3/9/2026
Show HN: FretBench – I tested 14 LLMs on reading guitar tabs. Most failed
FretBench: 182-test-case benchmark for LLM guitar tab reading. Qwen models outperformed flagships; open source results via OpenRouter.
3/9/2026
Sumi – Open-source voice-to-text with local AI polishing
Voice-to-text tool with local LLM polishing. Rust-based Whisper/Qwen3-ASR pipeline optimized for Claude Code agent instruction input.
3/9/2026
Why AI Agents Need Email Guardrails
Essay on email safety guardrails for AI agents. Discusses send_email tool risks in LangChain, CrewAI, AutoGen frameworks.
3/9/2026
Kairos – real-time AI that cross-verifies news before answering (Python, 90KB)
Kairos cross-verifies live news data via RSS/DDG/NewsAPI before LLM answering to reduce hallucination on current events.
3/9/2026
Show HN: OpenCode Benchmark Dashboard
Benchmark dashboard for testing LLM models on opencode tasks, measuring latency and accuracy. Page has loading errors.
3/9/2026
Show HN: Supaguard – AI agent that writes and repairs Playwright tests
AI agent tool that autonomously writes and repairs Playwright browser tests using real sessions. Replaces manual test script management with semantic repair suggestions.
3/9/2026
A simple rule set that fixes Claude Code's worst habits
Rule system for Claude Code that adds structural discipline through phase tracking, decision logging, and language-specific best practices.
3/9/2026
Show HN: CiderStack – Run macOS CI runners on your own Mac mini cluster
CiderStack orchestrates macOS CI/CD infrastructure via GitHub Actions runners on Mac clusters. Single binary with web UI, SQLite backend.
3/9/2026
MARL: Runtime Middleware That Reduces LLM Hallucination Without Fine-Tuning
MARL middleware reduces LLM hallucination via multi-agent self-verification without fine-tuning or RAG. Model-agnostic runtime approach.
3/9/2026
Show HN: Botais (Battle of the AI's) – Competitive Snake Game for LLMs
Competitive multiplayer snake game where frontier LLMs compete autonomously. Demonstrates LLM agent behavior and decision-making capabilities.
3/9/2026
Causal Interpretation of Neural Network Computations with Contribution Decomposition
Introduces CODEC, sparse autoencoder method for causal interpretation of neural network computations via contribution decomposition.
3/9/2026
A recipe for scalable attention-based MLIPs: unlocking long-range accuracy with all-to-all node attention
Presents AllScAIP, attention-based machine learning interatomic potential using all-to-all node attention for long-range interactions.
3/9/2026
Information-Theoretic Privacy Control for Sequential Multi-Agent LLM Systems
Studies privacy preservation in sequential multi-agent LLM systems through information-theoretic controls against inference attacks.
3/9/2026
RoboLayout: Differentiable 3D Scene Generation for Embodied Agents
Introduces RoboLayout for generating differentiable 3D scene layouts from language instructions feasible for embodied agent interaction.
3/9/2026
Attention Meets Reachability: Structural Equivalence and Efficiency in Grammar-Constrained LLM Decoding
Analyzes grammar-constrained LLM decoding as coupling between autoregressive distribution and reachability oracle over context-free grammars.
3/9/2026
Prediction-Powered Conditional Inference
Develops prediction-powered conditional inference method combining localization and prediction-based variance reduction for scarce labeled data.
3/9/2026
RACAS: Controlling Diverse Robots With a Single Agentic System
Presents RACAS, an agentic system for controlling diverse robotic platforms with unified API and autonomous behavior pipeline.
3/9/2026
Making Reconstruction FID Predictive of Diffusion Generation FID
Introduces interpolated FID metric to improve correlation between VAE reconstruction and diffusion model generation quality.
3/9/2026
When Rubrics Fail: Error Enumeration as Reward in Reference-Free RL Post-Training for Virtual Try-On
Proposes error enumeration as reward signal for RL post-training in reference-free settings without ideal answer references.
3/9/2026
Parallelization Strategies for Dense LLM Deployment: Navigating Through Application-Specific Tradeoffs and Bottlenecks
Comprehensive analysis of parallelization strategies for dense LLM deployment, evaluating tradeoffs between tensor/pipeline/sequence parallelism.
3/9/2026
Knowing without Acting: The Disentangled Geometry of Safety Mechanisms in Large Language Models
Mechanistic analysis of LLM safety mechanisms revealing decoupling between harmfulness recognition and refusal via disentangled geometry.
3/9/2026
ReflexiCoder: Teaching Large Language Models to Self-Reflect on Generated Code and Self-Correct It via Reinforcement Learning
LLMs trained via RL to self-reflect and correct generated code without external oracles, improving complex algorithmic task performance.
3/9/2026
ROSE: Reordered SparseGPT for More Accurate One-Shot Large Language Models Pruning
Improved one-shot LLM pruning using optimal weight reordering instead of predefined order, advancing SparseGPT methodology.
3/9/2026
Addressing the Ecological Fallacy in Larger LMs with Human Context
Addresses ecological fallacy in language models by incorporating author context through specialized LM pretraining tasks.
3/9/2026
Implicit Style Conditioning: A Structured Style-Rewrite Framework for Low-Resource Character Modeling
Framework for fine-tuning small language models with stylized personas using structured style-rewriting to improve character consistency.
3/9/2026
Who We Are, Where We Are: Mental Health at the Intersection of Person, Situation, and Large Language Models
Interpretable models using LLMs to predict mental health and well-being from longitudinal social media data by integrating psychological traits.
3/9/2026
TADPO: Reinforcement Learning Goes Off-road
Reinforcement learning approach for off-road autonomous driving handling unmapped terrain, variable dynamics, and long-horizon planning.
3/9/2026
Diffusion Language Models Are Natively Length-Aware
Diffusion Language Models adapt generation length dynamically, reducing computational waste on short responses in reasoning tasks.
3/9/2026
Efficient Vector Search in the Wild: One Model for Multi-K Queries
Method for efficient vector search that generalizes across multiple K values in top-K retrieval without retraining, improving serving performance.
3/9/2026
Learning Where the Physics Is: Probabilistic Adaptive Sampling for Stiff PDEs
Adaptive sampling method using Gaussian Mixture Models to improve Physics-Informed Neural Networks training on stiff PDEs.
3/9/2026
SAHOO: Safeguarded Alignment for High-Order Optimization Objectives in Recursive Self-Improvement
Framework for monitoring and preventing alignment drift in recursive self-improvement systems using multi-signal detection and constraint preservation.
3/9/2026
MoEless: Efficient MoE LLM Serving via Serverless Computing
Serverless deployment system for efficient serving of Mixture-of-Experts LLMs by optimizing sparse activation patterns.
3/9/2026
Dynamic Chunking Diffusion Transformer
Diffusion Transformer variant with dynamic token chunking that adapts compute allocation based on image content detail and denoising stages.
3/9/2026
Kinetic-based regularization: Learning spatial derivatives and PDE applications
Kinetic-based regularization extension for learning spatial derivatives from noisy data with provable accuracy for PDE applications.
3/9/2026
Talk Freely, Execute Strictly: Schema-Gated Agentic AI for Flexible and Reproducible Scientific Workflows
Framework enabling LLMs to execute scientific workflows with schema-gated constraints ensuring determinism, provenance, and governance.
3/9/2026
Efficient, Property-Aligned Fan-Out Retrieval via RL-Compiled Diffusion
RL-based method for retrieving diverse, property-aligned result sets using diffusion models for set-valued retrieval objectives.
3/9/2026
A Reference Architecture of Reinforcement Learning Frameworks
Reference architecture framework analyzing 18 RL implementations to establish common patterns and standardization for RL frameworks.
3/9/2026
CLoPA: Continual Low Parameter Adaptation of Interactive Segmentation for Medical Image Annotation
Continual learning strategy for online adaptation of interactive segmentation models in medical imaging with low-parameter updates.
3/9/2026
Certified and accurate computation of function space norms of deep neural networks
Method for computing certified bounds on function space norms of deep neural networks applied to PDE solutions.
3/9/2026
Semantics-Aware Caching for Concept Learning
Optimization technique using semantic-aware caching to improve instance retrieval efficiency in concept learning on knowledge bases.
3/9/2026
Boosting deep Reinforcement Learning using pretraining with Logical Options
Two-stage hybrid framework combining logical options with deep reinforcement learning to improve agent alignment and prevent over-exploitation of early reward signals.
3/9/2026
SCOPE: Scene-Contextualized Incremental Few-Shot 3D Segmentation
SCOPE incremental few-shot 3D point cloud segmentation addressing catastrophic forgetting by leveraging unlabeled background scenes in sparse supervision settings.
3/9/2026
BEVLM: Distilling Semantic Knowledge from LLMs into Bird's-Eye View Representations
BEVLM distills semantic knowledge from LLMs into bird's-eye view representations for autonomous driving with improved spatial consistency and reduced computation.
3/9/2026
Predictive Coding Networks and Inference Learning: Tutorial and Survey
Tutorial and survey on predictive coding networks based on neuroscientific framework viewing brain as hierarchical Bayesian inference model minimizing prediction errors.
3/9/2026
PACE: Marrying generalization in PArameter-efficient fine-tuning with Consistency rEgularization
PACE combines parameter-efficient fine-tuning with consistency regularization to improve generalization by reducing gradient norms during transformer adaptation to downstream tasks.
3/9/2026
FragFM: Hierarchical Framework for Efficient Molecule Generation via Fragment-Level Discrete Flow Matching
FragFM hierarchical framework using fragment-level discrete flow matching and coarse-to-fine autoencoders for efficient scalable molecular graph generation.
3/9/2026
Aligning Compound AI Systems via System-level DPO
System-level DPO method for aligning compound AI systems with multiple interacting components including LLMs, foundation models, and external tools to human preferences.
3/9/2026
CAPS: Context-Aware Priority Sampling for Enhanced Imitation Learning in Autonomous Driving
Context-Aware Priority Sampling using VQ-VAEs to improve data efficiency and handle imbalanced datasets in imitation learning for autonomous driving systems.
3/9/2026
From Tokenizer Bias to Backbone Capability: A Controlled Study of LLMs for Time Series Forecasting
Controlled study examining how LLM tokenizer bias and backbone capability affect time series forecasting performance using pre-trained language models as backbone.
3/9/2026
Federated Learning: A Survey on Privacy-Preserving Collaborative Intelligence
Federated Learning survey covering privacy-preserving distributed machine learning enabling multiple clients to collaboratively train models without centralizing sensitive data.