3/18/2026
Analyzing Error Sources in Global Feature Effect Estimation
arXiv: Analyzes error sources in global feature effect estimation (PD, ALE plots) for black-box model interpretation.
3/18/2026
Open Biomedical Knowledge Graphs at Scale: Construction, Federation, and AI Agent Access with Samyama Graph Database
arXiv: Open-source biomedical knowledge graphs (Pathways, Clinical Trials, Drug-Gene) with AI agent access via Samyama database.
3/18/2026
To See is Not to Master: Teaching LLMs to Use Private Libraries for Code Generation
arXiv: Addresses LLM limitations in private-library code generation; shows API documentation retrieval alone is insufficient.
3/18/2026
HindSight: Evaluating LLM-Generated Research Ideas via Future Impact
arXiv: HindSight framework evaluates LLM-generated research ideas by matching against future publications and citation impact.
3/18/2026
More Test-Time Compute Can Hurt: Overestimation Bias in LLM Beam Search
arXiv: Analyzes how wider beam search can hurt LLM output quality due to overestimation bias in noisy scoring.
3/18/2026
The PokeAgent Challenge: Competitive and Long-Context Learning at Scale
arXiv: PokeAgent benchmark for multi-agent AI decision-making with partial observability, game theory, and long-horizon planning in Pokemon RPG.
3/18/2026
Physics-Informed Neural Systems for the Simulation of EUV Electromagnetic Wave Diffraction from a Lithography Mask
arXiv: Physics-informed neural networks for simulating EUV electromagnetic wave diffraction in lithography. Domain-specific neural networks.
3/18/2026
Tokenization Tradeoffs in Structured EHR Foundation Models
arXiv: Analyzes tokenization design choices for foundation models trained on structured electronic health records.
3/18/2026
Alternating Reinforcement Learning with Contextual Rubric Rewards
Reinforcement learning framework extending RLHF with multi-dimensional contextual rubric rewards and alternating optimization.
3/18/2026
Steering Frozen LLMs: Adaptive Social Alignment via Online Prompt Routing
Inference-time steering mechanism for frozen LLMs using adaptive prompt routing to enable evolving safety alignment without retraining.
3/18/2026
How to Achieve Prototypical Birth and Death for OOD Detection?
Prototype-based OOD detection method with dynamic prototype count adaptation based on category complexity.
3/18/2026
A federated learning framework with knowledge graph and temporal transformer for early sepsis prediction in multi-center ICUs
Federated learning framework combining knowledge graphs and temporal transformers for early sepsis prediction across multi-center ICUs.
3/18/2026
Discovering the Hidden Role of Gini Index In Prompt-based Classification
Study of Gini Index role in detecting and debiasing class accuracy disparities in prompt-based classification tasks.
3/18/2026
Beyond Reward Suppression: Reshaping Steganographic Communication Protocols in MARL via Dynamic Representational Circuit Breaking
Defense mechanism against steganographic collusion in multi-agent RL using dynamic representational circuit breaking at optimization substrate.
3/18/2026
Attribution-Guided Model Rectification of Unreliable Neural Network Behaviors
Attribution-guided framework using rank-one model editing to rectify unreliable neural network behavior on non-robust features.
3/18/2026
Spectral Edge Dynamics of Training Trajectories: Signal--Noise Geometry Across Scales
Analysis of transformer training dynamics via spectral edge detection showing parameter updates concentrate in few coherent directions.
3/18/2026
Evidential Domain Adaptation for Remaining Useful Life Prediction with Incomplete Degradation
Domain adaptation method for remaining useful life prediction with incomplete degradation trajectories using evidential learning.
3/18/2026
Tackling Over-smoothing on Hypergraphs: A Ricci Flow-guided Neural Diffusion Approach
Hypergraph neural network approach using Ricci flow to address over-smoothing and improve message passing.
3/18/2026
Mastering the Minority: An Uncertainty-guided Multi-Expert Framework for Challenging-tailed Sequence Learning
Multi-expert framework with uncertainty guidance for imbalanced sequence learning and minority class detection.
3/18/2026
Embedding-Aware Feature Discovery: Bridging Latent Representations and Interpretable Features in Event Sequences
Method bridging learned embeddings and interpretable handcrafted features for temporal event sequences in financial systems.
3/18/2026
Meta-TTRL: A Metacognitive Framework for Self-Improving Test-Time Reinforcement Learning in Unified Multimodal Models
Metacognitive test-time reinforcement learning framework for unified multimodal models enabling knowledge accumulation across similar prompts.
3/18/2026
OMNIFLOW: A Physics-Grounded Multimodal Agent for Generalized Scientific Reasoning
Physics-grounded multimodal LLM agent combining language models with PDE solvers for scientific reasoning without domain-specific fine-tuning.
3/18/2026
Time-Aware Prior Fitted Networks for Zero-Shot Forecasting with Exogenous Variables
Zero-shot forecasting method for time series with exogenous variables using prior-fitted networks.
3/18/2026
Mask Is What DLLM Needs: A Masked Data Training Paradigm for Diffusion LLMs
Masked data training paradigm for discrete diffusion language models using information density-driven noise scheduling.
3/18/2026
Hypothesis Class Determines Explanation: Why Accurate Models Disagree on Feature Attribution
Empirical study showing prediction-equivalent ML models produce substantially different feature attributions across 24 datasets, challenging assumptions in explainable AI.
3/18/2026
When Stability Fails: Hidden Failure Modes Of LLMS in Data-Constrained Scientific Decision-Making
Evaluates LLM failure modes in scientific decision-making when stability doesn't guarantee agreement with statistical ground truth.
3/18/2026
Informationally Compressive Anonymization: Non-Degrading Sensitive Input Protection for Privacy-Preserving Supervised Machine Learning
Privacy-preserving machine learning technique using informational compression for anonymization without performance degradation.
3/18/2026
Evaluating Black-Box Vulnerabilities with Wasserstein-Constrained Data Perturbations
Applies optimal transport theory to evaluate ML model vulnerabilities through Wasserstein-constrained data perturbations.
3/18/2026
Counteractive RL: Rethinking Core Principles for Efficient and Scalable Deep Reinforcement Learning
Proposes counteractive reinforcement learning approach addressing computational complexity in high-dimensional MDPs.
3/18/2026
PhasorFlow: A Python Library for Unit Circle Based Computing
Python library for unit circle based computing using complex phasors and unitary wave interference gates.
3/18/2026
Game-Theory-Assisted Reinforcement Learning for Border Defense: Early Termination based on Analytical Solutions
Hybrid approach combining game theory and reinforcement learning for adversarial scenarios using analytical solutions for early termination.
3/18/2026
The Agentic Researcher: A Practical Guide to AI-Assisted Research in Mathematics and Machine Learning
Practical guide for using AI systems and agents in mathematics and machine learning research with discussion of responsible guardrails.
3/18/2026
Auto Researching, not hyperparameter tuning: Convergence Analysis of 10,000 Experiments
Analyzes 10,469 experiments from LLM agents performing architecture search vs hyperparameter tuning using ANOVA decomposition.
3/18/2026
Generative Inverse Design with Abstention via Diagonal Flow Matching
Introduces diagonal flow matching for inverse design problems with better stability than conditional flow matching.
3/18/2026
Discovery of interaction and diffusion kernels in particle-to-mean-field multi-agent systems
Data-driven framework learning interaction kernels in stochastic multi-agent systems via sparse regression on trajectory data.
3/18/2026
Data-Local Autonomous LLM-Guided Neural Architecture Search for Multiclass Multimodal Time-Series Classification
LLM-guided neural architecture search for time-series classification in privacy-constrained domains using data-local constraints.
3/18/2026
MobileLLM-Flash: Latency-Guided On-Device LLM Design for Industry Scale
Hardware-in-the-loop architecture search methodology for designing efficient on-device LLMs with real-time latency constraints for mobile deployment.
3/18/2026
GASP: Guided Asymmetric Self-Play For Coding LLMs
Proposes guided asymmetric self-play method for post-training coding LLMs with better problem selection to improve model capabilities.
3/18/2026
Deriving Hyperparameter Scaling Laws via Modern Optimization Theory
Derives hyperparameter scaling laws for modern optimizers enabling transfer across model sizes, batch sizes, and training horizons.
3/18/2026
W2T: LoRA Weights Already Know What They Can Do
Analyzes whether LoRA checkpoint weights encode task performance information readable without running the base model, enabling efficient adapter analysis.
3/18/2026
Collaborative Temporal Feature Generation via Critic-Free Reinforcement Learning for Cross-User Sensor-Based Activity Recognition
Reinforcement learning approach for temporal feature generation in cross-user activity recognition from wearable sensor data.
3/18/2026
MDM-Prime-v2: Binary Encoding and Index Shuffling Enable Compute-optimal Scaling of Diffusion Language Models
Masked diffusion model optimization using binary encoding and index shuffling for improved scaling of diffusion language models.
3/18/2026
Noisy Data is Destructive to Reinforcement Learning with Verifiable Rewards
Analysis showing noisy data significantly degrades reinforcement learning with verifiable rewards despite claims of robustness.
3/18/2026
HIPO: Instruction Hierarchy via Constrained Reinforcement Learning
Constrained reinforcement learning approach for hierarchical instruction following in LLMs with priority-ordered system prompts.
3/18/2026
DyJR: Preserving Diversity in Reinforcement Learning with Verifiable Rewards via Dynamic Jensen-Shannon Replay
Experience replay mechanism preserving diversity in on-policy reinforcement learning for LLM reasoning using Jensen-Shannon divergence.
3/18/2026
Execution-Grounded Credit Assignment for GRPO in Code Generation
Credit assignment method using execution traces to improve GRPO performance in code generation tasks with verifiable rewards.
3/18/2026
The Finetuner's Fallacy: When to Pretrain with Your Finetuning Data
Study of specialized pretraining strategy using domain data during pretraining to improve finetuning performance and reduce forgetting.
3/18/2026
Offline Exploration-Aware Fine-Tuning for Long-Chain Mathematical Reasoning
Fine-tuning approach for improving mathematical reasoning in LLMs by optimizing exploration-aware trajectories with verifiable rewards.
3/18/2026
Dual Consensus: Escaping from Spurious Majority in Unsupervised RLVR via Two-Stage Vote Mechanism
Dual consensus mechanism for improving reinforcement learning from verifiable rewards in LLMs, avoiding convergence to spurious answers.
3/18/2026
Decoding the Critique Mechanism in Large Reasoning Models
Study of how large reasoning models use backtracking and self-verification to detect and correct errors in complex logical reasoning tasks.