4/16/2026
Learning Dynamics from Input-Output Data with Hamiltonian Gaussian Processes
Hamiltonian Gaussian Processes for learning physically consistent dynamics from input-output data without velocity information.
4/16/2026
Guided Transfer Learning for Discrete Diffusion Models
Transfer learning via classifier guidance for discrete diffusion models in small-data regimes, extending continuous diffusion techniques.
4/16/2026
SHARe-KAN: Post-Training Vector Quantization for Cache-Resident KAN Inference
Vector quantization technique for optimizing Kolmogorov-Arnold Network inference on edge devices with memory constraints.
4/16/2026
A Review of Diffusion-based Simulation-Based Inference: Foundations and Applications in Non-Ideal Data Scenarios
Review of diffusion models for simulation-based inference with intractable likelihoods, covering theoretical foundations and applications.
4/16/2026
FlexGuard: Continuous Risk Scoring for Strictness-Adaptive LLM Content Moderation
LLM content moderation system with continuous risk scoring that adapts to changing strictness requirements across platforms, replacing fixed binary classification.
4/16/2026
Graph In-Context Operator Networks for Generalizable Spatiotemporal Prediction
Systematic comparison of in-context operator learning versus single-operator learning for spatiotemporal prediction using neural networks.
4/16/2026
ReproMIA: A Comprehensive Analysis of Model Reprogramming for Proactive Membership Inference Attacks
Comprehensive analysis of model reprogramming techniques for membership inference attacks, evaluating privacy vulnerabilities in deep learning models.
4/16/2026
Restless Bandits with Individual Penalty Constraints: A New Near-Optimal Index Policy and How to Learn It
Near-optimal index policy for restless multi-armed bandits with individual penalty constraints for resource allocation in dynamic wireless networks.
4/16/2026
WOMBET: World Model-based Experience Transfer for Robust and Sample-efficient Reinforcement Learning
Framework for generating and leveraging prior data through world models for sample-efficient offline-to-online reinforcement learning in robotics.
4/16/2026
When Can You Poison Rewards? A Tight Characterization of Reward Poisoning in Linear MDPs
Characterizes necessary and sufficient conditions for reward poisoning attacks in linear MDPs, providing theoretical framework for attack feasibility.
4/16/2026
Robust Adversarial Policy Optimization Under Dynamics Uncertainty
Proposes dual formulation for robust reinforcement learning under dynamics uncertainty, addressing limitations of domain randomization and adversarial RL methods.
4/16/2026
A Faster Path to Continual Learning
C-Flat optimization for continual learning on task streams avoiding forgetting with reduced computational overhead compared to prior approaches.
4/16/2026
THEIA: Learning Complete Kleene Three-Valued Logic in a Pure-Neural Modular Architecture
THEIA: modular neural architecture learning complete Kleene three-valued logic end-to-end across mathematical domains with compositional generalization.
4/16/2026
Fast and principled equation discovery from chaos to climate
Bayesian-ARGOS: principled method for discovering equations governing complex systems from noisy observations using sparse regression.
4/16/2026
Rethinking On-Policy Distillation of Large Language Models: Phenomenology, Mechanism, and Recipe
Systematic investigation of on-policy distillation dynamics in LLM post-training, identifying conditions for success and failure mechanisms.
4/16/2026
Deep Learning Based Amharic Chatbot for FAQs in Universities
Chatbot using NLP and deep learning to answer FAQs in Amharic language for university students, addressing common administrative questions.
4/16/2026
Nonparametric Sparse Online Learning of the Koopman Operator
Sparse online learning algorithm for Koopman operator with stochastic approximation and convergence guarantees for nonlinear dynamical systems.
4/16/2026
Fast training of accurate physics-informed neural networks without gradient descent
Fast training method for physics-informed neural networks solving PDEs without gradient descent, addressing optimization and temporal causality.
4/16/2026
AudioX: A Unified Framework for Anything-to-Audio Generation
AudioX: unified multimodal framework for anything-to-audio generation integrating text, video, and audio signals for flexible audio synthesis.
4/16/2026
Fast and Simple Densest Subgraph with Predictions
Learning-augmented algorithms for densest subgraph problem using ML classifier predictions to achieve linear-time approximation.
4/16/2026
Flow-based Generative Modeling of Potential Outcomes and Counterfactuals
PO-Flow: continuous normalizing flow framework for causal inference modeling potential outcomes and counterfactuals from observational data.
4/16/2026
Visual Sparse Steering (VS2): Unsupervised Adaptation for Image Classification using Sparsity-Guided Steering Vectors
VS2 method for unsupervised adaptation of vision foundation models using sparse autoencoders for steering vectors without weight updates or labels.
4/16/2026
Geminet: Learning the Duality-based Iterative Process for Lightweight Traffic Engineering in Changing Topologies
Geminet: lightweight ML-based traffic engineering framework using duality-based iterative process that handles topology changes with scalability.
4/16/2026
Frozen Forecasting: A Unified Evaluation
Proposes unified evaluation framework for assessing forecasting capabilities of frozen vision models across diverse tasks and abstraction levels.
4/16/2026
Autonomous Multi-objective Alloy Design through Simulation-guided Optimization
AutoMAT framework combines simulation, ML, and experiments for autonomous alloy discovery across competing objectives with data-efficient workflow.
4/16/2026
RL-PLUS: Countering Capability Boundary Collapse of LLMs in Reinforcement Learning with Hybrid-policy Optimization
RL-PLUS method addresses capability boundary collapse in LLMs using reinforcement learning with hybrid-policy optimization to improve reasoning abilities beyond base model limits.
4/16/2026
Memp: Exploring Agent Procedural Memory
Memp framework endowing LLM agents with learnable, updatable procedural memory. Distills agent trajectories into fine-grained instructions and script-like abstractions.
4/16/2026
Language steering in latent space to mitigate unintended code-switching
Latent-space steering method to reduce code-switching in multilingual LLMs. Uses PCA on parallel translations to control language identity at inference time.
4/16/2026
Saber: An Efficient Sampling with Adaptive Acceleration and Backtracking Enhanced Remasking for Diffusion Language Model
Diffusion language models with adaptive acceleration for code generation. Proposes Saber to balance inference speed and output quality with sampling optimization.
4/16/2026
Hierarchical DLO Routing with Reinforcement Learning and In-Context Vision-language Models
RL and vision-language models for long-horizon deformable object routing tasks in robotic assembly. Addresses planning and skill execution for cable/rope manipulation.
4/16/2026
ZK-APEX: Zero-Knowledge Approximate Personalized Unlearning with Executable Proofs
ZK-APEX system enables verifiable personalized machine unlearning on edge devices using zero-knowledge proofs for compliance verification.
4/16/2026
TRIM: Hybrid Inference via Targeted Stepwise Routing in Multi-Step Reasoning Tasks
TRIM framework routes only critical reasoning steps to capable models in multi-step reasoning tasks, reducing cascading failures in LLM applications.
4/16/2026
LoRA-MME: Multi-Model Ensemble of LoRA-Tuned Encoders for Code Comment Classification
LoRA-MME ensemble architecture using parameter-efficient fine-tuning of transformer encoders for multi-label code comment classification.
4/16/2026
Spectral methods: crucial for machine learning, natural for quantum computers?
Argument for quantum computers being naturally suited for spectral machine learning methods that manipulate Fourier spectra.
4/16/2026
Evaluating the Formal Reasoning Capabilities of Large Language Models through Chomsky Hierarchy
Systematic evaluation of LLM formal reasoning capabilities using Chomsky hierarchy and computation theory benchmarks for automated software engineering.
4/16/2026
Hierarchical Reinforcement Learning with Augmented Step-Level Transitions for LLM Agents
STEP-HRL hierarchical reinforcement learning framework reduces computational cost of LLM agents by learning from single-step transitions instead of long histories.
4/16/2026
Reason in Chains, Learn in Trees: Self-Rectification and Grafting for Multi-turn Agent Policy Optimization
T-STAR framework applies tree-structured reinforcement learning to improve multi-turn LLM agent policy optimization by identifying critical reasoning steps.
4/16/2026
IatroBench: Pre-Registered Evidence of Iatrogenic Harm from AI Safety Measures
Pre-registered evidence showing AI safety measures can produce iatrogenic harm in medical LLM outputs depending on prompt phrasing.
4/16/2026
LangFlow: Continuous Diffusion Rivals Discrete in Language Modeling
LangFlow demonstrates continuous diffusion language models can match discrete counterparts by connecting embeddings and diffusion processes for language generation.
4/16/2026
Spatial Atlas: Compute-Grounded Reasoning for Spatial-Aware Research Agent Benchmarks
Spatial Atlas introduces compute-grounded reasoning for spatial-aware research agents, handling multimodal benchmarks through deterministic computation before LLM generation.
4/16/2026
The local LLM ecosystem doesn’t need Ollama
Essay arguing local LLM infrastructure doesn't require Ollama tooling.
4/16/2026
An Autonomous RL Agent Methodology for Dynamic Web UI Testing in a BDD Framework
Autonomous RL agent integrated with BDD framework for dynamic web UI testing, generating test scenarios aligned with business expectations.
4/16/2026
Interface of Capitulation: A Black-Box Audit of Instructed Dishonesty in LLMs
Black-box audit documenting systematic dishonesty in frontier LLMs (GPT-4o, Claude, DeepSeek-V3) designed for user satisfaction over truthfulness.
4/16/2026
Eternal November – new influx of users, and why it's better than the last one
Overview of free/open source software advocacy organization, its legal efforts, and community programs.
4/16/2026
Mesh LLM
Mesh LLM pools spare GPU capacity across machines and exposes results via OpenAI-compatible API for distributed model inference.
4/16/2026
Hacking MCP Servers in AI Systems – The Rug Pull: Tool Changes After Approval
Security analysis of MCP server vulnerabilities where tool definitions can change after user approval, enabling tool-based attacks.
4/16/2026
Speeding up GPU kernels by 38% with a multi-agent system
Multi-agent system autonomously optimized 235 CUDA kernels for NVIDIA Blackwell GPUs, achieving 38% speedup in 3 weeks.
4/16/2026
Show HN: Tokanban, an agent-first task management system
Tokanban is an agent-first task management system built to eliminate friction points when using AI coding agents, with minimal UI.
4/16/2026
Free open source AI Editor
KubeezCut: client-side video editor running entirely in-browser using WebGPU/WebCodecs, no server uploads or installation required.
4/16/2026
Query LLMs like a graph database [video]
Video demonstrating graph database-style querying interface for LLMs.