4/16/2026
The Elegant Laminar Flow of Moroccan Tea [video]
Dojo: declarative testing engine in Go acting as transparent proxy to assert, mock, or AI-evaluate application behavior via HTTP and database interception.
4/16/2026
I Let Claude Opus Write a Chrome Exploit
Claude Opus used to generate Chrome V8 exploit chains through iterative prompting. Demonstrates LLM capability for security vulnerability discovery with detailed exploitation workflow.
4/16/2026
Shouldn't we have an agent.lock file for AI coding agents?
Proposes agent.lock file concept for reproducible AI coding agent behavior. Discusses determinism and version control for agentic systems.
4/16/2026
DFlash: Block Diffusion for Flash Speculative Decoding
DFlash: block diffusion model for speculative decoding achieving 6× speedup over EAGLE-3. Parallel token drafting improves LLM inference efficiency.
4/16/2026
Teaching AI Agents to Speak Hardware
MCP server for improving AI agent knowledge of specialized hardware (Chimera GPNPU). Addresses hallucination problems in domain-specific contexts.
4/16/2026
Who Tried Hermes Agent?
AIPOCH: curated library of 420+ medical research skills for AI agents. Open source tool for domain-specific agent capabilities.
4/16/2026
Why Sal Khan's AI revolution hasn't happened yet, according to Sal Khan
Sal Khan discusses why AI revolution in education hasn't materialized yet, citing low student adoption of Khanmigo AI tutoring chatbot.
4/16/2026
Show HN: Centrality – Visualize your how Claude Code operates on your codebase
Centrality visualization tool for observing Claude Code agent operations on codebases, showing file graphs and token consumption.
4/16/2026
Git blame your Claude Code setup
Guide for version controlling Claude Code IDE setup using git for syncing across machines.
4/16/2026
Charts-of-Thought: Enhancing LLM Visualization Literacy (PDF, 2026)
Research paper on Charts-of-Thought method for enhancing LLM visualization literacy and understanding of data representations.
4/16/2026
Spatial Atlas: Compute-Grounded Reasoning for Spatial-Aware Research Agent Benchmarks
Spatial Atlas framework instantiating compute-grounded reasoning paradigm for spatial-aware research agents with A2A architecture.
4/16/2026
DocSeeker: Structured Visual Reasoning with Evidence Grounding for Long Document Understanding
DocSeeker multimodal LLM system for long document understanding with evidence grounding, addressing signal-to-noise and weak supervision challenges.
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
Safe-FedLLM: Delving into the Safety of Federated Large Language Models
Security analysis of federated learning for LLMs, investigating attack surfaces and defenses against malicious clients in open environments.
4/16/2026
GUIDE: Guided Updates for In-context Decision Evolution in LLM-Driven Spacecraft Operations
GUIDE framework for LLM-driven spacecraft operations using in-context learning to improve agent decisions across episodes without weight updates.
4/16/2026
CodeTracer: Towards Traceable Agent States
CodeTracer framework for debugging and tracing AI agent state transitions, error propagation, and tool orchestration in code agents.
4/16/2026
Adaptive Memory Crystallization for Autonomous AI Agent Learning in Dynamic Environments
Adaptive Memory Crystallization architecture enabling continual learning in autonomous AI agents without catastrophic forgetting.
4/16/2026
Design Conditions for Intra-Group Learning of Sequence-Level Rewards: Token Gradient Cancellation
Analysis of sequence-level reward learning in reinforcement learning for reasoning models, addressing gradient cancellation and learning efficiency.
4/16/2026
Generalization Guarantees on Data-Driven Tuning of Gradient Descent with Langevin Updates
Langevin Gradient Descent algorithm with generalization guarantees for hyperparameter tuning in convex regression via learning to learn.
4/16/2026
Automated co-design of high-performance thermodynamic cycles via graph-based hierarchical reinforcement learning
Graph-based hierarchical reinforcement learning for automated co-design of thermodynamic cycle parameters.
4/16/2026
Pareto-Optimal Offline Reinforcement Learning via Smooth Tchebysheff Scalarization
Pareto-optimal offline reinforcement learning via Tchebysheff scalarization for multi-objective LLM alignment and optimization.
4/16/2026
KV Packet: Recomputation-Free Context-Independent KV Caching for LLMs
KV Packet enables context-independent key-value caching for LLMs without recomputation, improving inference latency.
4/16/2026
Does Dimensionality Reduction via Random Projections Preserve Landscape Features?
Studies whether dimensionality reduction via random projections preserves landscape features for exploratory landscape analysis.
4/16/2026
Out of Context: Reliability in Multimodal Anomaly Detection Requires Contextual Inference
Context-dependent anomaly detection framework for multimodal data recognizing that anomalies depend on contextual factors.
4/16/2026
Bias-Corrected Adaptive Conformal Inference for Multi-Horizon Time Series Forecasting
Bias-corrected adaptive conformal inference for multi-horizon time series forecasting with distribution shift adaptation.
4/16/2026
Counterfactual Peptide Editing for Causal TCR--pMHC Binding Inference
Counterfactual invariant prediction framework prevents shortcut learning in TCR-pMHC binding neural prediction models.
4/16/2026
Binomial Gradient-Based Meta-Learning for Enhanced Meta-Gradient Estimation
Binomial gradient-based meta-learning approach to reduce computational overhead in gradient-based meta-learning.
4/16/2026
Enhancing Confidence Estimation in Telco LLMs via Twin-Pass CoT-Ensembling
Twin-pass chain-of-thought ensembling method to improve confidence estimation reliability in telecommunications LLMs.
4/16/2026
MOONSHOT : A Framework for Multi-Objective Pruning of Vision and Large Language Models
MOONSHOT framework for multi-objective one-shot pruning of vision and large language models without retraining.
4/16/2026
Beyond Uniform Sampling: Synergistic Active Learning and Input Denoising for Robust Neural Operators
Combines active learning and input denoising to improve robustness of neural operators against adversarial perturbations.
4/16/2026
Multi-Task LLM with LoRA Fine-Tuning for Automated Cancer Staging and Biomarker Extraction
Multi-task LLM framework with LoRA fine-tuning for automated cancer staging and biomarker extraction from pathology reports.
4/16/2026
Text-Attributed Knowledge Graph Enrichment with Large Language Models for Medical Concept Representation
Uses LLMs to enrich knowledge graphs for medical concept representation in EHR mining and clinical prediction tasks.
4/16/2026
Selecting Feature Interactions for Generalized Additive Models by Distilling Foundation Models
TabDistill method leverages tabular foundation models to identify feature interactions for generalized additive models on tabular data.
4/16/2026
When Less Latent Leads to Better Relay: Information-Preserving Compression for Latent Multi-Agent LLM Collaboration
Orthogonal Backfill compression for LLM multi-agent systems reducing KV cache relay costs while preserving communication context and information.
4/16/2026
BioTrain: Sub-MB, Sub-50mW On-Device Fine-Tuning for Edge-AI on Biosignals
BioTrain framework enabling sub-50mW on-device fine-tuning for MCU-based wearable edge AI on biosignals addressing domain shift and privacy.
4/16/2026
Diffusion Sequence Models for Generative In-Context Meta-Learning of Robot Dynamics
Diffusion sequence models and Transformer meta-models for in-context robot dynamics learning addressing distributional shifts and real-time constraints.
4/16/2026
Dataset-Level Metrics Attenuate Non-Determinism: A Fine-Grained Non-Determinism Evaluation in Diffusion Language Models
Fine-grained non-determinism evaluation in diffusion language models showing dataset-level metrics mask run-to-run variations and condition sensitivity.
4/16/2026
WIN-U: Woodbury-Informed Newton-Unlearning as a retain-free Machine Unlearning Framework
WIN-U: Woodbury-informed Newton method for machine unlearning in LLMs enabling 'right to be forgotten' without requiring retain set data.
4/16/2026
A KL Lens on Quantization: Fast, Forward-Only Sensitivity for Mixed-Precision SSM-Transformer Models
Forward-only KL-based sensitivity analysis for mixed-precision quantization of hybrid SSM-Transformer LLMs targeting edge device deployment.
4/16/2026
Chain of Uncertain Rewards with Large Language Models for Reinforcement Learning
Proposes Chain of Uncertain Rewards method for designing reward functions in RL using LLMs, addressing inefficiencies in manual reward design and capturing intermediate uncertainties.
4/16/2026
SFT-GRPO Data Overlap as a Post-Training Hyperparameter for Autoformalization
Research on SFT-GRPO data overlap as a post-training hyperparameter for Lean 4 autoformalization using Qwen3-8B, ablating overlap percentages (0%, 30%, 100%).
4/16/2026
Representation over Routing: Overcoming Surrogate Hacking in Multi-Timescale PPO
Analysis of multi-timescale PPO revealing surrogate hacking when fusing multi-scale signals, proposing representation-focused solutions.
4/16/2026
From Alignment to Prediction: A Study of Self-Supervised Learning and Predictive Representation Learning
Study of self-supervised learning and predictive representation learning comparing alignment and reconstruction approaches.
4/16/2026
C-voting: Confidence-Based Test-Time Voting without Explicit Energy Functions
Confidence-based test-time voting mechanism for latent recurrent neural networks enabling test-time scaling without explicit energy functions.
4/16/2026
Learning Inference Concurrency in DynamicGate MLP Structural and Mathematical Justification
DynamicGate MLP architecture permitting concurrent learning and inference by separating routing from representation parameters.
4/16/2026
Parameter-efficient Quantum Multi-task Learning
Parameter-efficient quantum multi-task learning with shared backbone and task-specific heads for quantum neural networks.
4/16/2026
Enhancing Reinforcement Learning for Radiology Report Generation with Evidence-aware Rewards and Self-correcting Preference Learning
RL approach for radiology report generation using evidence-aware rewards and self-correcting preference learning for clinical alignment.
4/16/2026
Reward Hacking in the Era of Large Models: Mechanisms, Emergent Misalignment, Challenges
Analyzes reward hacking vulnerabilities in RLHF and alignment approaches for LLMs, examining mechanisms and emergent misalignment issues.
4/16/2026
Golden Handcuffs make safer AI agents
Bayesian mitigation strategy for safer AI agents using expanded subjective reward range to prevent reward hacking via risk aversion.
4/16/2026
(How) Learning Rates Regulate Catastrophic Overtraining
Studies how learning rates regulate catastrophic overtraining in LLM fine-tuning through catastrophic forgetting lens.