2/17/2026
Large Language Model (LLM)-enabled Reinforcement Learning for Wireless Network Optimization
LLM-enabled reinforcement learning framework for optimizing wireless networks with distributed intelligence.
2/17/2026
Agentic AI for Commercial Insurance Underwriting with Adversarial Self-Critique
Agentic AI system for commercial insurance underwriting with adversarial self-critique and human-in-the-loop reliability.
2/17/2026
Scaling the Scaling Logic: Agentic Meta-Synthesis of Logic Reasoning
SSLogic: agentic meta-synthesis approach scaling logical reasoning tasks with verifiable training signals for RLVR.
2/17/2026
Boltz is a Strong Baseline for Atom-level Representation Learning
Boltz foundation model for atom-level representation learning in molecular property prediction tasks.
2/17/2026
Expected Moral Shortfall for Ethical Competence in Decision-making Models
Framework for instilling ethical competence into AI decision-making models with performance metrics.
2/17/2026
Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework
XAI-enhanced deep learning intrusion detection framework for cybersecurity with interpretability.
2/17/2026
TemporalBench: A Benchmark for Evaluating LLM-Based Agents on Contextual and Event-Informed Time Series Tasks
TemporalBench evaluates LLM-based agents on temporal reasoning with contextual and event-informed time series tasks.
2/17/2026
Explanatory Interactive Machine Learning for Bias Mitigation in Visual Gender Classification
Explanatory interactive learning to mitigate gender classification bias through user-guided model training.
2/17/2026
Benchmarking Anomaly Detection Across Heterogeneous Cloud Telemetry Datasets
Benchmarking deep learning models (GRU, TCN, Transformer, TSMixer) for anomaly detection across cloud telemetry.
2/17/2026
Fine-Tuning a Large Vision-Language Model for Artwork's Scoring and Critique
Fine-tuned vision-language model for automated artistic creativity scoring with explanatory feedback.
2/17/2026
DECKBench: Benchmarking Multi-Agent Frameworks for Academic Slide Generation and Editing
DECKBench evaluates multi-agent frameworks for academic slide generation and editing tasks.
2/17/2026
Detecting Jailbreak Attempts in Clinical Training LLMs Through Automated Linguistic Feature Extraction
Automated linguistic feature extraction for detecting jailbreak attempts in clinical training LLMs.
2/17/2026
Diagnostic Benchmarks for Invariant Learning Dynamics: Empirical Validation of the Eidos Architecture
PolyShapes-Ideal benchmark dataset tests topological invariance in vision models under affine transformations.
2/17/2026
Ask the Expert: Collaborative Inference for Vision Transformers with Near-Edge Accelerators
Collaborative inference framework routing vision transformer queries between edge and near-edge accelerators.
2/17/2026
Nonparametric Distribution Regression Re-calibration
Distribution regression re-calibration for ensuring predictive uncertainty reflects empirical accuracy.
2/17/2026
MoralityGym: A Benchmark for Evaluating Hierarchical Moral Alignment in Sequential Decision-Making Agents
MoralityGym: benchmark for evaluating hierarchical moral alignment in sequential decision-making agents.
2/17/2026
Unsafer in Many Turns: Benchmarking and Defending Multi-Turn Safety Risks in Tool-Using Agents
Multi-turn safety benchmark for tool-using LLM agents evaluating hierarchical risks in sequential interactions.
2/17/2026
Protect$^*$: Steerable Retrosynthesis through Neuro-Symbolic State Encoding
Protect*: neuro-symbolic method for steerable retrosynthesis controlling LLM chemical pathway generation.
2/17/2026
Language Model Memory and Memory Models for Language
Analysis of information storage in language model embeddings versus autoencoders for memory characterization.
2/17/2026
AsyncVLA: An Asynchronous VLA for Fast and Robust Navigation on the Edge
AsyncVLA: asynchronous framework for fast robotic navigation decoupling semantic reasoning from reactive control.
2/17/2026
Learning Gradient Flow: Using Equation Discovery to Accelerate Engineering Optimization
Data-driven equation discovery for modeling gradient descent dynamics to accelerate optimization.
2/17/2026
SpargeAttention2: Trainable Sparse Attention via Hybrid Top-k+Top-p Masking and Distillation Fine-Tuning
Trainable sparse attention via hybrid Top-k+Top-p masking for accelerating diffusion model inference.
2/17/2026
On Calibration of Large Language Models: From Response To Capability
LLM calibration from response-level to capability-level confidence estimation for reliable deployment.
2/17/2026
LiveNewsBench: Evaluating LLM Web Search Capabilities with Freshly Curated News
LiveNewsBench: benchmark for evaluating LLM web search and agentic capabilities with fresh news data.
2/17/2026
Differentiable Rule Induction from Raw Sequence Inputs
Differentiable inductive logic programming for rule learning from raw sequence data.
2/17/2026
Towards Sparse Video Understanding and Reasoning
ReViS: multi-round agent for video question answering with selective frame sampling and early stopping.
2/17/2026
DiffusionRollout: Uncertainty-Aware Rollout Planning in Long-Horizon PDE Solving
Uncertainty-aware rollout planning for diffusion models in long-horizon PDE solving.
2/17/2026
No Need to Train Your RDB Foundation Model
Foundation model using in-context learning for relational databases that avoids retraining across different prediction targets.
2/17/2026
Fine-tuned Vision Language Model for Localization of Parasitic Eggs in Microscopic Images
Fine-tunes vision-language model to localize parasitic eggs in microscopic images for soil-transmitted helminth diagnostic support.
2/17/2026
NeuroMambaLLM: Dynamic Graph Learning of fMRI Functional Connectivity in Autistic Brains Using Mamba and Language Model Reasoning
Combines Mamba state-space models with LLM reasoning to analyze dynamic fMRI functional connectivity in autistic brains.
2/17/2026
Attention in Constant Time: Vashista Sparse Attention for Long-Context Decoding with Exponential Guarantees
Sparse attention mechanism with constant-time complexity for long-context LLM decoding using projection onto convex hull of keys.
2/17/2026
A Unified Physics-Informed Neural Network for Modeling Coupled Electro- and Elastodynamic Wave Propagation Using Three-Stage Loss Optimization
Physics-Informed Neural Networks for modeling coupled electro-elastodynamic wave propagation with three-stage loss optimization.
2/17/2026
VAR-3D: View-aware Auto-Regressive Model for Text-to-3D Generation via a 3D Tokenizer
Auto-regressive transformer for text-to-3D generation using discrete 3D tokenizer to address information loss in encoding.
2/17/2026
Causally constrained reduced-order neural models of complex turbulent dynamical systems
Causal constraints framework using response theory and score matching for reduced-order neural emulators of turbulent dynamical systems.
2/17/2026
Evolving Multi-Channel Confidence-Aware Activation Functions for Missing Data with Channel Propagation
Proposes evolved activation functions that account for missing data indicators and confidence scores in neural networks.
2/17/2026
Enabling Option Learning in Sparse Rewards with Hindsight Experience Replay
Integrates Hindsight Experience Replay into Option-Critic hierarchical RL to improve multi-goal learning in sparse reward environments.
2/17/2026
Ensemble-Conditional Gaussian Processes (Ens-CGP): Representation, Geometry, and Inference
Formulation of Ensemble-Conditional Gaussian Processes connecting ensemble methods with conditional Gaussian inference and Kalman filtering.
2/17/2026
Ambient Physics: Training Neural PDE Solvers with Partial Observations
Framework for training neural PDE solvers on partial observations using diffusion models, avoiding need for complete observation datasets.
2/17/2026
Parameter-Efficient Fine-Tuning of DINOv2 for Large-Scale Font Classification
Fine-tunes DINOv2 Vision Transformer with LoRA for font classification, achieving 86% accuracy while training <1% of 87.2M parameters.
2/17/2026
Statistical Early Stopping for Reasoning Models
Statistical early stopping methods for LLM reasoning that monitor uncertainty signals to prevent overthinking during generation.
2/17/2026
A Theoretical Framework for LLM Fine-tuning Using Early Stopping for Non-random Initialization
Theoretical framework explaining why LLM fine-tuning requires only few epochs, combining early stopping theory with Neural Tangent Kernel analysis.
2/17/2026
Cognitive Chunking for Soft Prompts: Accelerating Compressor Learning via Block-wise Causal Masking
Method for compressing long LLM contexts into soft prompts via block-wise causal masking to reduce inference latency from quadratic attention costs.
2/17/2026
Named Entity Recognition for Payment Data Using NLP
Research on NER algorithms (CRF, BiLSTM-CRF, transformers) for extracting structured information from payment transaction data.
2/17/2026
Computable Bernstein Certificates for Cross-Fitted Clipped Covariance Estimation
Research on robust covariance estimation from heavy-tailed samples with outliers using clipped Euclidean norm approach and computable Bernstein certificates.
2/17/2026
Why Self-Training Helps and Hurts: Denoising vs. Signal Forgetting
Theoretical analysis of iterative self-training showing tradeoffs between noise denoising and signal forgetting in overparameterized linear regression.
2/17/2026
MC$^2$Mark: Distortion-Free Multi-Bit Watermarking for Long Messages
MC²Mark: distortion-free multi-bit watermarking framework for embedding long provenance identifiers in LLM-generated text.
2/17/2026
Choosing How to Remember: Adaptive Memory Structures for LLM Agents
Adaptive memory structures for LLM agents enabling context-dependent memory selection across heterogeneous interaction patterns.
2/17/2026
Geometry-Preserving Aggregation for Mixture-of-Experts Embedding Models
Geometry-preserving aggregation for mixture-of-experts embedding models accounting for hyperspherical manifold structure of expert outputs.
2/17/2026
GTS: Inference-Time Scaling of Latent Reasoning with a Learnable Gaussian Thought Sampler
GTS: learnable Gaussian thought sampler for efficient inference-time scaling in latent reasoning models with structured exploration.
2/17/2026
GUI-GENESIS: Automated Synthesis of Efficient Environments with Verifiable Rewards for GUI Agent Post-Training
GUI-GENESIS: framework for automated synthesis of efficient GUI training environments with verifiable rewards for agent post-training.