4/17/2026
From Memorization to Creativity: LLM as a Designer of Novel Neural Architectures
NNGPT framework uses LLMs for neural architecture synthesis through iterative supervised fine-tuning cycles generating validated PyTorch networks.
4/17/2026
ORBIT: On-policy Exploration-Exploitation for Controllable Multi-Budget Reasoning
ORBIT system for controlling reasoning budget in Large Reasoning Models via on-policy exploration-exploitation to reduce computational cost.
4/17/2026
Fundamental Limitations of Favorable Privacy-Utility Guarantees for DP-SGD
Theoretical analysis of differential privacy limitations in DP-SGD using f-differential privacy framework with shuffled sampling.
4/17/2026
Threshold Differential Attention for Sink-Free, Ultra-Sparse, and Non-Dispersive Language Modeling
Threshold Differential Attention mechanism for long-context language modeling, addressing attention sink and sparsity issues without projection overhead.
4/17/2026
LLMOrbit: A Circular Taxonomy of Large Language Models -From Scaling Walls to Agentic AI Systems
Comprehensive circular taxonomy surveying 50+ LLMs from 2019-2025 across 15 organizations, documenting architectural innovations and scaling properties.
4/17/2026
Learning temporal embeddings from electronic health records of chronic kidney disease patients
Study of temporal embedding models for electronic health records of chronic kidney disease patients, balancing predictive performance with clinical interpretability.
4/17/2026
Rethinking LLM-Driven Heuristic Design: Generating Efficient and Specialized Solvers via Dynamics-Aware Optimization
Framework for LLM-driven automated heuristic generation for combinatorial optimization with dynamics-aware evaluation beyond endpoint metrics.
4/17/2026
Continuous-time reinforcement learning: ellipticity enables model-free value function approximation
Research on model-free reinforcement learning for continuous-time processes with function approximation using ellipticity properties and Hilbert-space methods.
4/17/2026
MedVerse: Efficient and Reliable Medical Reasoning via DAG-Structured Parallel Execution
MedVerse framework enables parallel reasoning in LLMs for medical diagnosis using DAG-structured execution instead of sequential autoregressive decoding.
4/17/2026
Quantitative Approximation Rates for Group Equivariant Learning
arXiv paper on approximation rates for group equivariant neural networks. Theoretical ML research.
4/17/2026
OptEMA: Adaptive Exponential Moving Average for Stochastic Optimization with Zero-Noise Optimality
Adaptive optimizer using exponential moving average with theoretical guarantees for zero-noise convergence without restrictive boundedness conditions.
4/17/2026
AgentOpt v0.1 Technical Report: Client-Side Optimization for LLM-Based Agent
Client-side optimization framework for LLM-based agents that compose local tools, remote APIs, and multiple models efficiently.
4/17/2026
SAGE: Sign-Adaptive Gradient for Memory-Efficient LLM Optimization
Memory-efficient optimizer for LLM training using sign-adaptive gradient updates to reduce optimizer state overhead.
4/17/2026
Deliberative Alignment is Deep, but Uncertainty Remains: Inference time safety improvement in reasoning via attribution of unsafe behavior to base model
Studies deliberative alignment approach for improving LLM safety at inference time through reasoning model distillation and behavior attribution.
4/17/2026
Not All Forgetting Is Equal: Architecture-Dependent Retention Dynamics in Fine-Tuned Image Classifiers
Studies which samples are forgotten during fine-tuning of image classifiers and whether forgetting patterns depend on architecture.
4/17/2026
TempusBench: An Evaluation Framework for Time-Series Forecasting
Comprehensive evaluation framework for assessing time-series foundation models with benchmarks and community standards.
4/17/2026
Drowsiness-Aware Adaptive Autonomous Braking System based on Deep Reinforcement Learning for Enhanced Road Safety
Deep reinforcement learning system for autonomous braking that adapts to driver drowsiness using physiological state detection.
4/17/2026
Improving Language Models with Intentional Analysis
Proposes intentional analysis framework to improve language model reasoning by explicitly understanding user intent behind questions.
4/17/2026
Towards Bridging the Reward-Generation Gap in Direct Alignment Algorithms
Identifies reward-generation gap in Direct Alignment Algorithms like DPO and SimPO for LLM alignment, proposes methods to bridge the discrepancy.
4/17/2026
Measuring multi-calibration
Proposes scalar metrics for measuring multi-calibration of probabilistic predictions across multiple subpopulations.
4/17/2026
Random Matrix Theory for Deep Learning: Beyond Eigenvalues of Linear Models
Theoretical analysis extending random matrix theory to understand behavior of overparameterized deep neural networks in high-dimensional settings.
4/17/2026
KnowRL: Exploring Knowledgeable Reinforcement Learning for Factuality
KnowRL reinforcement learning approach to reduce hallucination in LLMs by providing factual supervision during reasoning process.
4/17/2026
Constrained Decoding for Safe Robot Navigation Foundation Models
Constrained decoding approach for ensuring safe navigation in robotic foundation models with explicit behavioral constraints.
4/17/2026
Multi-Modal Manipulation via Multi-Modal Policy Consensus
Multi-modal policy consensus approach factorizing robotic manipulation policies into modality-specific diffusion models for flexible integration.
4/17/2026
Flow with the Force Field: Learning 3D Compliant Flow Matching Policies from Force and Demonstration-Guided Simulation Data
Flow matching policies for contact-rich robotic manipulation tasks using force and demonstration-guided simulation data.
4/17/2026
The Specification Trap: Why Static Value Alignment Alone Is Insufficient for Robust Alignment
Philosophical analysis arguing static value alignment insufficient for robust AI alignment under capability scaling and distributional shift.
4/17/2026
Model-Free Assessment of Simulator Fidelity via Quantile Curves
Model-free methods for assessing simulator fidelity and quantifying sim-to-real gaps in generative AI models.
4/17/2026
Adaptive Layer Selection for Layer-Wise Token Pruning in LLM Inference
Adaptive layer selection technique for layer-wise token pruning to reduce KV cache in LLM inference with improved efficiency.
4/17/2026
De-Anonymization at Scale via Tournament-Style Attribution
DAS method for authorship de-anonymization at scale using tournament-style attribution with LLMs, analyzing privacy implications.
4/17/2026
Beyond Translation: Evaluating Mathematical Reasoning Capabilities of LLMs in Sinhala and Tamil
Evaluation of LLM mathematical reasoning capabilities in low-resource languages Sinhala and Tamil.
4/17/2026
Conformal Policy Control
Conformal policy control framework using safe reference policies as regulators for untested policies in high-stakes agent exploration.
4/17/2026
IROSA: Interactive Robot Skill Adaptation using Natural Language
IROSA framework combining foundation models with imitation learning for robot skill adaptation via natural language instructions.
4/17/2026
Large Language Model Post-Training: A Unified View of Off-Policy and On-Policy Learning
Survey unifying LLM post-training methods (SFT, preference optimization, RL, process supervision) through lens of off-policy and on-policy learning.
4/17/2026
Reproduction Beyond Benchmarks: ConstBERT and ColBERT-v2 Across Backends and Query Distributions
Reproducibility study of ColBERT-v2 and ConstBERT showing 86-97% performance drop on long narrative queries due to architectural limitations.
4/17/2026
Revisiting Compositionality in Dual-Encoder Vision-Language Models: The Role of Inference
Research on CLIP and dual-encoder vision-language models showing compositional limitations stem from inference protocol, not representations.
4/17/2026
Functional Emotions or Situational Contexts? A Discriminating Test from the Mythos Preview System Card
Research using SAE features and emotion vectors to study Claude Mythos Preview system behavior during misaligned responses.
4/17/2026
From Feelings to Metrics: Understanding and Formalizing How Users Vibe-Test LLMs
Research formalizing user 'vibe-testing' practices for evaluating LLMs, moving from informal experience-based evaluation to structured methodology for reproducibility.
4/17/2026
NuHF Claw: A Risk Constrained Cognitive Agent Framework for Human Centered Procedure Support in Digital Nuclear Control Rooms
Research paper proposing NuHF Claw cognitive agent framework using LLMs for safety-critical decision support in nuclear control rooms.
4/17/2026
Simulating Human Cognition: Heartbeat-Driven Autonomous Thinking Activity Scheduling for LLM-based AI systems
Heartbeat-driven autonomous thinking framework for LLM agents enabling proactive scheduling and continuous reflection instead of reactive control flows.
4/17/2026
Fun-TSG: A Function-Driven Multivariate Time Series Generator with Variable-Level Anomaly Labeling
Synthetic multivariate time series generator with fine-grained anomaly annotations and variable-level dependencies for benchmarking detection methods.
4/17/2026
Interpretable and Explainable Surrogate Modeling for Simulations: A State-of-the-Art Survey and Perspectives on Explainable AI for Decision-Making
Survey of interpretable surrogate modeling for complex system simulations, covering explainable AI techniques for decision-making and black-box model transparency.
4/17/2026
GFT: From Imitation to Reward Fine-Tuning with Unbiased Group Advantages and Dynamic Coefficient Rectification
Training dynamics analysis unifying supervised fine-tuning and reinforcement learning for LLMs via reward perspective, with group advantage optimization and coefficient rectification.
4/17/2026
Seeing Through Experts Eyes A Foundational Vision Language Model Trained on Radiologists Gaze and Reasoning
Vision-language model trained on radiologist gaze and reasoning patterns to improve chest X-ray interpretation by emulating expert diagnostic workflows.
4/17/2026
Mistake gating leads to energy and memory efficient continual learning
Biologically-inspired mistake-gated learning mechanism reducing synaptic plasticity costs, achieving energy and memory efficient continual learning in neural networks.
4/17/2026
Credo: Declarative Control of LLM Pipelines via Beliefs and Policies
Framework for declarative control of LLM agent pipelines using beliefs and policies, enabling transparent behavior adaptation and stateful decision-making.
4/17/2026
Equifinality in Mixture of Experts: Routing Topology Does Not Determine Language Modeling Quality
Geometric MoE architecture using cosine-similarity routing in low-dimensional space, achieving 80% fewer routing parameters while maintaining language modeling quality.
4/17/2026
Demonstration of Pneuma-Seeker: Agentic System for Reifying and Fulfilling Information Needs on Tabular Data
Agentic system for interactive data exploration that reifies vague information needs into explicit relational specifications with iterative refinement and provenance tracking.
4/17/2026
Geometric Routing Enables Causal Expert Control in Mixture of Experts
Demonstrates causal meaningfulness of individual experts in sparse MoE models via geometric routing, showing monosemantic expert behavior despite routing topology equivalence.
4/17/2026
AIBuildAI: An AI Agent for Automatically Building AI Models
AutoML system that automates AI model development including architecture design, feature engineering, training pipeline implementation, and empirical refinement.
4/17/2026
Improving Human Performance with Value-Aware Interventions: A Case Study in Chess
Framework for value-aware AI interventions in sequential decision-making, accounting for human execution limitations rather than assuming optimal follow-up actions.