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Meta-Vector++ Autoresearch

Parallel exploration of ICV composition methods for zero-shot reasoning improvement, powered by claudini's autoresearch loop.

What This Is

An adaptation of claudini's autoresearch pipeline to explore 4 parallel research directions for improving in-context vector (ICV) composition:

Direction Run Code Core Idea
Phase Decomposition phase Decompose ICVs into execution/reflection/transition components
Layer-Aware Composition layer Different composition strategies for early/mid/late transformer layers
Uncertainty Gating adaptive Entropy-adaptive steering strength with norm preservation
Test-Time Compute ttc Diverse steering ensemble + majority vote / LatentSeek warm-start

Setup

git clone https://huggingface.co/kweCobi/metavector-autoresearch
cd metavector-autoresearch
chmod +x setup.sh launch_all.sh monitor.sh
./setup.sh

Prerequisites: Python 3.12+, uv, Claude Code CLI, tmux, GPU (β‰₯16GB for dev, β‰₯24GB for full eval).

Launch All Directions

cd claudini
./launch_all.sh      # launches 4 tmux sessions
./monitor.sh         # cross-direction leaderboard

Launch One Direction

cd claudini
claude
> /loop /metavector phase improve zero-shot reasoning on MATH-500 via phase-specific ICV decomposition

Research Context

Based on the Meta-Vector paper (ICLR 2026 submission) and 6 key concurrent papers:

  • SEAL (2504.07986): Reasoning phases form disjoint latent subspaces
  • Fractional Reasoning (2506.15882): Contrastive steering with norm preservation
  • LatentSeek (2505.13308): Test-time policy gradient in latent space
  • Steering Vector RL (2509.06608): Three-cluster layer structure for steering
  • DeepSeek-R1 (2501.12948): GRPO + rule-based rewards for reasoning

File Structure

metavector_claudini/
β”œβ”€β”€ setup.sh                          # One-time setup
β”œβ”€β”€ launch_all.sh                     # Launch 4 parallel tmux sessions
β”œβ”€β”€ monitor.sh                        # Cross-direction leaderboard
β”œβ”€β”€ CLAUDE.md                         # Developer guide for the agent
β”œβ”€β”€ skills/metavector/SKILL.md        # Claude Code autoresearch skill
β”œβ”€β”€ configs/
β”‚   β”œβ”€β”€ mv_math500_dev.yaml           # Fast dev (1.5B, 50 problems)
β”‚   β”œβ”€β”€ mv_math500.yaml               # Full eval (7B, 500 problems)
β”‚   β”œβ”€β”€ mv_gsm8k_dev.yaml             # GSM8K sanity check
β”‚   └── mv_aime.yaml                  # AIME 2024 hard eval
β”œβ”€β”€ metavector_base/                  # Shared evaluation code
β”‚   β”œβ”€β”€ steering_optimizer.py         # SteeringOptimizer ABC
β”‚   β”œβ”€β”€ source_bank.py               # ICV bank management
β”‚   β”œβ”€β”€ evaluator.py                  # Benchmark runner
β”‚   β”œβ”€β”€ baselines.py                  # Zero-shot, static ICV, holistic composition
β”‚   └── utils.py                      # Hidden states, phase classification, answer extraction
└── starter_methods/                  # v1 for each direction
    β”œβ”€β”€ mv_phase_v1/
    β”œβ”€β”€ mv_layer_v1/
    β”œβ”€β”€ mv_adaptive_v1/
    └── mv_ttc_v1/
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