recursive-language-models

Method for Long Context RLMs using verifiable Lambda Calculus

Automated generation of comprehensive Agents.md for LLMs, driven by the DSPy Recursive language model implementation.

Replace LLMs reasoning with code execution to solve real-world tasks.

The Research Playground for the RLMSs and Coding Agents

Implementation of Recursive Language Model paper from scratch

🫛👣 FAVA Trails — Git-native, curated memory for AI agents via MCP. Draft isolation, promotion gate, thought lifecycle hooks, memory curation protocols, supersession chains.

Agent swarms that recursively evolve themselves — recursive self-improvement as auditable topology. Build an agentic harness swarm as a directory tree. One Rust binary.

CLI agent that analyses meeting transcripts using Recursive Language Models (RLMs) to extract decisions, ownership, deadlines, and contradictions across documents.

AccInt - local-first MCP Work Model for coding agents that learns from real outcomes.

Running Recursive Language Models (RLM) on Azure

Recursive Language Models — process arbitrarily long prompts by offloading context into a REPL with symbolic recursion via sub-LLM calls. Based on Zhang, Kraska & Khattab (2025).

Zig runtime for Recursive Language Model workflows, inspired by alexzhang13/rlm

Recursive Language Models in ~400 lines of Python. Minimal implementation of Algorithm 1 from the RLM paper (Zhang, Kraska, Khattab — MIT CSAIL, 2026).

Minimal harness-agnostic recursive language model layer — one binary, Python + llm()

Machine-checked Lean 4 proofs for "Recursive Language Models Through the Admissibility-Dynamics Framework." Covers RLM sub-call architecture, three sufficient conditions for bounded-inconsistency deployment (safe abstention, bounded-decomposable predicates, runtime depth verification), training class closure, and the deployment-boundary synthesis.

Stateful agent on a Recursive Language Model engine — a local LLM drives an IPython REPL, queries sub-models from code, and consolidates a durable memory each episode.

Recursive Language Model - answers questions by navigating a document tree instead of reading it whole; bounded context per call, OpenAI & Gemini

A verifiers RLM environment for testing whether adaptive recursive search outperforms brittle manual RAG choreography on long synthetic corpora.

Recursive Language Models for pi: persistent Python REPL with rlm() sub-agent recursion, namespace snapshots and a continual harness (/refine) — as a single extension

Chain-of-density study of 'Recursive Language Models' (Zhang, Kraska & Khattab 2025, MIT CSAIL, arXiv:2512.24601) - five-tier note, locator-verified. The prompt-as-environment paradigm Trellis implements: REPL offloading, recursive sub-calls, 10M+ token inputs.