3/25/2026
Reinforcement-Guided Hyper-Heuristic Hyperparameter Optimization for Fair and Explainable Spiking Neural Network-Based Financial Fraud Detection
Spiking neural network framework with hyperparameter optimization for fraud detection.
3/25/2026
TopoMap: A Feature-based Semantic Discriminator of the Topographical Regions in the Test Input Space
Testing framework for deep learning systems using topographical feature discrimination.
3/25/2026
FTTE: Enabling Federated and Resource-Constrained Deep Edge Intelligence
Federated learning framework for training deep models on resource-constrained edge devices.
3/25/2026
Guided Star-Shaped Masked Diffusion
Novel sampling algorithm for masked diffusion models improving generation quality and efficiency.
3/25/2026
On-device Semantic Selection Made Low Latency and Memory Efficient with Monolithic Forwarding
Optimizes on-device semantic selection with cross-encoder rerankers for retrieval, agent memory, and recommendations via monolithic forwarding.
3/25/2026
GUIrilla: A Scalable Framework for Automated Desktop UI Exploration
Scalable framework for automated desktop UI exploration to generate training data for LLM-based GUI understanding and automation.
3/25/2026
Parameter-Free Clustering via Self-Supervised Consensus Maximization (Extended Version)
Parameter-free clustering framework using self-supervised consensus maximization without requiring hyperparameter tuning.
3/25/2026
Data-Efficient and Robust Trajectory Generation through Pathlet Dictionary Learning
Pathlet dictionary learning approach for robust and interpretable trajectory generation in privacy-preserving urban mobility applications.
3/25/2026
Latent Diffusion Inversion Requires Understanding the Latent Space
Studies model inversion attacks on latent diffusion models, showing non-uniform memorization patterns in latent space.
3/25/2026
DP-FedSOFIM: Differentially Private Federated Stochastic Optimization using Regularized Fisher Information Matrix
Proposes differentially private federated learning optimization using regularized Fisher information matrix for faster convergence under privacy constraints.
3/25/2026
Representational Homomorphism Predicts and Improves Compositional Generalization In Transformer Language Model
Introduces homomorphism error metric to measure representational inconsistencies and predict compositional generalization failures in transformers.
3/25/2026
How Understanding Forecast Uncertainty Resolves the Explainability Problem in Machine Learning Models
Analyzes forecast uncertainty in ML model explainability, arguing uncertainty at decision boundaries explains LIME/SHAP instability.
3/25/2026
FlyPrompt: Brain-Inspired Random-Expanded Routing with Temporal-Ensemble Experts for General Continual Learning
Brain-inspired routing method with temporal-ensemble experts for general continual learning from non-stationary data streams.
3/25/2026
T1: One-to-One Channel-Head Binding for Multivariate Time-Series Imputation
Proposes one-to-one channel-head binding method for imputing missing values in multivariate time series data.
3/25/2026
When Sensors Fail: Temporal Sequence Models for Robust PPO under Sensor Drift
Studies robustness of PPO reinforcement learning under sensor drift using temporal sequence models to handle partial observability.
3/25/2026
MJ1: Multimodal Judgment via Grounded Verification
arXiv paper MJ1: multimodal judge trained with RL enforcing visual grounding through structured verification chains and counterfactual consistency rewards.
3/25/2026
Rethinking Machine Unlearning: Models Designed to Forget via Key Deletion
arXiv paper proposing key deletion approach for machine unlearning designed at model development stage rather than post-hoc, addressing privacy regulations and data errors.
3/25/2026
PRISM: Demystifying Retention and Interaction in Mid-Training
arXiv paper PRISM: empirical study of mid-training design choices across 7 LLM base models showing consistent +15 to +40 point gains from 27B token sequences.
3/25/2026
Elastic Weight Consolidation Done Right for Continual Learning
arXiv paper systematically analyzing Elastic Weight Consolidation for continual learning, revealing suboptimal importance estimation and proposing improvements.
3/25/2026
MemReward: Graph-Based Experience Memory for LLM Reward Prediction with Limited Labels
arXiv paper presenting MemReward, graph-based experience memory framework reducing human labeling needs for LLM reward prediction in RL post-training.
3/25/2026
Global Convergence of Multiplicative Updates for the Matrix Mechanism: A Collaborative Proof with Gemini 3
arXiv paper analyzing fixed-point iterations for nuclear norm optimization in private machine learning, proved with Gemini 3 collaboration.
3/25/2026
FIPO: Eliciting Deep Reasoning with Future-KL Influenced Policy Optimization
arXiv paper presenting FIPO reinforcement learning algorithm for improving reasoning in LLMs through fine-grained credit assignment beyond outcome-based rewards.
3/25/2026
MKA: Memory-Keyed Attention for Efficient Long-Context Reasoning
arXiv paper proposing Memory-Keyed Attention (MKA) to reduce KV cache memory costs in long-context LLM inference without sacrificing representation quality.
3/25/2026
mSFT: Addressing Dataset Mixtures Overfitting Heterogeneously in Multi-task SFT
Algorithm for optimal multi-task dataset mixture selection in LLM supervised fine-tuning. Addresses heterogeneous learning dynamics and overfitting.
3/25/2026
Uncertainty Quantification for Distribution-to-Distribution Flow Matching in Scientific Imaging
Uncertainty quantification methods for distribution-to-distribution generative models in scientific imaging. Ensures trustworthy cell and medical image generation.
3/25/2026
CellFluxRL: Biologically-Constrained Virtual Cell Modeling via Reinforcement Learning
Reinforcement learning post-training for virtual cell models to enforce biological constraints. Improves generative model reliability for drug discovery.
3/25/2026
Arena: Efficiently Training Large Models via Dynamic Scheduling and Adaptive Parallelism Co-Design
Dynamic scheduling system for efficient large model training across GPU clusters. Addresses training efficiency and resource utilization.
3/25/2026
Table-LLM-Specialist: Language Model Specialists for Tables using Iterative Generator-Validator Fine-tuning
Self-trained fine-tuning paradigm for LLMs on table understanding tasks like NL-to-Code and data cleaning. Reduces need for expensive human labeling.
3/25/2026
Replay-Free Continual Low-Rank Adaptation with Dynamic Memory
Continual learning technique combining parameter-efficient fine-tuning with vision transformers to prevent catastrophic forgetting. Addresses sequential task adaptation.
3/25/2026
LatentQA: Teaching LLMs to Decode Activations Into Natural Language
Method for training LLMs to explain their own internal activations using natural language probes. Advances LLM interpretability research.
3/25/2026
EmbBERT: Attention Under 2 MB Memory
Transformer attention mechanism compressed to run in under 2MB memory for IoT and wearable devices. Enables NLP deployment on ultra-constrained hardware.
3/25/2026
Redefining non-IID Data in Federated Learning for Computer Vision Tasks: Migrating from Labels to Embeddings for Task-Specific Data Distributions
Study redefining non-IID data heterogeneity in federated learning by migrating from label to embedding-level task-specific distributions.
3/25/2026
Learning dynamically inspired bases for Koopman and transfer operator approximation
Learning dynamically-inspired bases for Koopman and transfer operator approximation in complex nonlinear dynamical systems.
3/25/2026
Flying Pigs, FaR and Beyond: Evaluating LLM Reasoning in Counterfactual Worlds
CounterLogic benchmark evaluating LLM reasoning in counterfactual scenarios where context contradicts parametric knowledge.
3/25/2026
Image Generation from Contextually-Contradictory Prompts
Method for text-to-image diffusion models to handle contextually contradictory prompts where concepts implicitly negate each other.
3/25/2026
CyberGym: Evaluating AI Agents' Real-World Cybersecurity Capabilities at Scale
Large-scale benchmark with 1,507 real-world vulnerabilities evaluating AI agents' dynamic cybersecurity capabilities at scale.
3/25/2026
Morphology-Aware Peptide Discovery via Masked Conditional Generative Modeling
Masked conditional generative model for peptide discovery that predicts aggregate morphology for biomedical material design.
3/25/2026
BuilderBench: The Building Blocks of Intelligent Agents
BuilderBench benchmark for evaluating intelligent agents' ability to learn through interaction and exploration beyond training data.
3/25/2026
Information Gain-based Policy Optimization: A Simple and Effective Approach for Multi-Turn Search Agents
Reinforcement learning approach using information gain-based rewards to optimize LLM agents for multi-turn search with tool use.
3/25/2026
Generative AI Meets 6G and Beyond: Diffusion Models for Semantic Communications
Application of diffusion models to semantic communications in 6G wireless systems for meaning-centric data transmission.
3/25/2026
MOON2.0: Dynamic Modality-balanced Multimodal Representation Learning for E-commerce Product Understanding
Multimodal model addressing modality imbalance and noise in e-commerce product understanding with dynamic balancing.
3/25/2026
Delay-Aware Diffusion Policy: Bridging the Observation-Execution Gap in Dynamic Tasks
Framework for incorporating inference delays into diffusion policy learning for robotic control in dynamic environments.
3/25/2026
Impact of Positional Encoding: Clean and Adversarial Rademacher Complexity for Transformers under In-Context Regression
Analysis of positional encoding impact on Transformer generalization and robustness in in-context regression, showing PE enlarges generalization gap.
3/25/2026
ASK: Adaptive Self-improving Knowledge Framework for Audio Text Retrieval
ASK framework addresses gradient locality bottleneck in audio-text retrieval by incorporating external knowledge injection in dual-encoder architectures.
3/25/2026
1S-DAug: One-Shot Data Augmentation for Robust Few-Shot Generalization
1S-DAug introduces one-shot generative data augmentation synthesizing diverse image variants from single examples for improved few-shot learning generalization.
3/25/2026
KDFlow: A User-Friendly and Efficient Knowledge Distillation Framework for Large Language Models
KDFlow is a knowledge distillation framework for compressing large language models using heterogeneous training backends for student and teacher models.
3/25/2026
A Survey of Reinforcement Learning For Economics
Survey introducing reinforcement learning methods to economists for solving high-dimensional dynamic programming problems in economic modeling.
3/25/2026
Catalogue Grounded Multimodal Attribution for Museum Video under Resource and Regulatory Constraints
Method automating metadata curation for museum audiovisual archives using multimodal grounding in existing collection databases.
3/25/2026
Foundation-Model Surrogates Enable Data-Efficient Active Learning for Materials Discovery
Research using foundation model surrogates with active learning for materials discovery, reducing experimental cycles needed for optimal material identification.
3/25/2026
NCCL EP: Towards a Unified Expert Parallel Communication API for NCCL
NCCL EP presents a unified expert parallel communication API built on NCCL for GPU-initiated RDMA operations in Mixture-of-Experts LLM architectures.