topic Classification in Nepali Language
Benchmarking 10 BERT variants for Nepali sentence-level topic classification, evaluating multilingual and Indic-specific models.
3/2/2026
Jailbreak Foundry: From Papers to Runnable Attacks for Reproducible Benchmarking
Jailbreak Foundry: multi-agent system translating jailbreak papers into executable modules for unified benchmarking and reproducible LLM robustness evaluation.
3/2/2026
Data Driven Optimization of GPU efficiency for Distributed LLM Adapter Serving
Data-driven optimization pipeline for GPU efficiency in distributed LLM adapter serving, maximizing throughput with concurrent adapter hosting.
3/2/2026
Unsupervised Baseline Clustering and Incremental Adaptation for IoT Device Traffic Profiling
Two-stage unsupervised pipeline for IoT device traffic profiling with incremental model adaptation using density-based clustering.
3/2/2026
The Subjectivity of Monoculture
Analysis of monoculture in LLMs showing agreement metrics depend on subjective baseline assumptions for independence.
3/2/2026
Artificial Agency Program: Curiosity, compression, and communication in agents
Artificial Agency Program: research agenda for building resource-bounded AI agents driven by curiosity-as-learning-progress and human-tool integration.
3/2/2026
A multimodal slice discovery framework for systematic failure detection and explanation in medical image classification
Automated auditing framework for detecting systematic failures in medical image classifiers using multimodal features and slice discovery.
3/2/2026
Uncertainty Quantification for Multimodal Large Language Models with Incoherence-adjusted Semantic Volume
Proposes uncertainty quantification method for multimodal LLMs using incoherence-adjusted semantic volume for reliable deployment.
3/2/2026
SenCache: Accelerating Diffusion Model Inference via Sensitivity-Aware Caching
SenCache: training-free acceleration for diffusion model inference via sensitivity-aware caching of model outputs across timesteps.
3/2/2026
Compositional Generalization Requires Linear, Orthogonal Representations in Vision Embedding Models
Formalizes desiderata showing compositional generalization requires linear, orthogonal representations in vision embedding models.
3/2/2026
Mode Seeking meets Mean Seeking for Fast Long Video Generation
Proposes training paradigm decoupling local fidelity from long-term coherence for scaling video generation from seconds to minutes.
3/2/2026
TimeMAE: Self-Supervised Representations of Time Series with Decoupled Masked Autoencoders
TimeMAE: self-supervised framework for learning transferable time series representations using decoupled masked autoencoders.
3/2/2026
Less is more -- the Dispatcher/ Executor principle for multi-task Reinforcement Learning
Proposes dispatcher/executor principle for multi-task reinforcement learning that abstracts unnecessary details for better generalization.
3/2/2026
Joint Distribution-Informed Shapley Values for Sparse Counterfactual Explanations
Introduces COLA framework for generating sparse counterfactual explanations using optimal transport and Shapley-based attribution methods.
3/2/2026
Quantifying Climate Change Impacts on Renewable Energy Generation: A Super-Resolution Recurrent Diffusion Model
Super-resolution recurrent diffusion model for renewable energy generation under climate change impacts.
3/2/2026
Rethinking Uncertainty Estimation in LLMs: A Principled Single-Sequence Measure
Single-sequence uncertainty estimation method for LLMs addressing computational expense of multi-sequence approaches.
3/2/2026
The Sample Complexity of Online Reinforcement Learning: A Multi-model Perspective
Sample complexity analysis for online reinforcement learning in nonlinear continuous state/action spaces.
3/2/2026
InfoBridge: Mutual Information estimation via Bridge Matching
Mutual information estimation method using diffusion bridge models for improved domain transfer problems.
3/2/2026
Semantic Parallelism: Redefining Efficient MoE Inference via Model-Data Co-Scheduling
Novel semantic parallelism approach for efficient MoE model inference via co-scheduling of model and data placement.
3/2/2026
Probabilistic Neural Networks (PNNs) with t-Distributed Outputs: Adaptive Prediction Intervals Beyond Gaussian Assumptions
Probabilistic neural networks using t-distribution outputs for improved prediction intervals beyond Gaussian assumptions.
3/2/2026
What Makes a Reward Model a Good Teacher? An Optimization Perspective
Optimization perspective on reward model quality for RLHF, analyzing factors beyond accuracy that make effective teachers.
3/2/2026
Operator Learning with Domain Decomposition for Geometry Generalization in PDE Solving
Domain decomposition approach for neural operators solving PDEs with improved geometry generalization capabilities.
3/2/2026
Sparsity Forcing: Reinforcing Token Sparsity of MLLMs
Research on enforcing token sparsity in multimodal LLMs to reduce computational overhead while maintaining accuracy.
3/2/2026
PAPN: Proximity Attention Encoder and Pointer Network Decoder for Parcel Pickup Route Prediction
Novel attention mechanism and pointer network for parcel pickup route prediction in logistics optimization.
3/2/2026
Manifold Learning with Normalizing Flows: Towards Regularity, Expressivity and Iso-Riemannian Geometry
Theoretical research on manifold learning with normalizing flows for Riemannian geometry in high-dimensional data.
3/2/2026
Continuous Optimization for Feature Selection with Permutation-Invariant Embedding and Policy-Guided Search
Research on feature selection using permutation-invariant embeddings and policy-guided search with generative models.
3/2/2026
Multi-View Encoders for Performance Prediction in LLM-Based Agentic Workflows
Lightweight prediction model for LLM-based agentic workflow performance across agent configurations and prompting strategies.