[ACL 2026 Oral] "LightReasoner: Can Small Language Models Teach Large Language Models Reasoning?"
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Updated
May 22, 2026 - Python
[ACL 2026 Oral] "LightReasoner: Can Small Language Models Teach Large Language Models Reasoning?"
The Context OS for Autonomous AI Agents. Distill terminal noise into pure semantic signal, stop agent hallucinations, and cut token costs by up to 90%.
Dev tools, optimized for agents. Structured, token-efficient MCP servers for git, test runners, npm, Docker, and more.
An agentic memory database that cuts session tokens by 82–99%. One portable SQLite file — your agent's memory, anywhere.
Token-efficient data serialization for LLM/AI. 50% fewer tokens than JSON, 93% better value/token. Rust, schema validation, LSP.
DoCoreAI is a next-gen open-source AI profiler that optimizes reasoning, creativity, precision and temperature in a single step—cutting token usage by 15-30% and lowering LLM API costs
Persistent memory for Claude Code — 3-5x longer sessions, 60-80% fewer wasted tokens. Branch-aware, self-healing, token-efficient.
Claude Code skills for developers who code like cats — never more effort than the problem requires.
One-Click Private AI Stack on your VPS. Deployed with a pre-built 50k-line Next.js Aircraft Carrier & Zero-Agent Design System. Shifting layout assembly to atomic MCP commands to eliminate file reads and drive AI token spend to absolute zero.
The web data layer for AI agents — fetch, search, crawl, extract, screenshot, and monitor the web with 50+ domain extractors and MCP.
The AI-native wire format for structured data. 100% comprehension on every frontier model. 71% fewer tokens than JSON. 33B+ lossless round-trips across 5 formats. Spec v3.1 Stable.
A curated list of strategies, tools, papers, and resources for reducing LLM token costs and improving efficiency in production.
Open-source platform for token-efficient AI agents. Self-host with docker compose up.
Coherent Workspace — the data plane for shared agent state
Navigate your way - manual steering, steered autonomy, or autonomously. Kompass keeps AI coding agents on course with token-efficient, composable workflows.
A Codex skill for token-efficient subagent delegation and lean handoffs.
MCP proxy: zero-code GCF adoption. Wraps any MCP server, converts JSON to GCF mid-flight. 53-71% fewer tokens. Works with any structured data.
Coding agents forget your repo. mcp-brain is the missing memory layer — repo-aware, team-aware, lifecycle-aware. 63% Hit@10, zero LLM cost. Works with any MCP client.
A lightweight Python protocol and tool for agent-oriented documentation
GCF Go implementation. 100% comprehension. 71% fewer tokens than JSON, 25% fewer than TOON. 200M round-trips verified. v1.2.0.
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