Claw Compactor: compress LLM tokens 54% with zero dependencies
Open source LLM token compression engine achieving 54% compression via 14-stage fusion pipeline with zero inference cost.
Open source LLM token compression engine achieving 54% compression via 14-stage fusion pipeline with zero inference cost.
Web tool for creating, optimizing and organizing prompts across multiple use cases with templates and search.
Benchmark results from First Proof initiative testing LLM capabilities for pure mathematics research contributions.
Pentagon plans secure environments for AI companies to train classified military models on sensitive defense data.
Interactive treemap visualization of AI exposure risk by occupation in Netherlands and Europe, based on Andrej Karpathy's US model.
Slice-Agent-Bench research on coding agents using slice-isolated execution instead of full repo context, testing minimal codebase projection efficiency.
Claude Code plugin orchestrating multiple LLMs (Codex, Gemini, Claude) with distinct roles and adversarial review to reduce model blind spots.
Community crowdsourced security scanning approach for AI agent skills, focusing on trust and safety validation.
Salience-gated memory system for Claude Code. Scores agent observations on 5 dimensions, consolidates patterns via dream cycles. Builds structured memory of tool usage.
Email infrastructure for AI agents. Provides dedicated inboxes, OTP polling endpoint, Steel Browser integration for signup automation.
Discussion: LLM cost optimization for AI agent fleet ($103K/week). Strategies include prompt caching, model routing, context truncation.
Remote Android instances streamed to browser, controllable by AI agents. No hardware/cables needed. Targets e-commerce, mobile testing automation.
ROMA orchestration tool running multiple coding agents simultaneously (Claude, Codex, Gemini, Copilot) with structured deliberation for coherent results.
Open-source macOS app for system-wide AI access via shortcuts and voice, with local model support.
Zero-configuration LLM inference. Auto-detects GPU, checks model fit, downloads correct format. Supports multiple model formats. Dashboard-based model selection.
Open-source Chrome extension for YouTube video interaction: transcript-first chat, summaries, timeline browsing, subtitle export.
Research on stability boundaries in iterative AI-assisted software development across Claude and GPT LLM families.
Thrum persistent messaging layer for AI agents across sessions and machines, with CLI and MCP server support for Claude Code agents.
ML project predicting Linux game compatibility (0.871 F1) using human-AI collaboration. Software engineer with minimal ML background used Claude to discover novel statistical techniques.
Open-source dependency manager for AI agents (apm). Standardizes agent configuration, skills, prompts across Claude, Copilot, Cursor. Similar to package.json for agents.
N0x browser-based LLM inference, autonomous agents, RAG, and Python execution with WebGPU and Pyodide, no backend or data sharing.
Development workflow framework for AI coding agents. Composable skills and instructions guide agent behavior from initial requirements gathering through code generation.
Analysis of longitudinal workplace studies showing productivity collapse when workers manage AI, contradicting optimistic coverage.
Meta's machine translation system extending to 1,600 languages using LLM approaches; advances beyond 200-language NLLB coverage.
Real-time terminal dashboard (llmtop) for monitoring LLM inference clusters supporting vLLM, SGLang, and Ollama with KV cache and latency metrics.
Terminal tool with local AI memory using Ollama. Save/recall commands, notes, URLs via natural language. Runs locally, no cloud.
Rust-accelerated RL framework using Polars pattern: Rust data plane + Python control plane via PyO3. 140x speedup with Rayon parallelism. Published on crates.io with 695 tests.
Vibe is a mobile app enabling remote code execution with Claude Code and Gemini CLI, with web preview and session management.
Personal setup combining Claude Code with specialized domain agents, parallel code review, and self-improving knowledge systems.
Dropbox optimized their relevance judge using DSPy for Dash, improving ranking and evaluation across multiple ML pipelines at scale.
TrustAgentAI is an open-source accountability layer adding cryptographic receipts and non-repudiation to MCP tool calls for AI agents.
Gas Town is Steve Yegge's agent orchestrator coordinating multiple AI coding agents simultaneously, hosted on Kilo Cloud infrastructure.
HYQNET is a neural-symbolic model that answers complex first-order logic queries on knowledge graphs by integrating interpretability with generalization.
NextMem proposes a latent factual memory framework for LLM-based agents to address limitations of existing textual and parametric memory approaches.
AIDABench: Comprehensive benchmark for AI data analytics and document understanding. Evaluates end-to-end task effectiveness in practical document processing scenarios.
Comprehension-Gated Agent Economy: Formal architecture linking AI agent economic permissions to verified comprehension. Robustness-first approach to agent authorization.
CraniMem: Neurocognitively-inspired gated and bounded multi-stage memory design for long-running LLM agents. Improves retention stability and content consolidation.
GSI Agent: Domain knowledge enhancement for LLMs in green stormwater infrastructure. Combines LLM with domain knowledge for inspection and maintenance guidance.
Cost-sensitive store routing for memory-augmented agents. Formulates selective memory retrieval as routing problem to reduce context tokens and improve efficiency.
DynaTrust: Defense mechanism against sleeper agents in multi-agent systems using dynamic trust graphs. Detects agents that hide malicious behavior until triggered.
Theoretical analysis of Query-Value mechanism in Transformers from linguistic perspective. Explains efficacy of MQA, GQA, and MLA architectures and trade-offs.
Atlas: Memory kernel that compiles task experience into agent instructions without fine-tuning or RAG. Improves agent memory utility via instruction-level compilation.
Quantum-Secure-By-Construction design paradigm for agentic AI systems. Addresses post-quantum cryptographic challenges in long-lived distributed agent deployments.
Latent Posterior Factors framework for aggregating multiple noisy evidence sources without manual feature engineering. Addresses uncertainty in real-world decision-making.
Theoretical characterization of Latent Posterior Factors for aggregating heterogeneous evidence in probabilistic prediction. Formal guarantees for multi-evidence reasoning.
Empirical study measuring LLM robustness to increasing context length on SQuAD and HotpotQA. Analyzes accuracy degradation with context size.
CUBE: Universal benchmark standard for AI agents built on MCP and Gym. Addresses fragmentation by allowing benchmarks to be wrapped once and used everywhere.
Prose2Policy: LLM pipeline translating natural-language access control policies into executable Rego code. End-to-end pipeline with test generation and validation.
Empirical study of GPT-4.1 behavior in gambling tasks under different persona prompts. Examines whether LLM risk behavior reflects principled patterns or prompt mimicry.
Regularized latent dynamics prediction as baseline for behavioral foundation models, examining how state feature choice affects task adaptability and reward function expressivity.