4/3/2026
Show HN: Skyreels V4 – AI Video Generator with Native Audio Sync
Multimodal AI video generator with native audio synchronization using dual-stream Diffusion Transformer architecture.
4/3/2026
WTFM – I found Anthropic's pub fix for AI policy comp, then built it myself
Personal anecdote about AI system disabling wireless drivers during automated recovery in an RV, causing offline situation.
4/3/2026
Can servers use elicitation for HITL scenarios?
Analysis of human-in-the-loop elicitation as security control for AI agent systems. Discusses exploit chain interruption.
4/3/2026
The Silicon Mirror: Dynamic Behavioral Gating for Anti-Sycophancy in LLM Agents
Framework detecting sycophancy in LLM agents with dynamic behavioral gating for factual integrity. ArXiv research on agent behavior.
4/3/2026
PsychAgent: An Experience-Driven Lifelong Learning Agent for Self-Evolving Psychological Counselor
Experience-driven lifelong learning agent for psychological counseling with memory-augmented planning. AI agent research paper.
4/3/2026
Omni-SimpleMem: Autoresearch-Guided Discovery of Lifelong Multimodal Agent Memory
Auto-research guided system for discovering effective lifelong multimodal memory architectures for AI agents. ArXiv research paper.
4/3/2026
Therefore I am. I Think
Evidence that language reasoning models encode tool-calling decisions before chain-of-thought generation. Analysis of model decision-making timing.
4/3/2026
Learning to Play Blackjack: A Curriculum Learning Perspective
Framework using LLMs to generate curriculum for RL agents. Applied to Blackjack with progressive action introduction.
4/3/2026
Hybrid Energy-Based Models for Physical AI: Provably Stable Identification of Port-Hamiltonian Dynamics
Energy-based models framework for port-Hamiltonian system identification with provable stability guarantees. Physical AI application.
4/3/2026
Deep Networks Favor Simple Data
Analysis of OOD anomaly where deep networks assign higher density to simple out-of-distribution data than in-distribution test data.
4/3/2026
MOON3.0: Reasoning-aware Multimodal Representation Learning for E-commerce Product Understanding
MOON3.0 multimodal representation learning for e-commerce product understanding using reasoning-aware MLLMs to capture fine-grained attributes.
4/3/2026
Think, Act, Build: An Agentic Framework with Vision Language Models for Zero-Shot 3D Visual Grounding
Think, Act, Build agentic framework using vision language models for zero-shot 3D visual grounding without relying on preprocessed point clouds.
4/3/2026
UniMixer: A Unified Architecture for Scaling Laws in Recommendation Systems
UniMixer unified architecture examining scaling laws across attention, TokenMixer, and factorization-machine recommendation systems.
4/3/2026
Learning to Learn-at-Test-Time: Language Agents with Learnable Adaptation Policies
Test-time learning for language agents with learnable adaptation policies. Improves agent behavior through iterative refinement at inference.
4/3/2026
Dual Optimal: Make Your LLM Peer-like with Dignity
Dignified Peer framework countering sycophancy and evasiveness in aligned LLMs through anti-sycophancy and empathy.
4/3/2026
Do Phone-Use Agents Respect Your Privacy?
MyPhoneBench evaluation framework measuring privacy compliance in phone-use agents during mobile task completion.
4/3/2026
ORBIT: Scalable and Verifiable Data Generation for Search Agents on a Tight Budget
ORBIT generates 20K training queries for search agents integrating LMs with web search using scalable and verifiable methods.
4/3/2026
DR-LoRA: Dynamic Rank LoRA for Fine-Tuning Mixture-of-Experts Models
DR-LoRA assigns dynamic ranks to expert modules in MoE models for efficient parameter-specific fine-tuning of LLMs.
4/3/2026
Cognitive Friction: A Decision-Theoretic Framework for Bounded Deliberation in Tool-Using Agents
Triadic Cognitive Architecture for tool-using agents with principled bounds on information-acquisition costs and deliberation.
4/3/2026
BIOGEN: Evidence-Grounded Multi-Agent Reasoning Framework for Transcriptomic Interpretation in Antimicrobial Resistance
BIOGEN multi-agent reasoning framework using evidence-grounding for transcriptomic interpretation in antimicrobial resistance.
4/3/2026
TaCarla: A comprehensive benchmarking dataset for end-to-end autonomous driving
TaCarla comprehensive benchmarking dataset for end-to-end autonomous driving with perception and planning tasks.
4/3/2026
MemFactory: Unified Inference & Training Framework for Agent Memory
MemFactory unified framework for training and inference in memory-augmented LLMs using RL to optimize memory operations.
4/3/2026
Sven: Singular Value Descent as a Computationally Efficient Natural Gradient Method
Sven optimization algorithm exploiting natural loss decomposition using Moore-Penrose pseudoinverse for efficient neural network training.
4/3/2026
Forecasting Supply Chain Disruptions with Foresight Learning
Framework training LLMs to forecast supply chain disruptions using calibrated probabilistic forecasts from disruption outcomes.
4/3/2026
UQ-SHRED: uncertainty quantification of shallow recurrent decoder networks for sparse sensing via engression
UQ-SHRED adds uncertainty quantification to shallow recurrent decoder networks for sparse spatiotemporal reconstruction.
4/3/2026
An Online Machine Learning Multi-resolution Optimization Framework for Energy System Design Limit of Performance Analysis
Online machine learning framework for multi-resolution energy system design optimization and performance analysis.
4/3/2026
JetPrism: diagnosing convergence for generative simulation and inverse problems in nuclear physics
JetPrism diagnoses convergence issues in Conditional Flow Matching for physics simulations and inverse problems.
4/3/2026
Detecting Complex Money Laundering Patterns with Incremental and Distributed Graph Modeling
Distributed graph modeling approach for detecting money laundering transaction patterns at scale.
4/3/2026
Efficient and Principled Scientific Discovery through Bayesian Optimization: A Tutorial
Tutorial on Bayesian Optimization as a principled framework for automating scientific discovery using surrogate models.
4/3/2026
Model Merging via Data-Free Covariance Estimation
Principled layer-wise optimization approach for model merging via data-free covariance estimation without task-specific training.
4/3/2026
SECURE: Stable Early Collision Understanding via Robust Embeddings in Autonomous Driving
SECURE framework addressing robustness issues in deep learning models for autonomous driving collision prediction.
4/3/2026
Massively Parallel Exact Inference for Hawkes Processes
GPU-accelerated inference algorithm for multivariate Hawkes processes achieving O(N) complexity with parallelization.
4/3/2026
Malliavin Calculus for Counterfactual Gradient Estimation in Adaptive Inverse Reinforcement Learning
Novel Langevin-based algorithm for adaptive inverse reinforcement learning using Malliavin calculus for gradient estimation.
4/3/2026
PI-JEPA: Label-Free Surrogate Pretraining for Coupled Multiphysics Simulation via Operator-Split Latent Prediction
PI-JEPA: Physics-informed surrogate model for multiphysics simulation exploiting unlabeled parameter fields via latent prediction.
4/3/2026
Residuals-based Offline Reinforcement Learning
Residuals-based offline reinforcement learning approach for high-stakes applications with restrictive data coverage assumptions.
4/3/2026
Benchmark Problems and Benchmark Datasets for the evaluation of Machine and Deep Learning methods on Photoplethysmography signals: the D4 report from the QUMPHY project
Benchmark datasets and evaluation protocols for machine learning methods on photoplethysmography medical signals.
4/3/2026
Test-Time Scaling Makes Overtraining Compute-Optimal
Train-to-Test scaling laws optimizing model size, training tokens, and inference samples jointly for compute-optimal LLM deployment.
4/3/2026
When Reward Hacking Rebounds: Understanding and Mitigating It with Representation-Level Signals
Study of reward hacking in LLM RL showing reproducible failure patterns and mitigation strategies using representation-level signals.
4/3/2026
DISCO-TAB: A Hierarchical Reinforcement Learning Framework for Privacy-Preserving Synthesis of Complex Clinical Data
Hierarchical RL framework for privacy-preserving synthetic clinical data generation combining LLMs with structured learning.
4/3/2026
CuTeGen: An LLM-Based Agentic Framework for Generation and Optimization of High-Performance GPU Kernels using CuTe
CuTeGen: LLM-based agentic framework for automated generation and optimization of high-performance GPU kernels using CuTe abstraction.
4/3/2026
Matching Accuracy, Different Geometry: Evolution Strategies vs GRPO in LLM Post-Training
Comparative study of Evolution Strategies vs GRPO for LLM post-training showing ES achieves comparable accuracy with different parameter geometry.
4/3/2026
Beyond Logit Adjustment: A Residual Decomposition Framework for Long-Tailed Reranking
Residual decomposition framework for improving classifier performance on long-tailed datasets beyond standard logit adjustment.
4/3/2026
Learning ECG Image Representations via Dual Physiological-Aware Alignments
Self-supervised framework for learning clinical ECG image representations without access to raw signal recordings.
4/3/2026
ZEUS: Accelerating Diffusion Models with Only Second-Order Predictor
ZEUS: Training-free acceleration method for diffusion models using second-order predictors to reduce sampling steps.
4/3/2026
Care-Conditioned Neuromodulation for Autonomy-Preserving Supportive Dialogue Agents
Care-Conditioned Neuromodulation framework for LLM-based dialogue agents that balances helpfulness with user autonomy preservation.
4/3/2026
Optimizing EEG Graph Structure for Seizure Detection: An Information Bottleneck and Self-Supervised Learning Approach
EEG seizure detection method using graph neural networks with self-supervised learning and information bottleneck principles.
4/3/2026
Learning from the Right Rollouts: Data Attribution for PPO-based LLM Post-Training
Influence-Guided PPO framework for LLM post-training that filters noisy rollouts using data attribution to improve training efficiency.
4/3/2026
Training In-Context and In-Weights Mixtures Via Contrastive Context Sampling
Research on training LLMs to develop both in-context and in-weights learning capabilities simultaneously via contrastive context sampling.
4/3/2026
Pseudo-Quantized Actor-Critic Algorithm for Robustness to Noisy Temporal Difference Error
Novel reinforcement learning algorithm addressing noisy temporal difference errors in deep RL through pseudo-quantization methods.
4/3/2026
Expert-Choice Routing Enables Adaptive Computation in Diffusion Language Models
arXiv paper on expert-choice routing for diffusion language models. Deterministic load balancing improves throughput and convergence vs token-choice.