Update README.md

README.md

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 # EXOKERN
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 Force/torque-aware data and pretrained manipulation skills for contact-rich robotics.
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 EXOKERN publishes datasets, pretrained policies, and evaluation tooling for assembly-style tasks where contact dynamics matter. The current public catalog focuses on peg insertion as a reproducible baseline for learning with 6-axis wrench signals, domain randomization, and multi-seed evaluation.
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 ## Start Here
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 | Artifact | Link | Purpose |
 | --- | --- | --- |
 | Current dataset | [contactbench-forge-peginsert-v0.1.1](https://huggingface.co/datasets/EXOKERN/contactbench-forge-peginsert-v0.1.1) | Semantic-versioned domain-randomized reference dataset |
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 | Clean baseline dataset | [contactbench-forge-peginsert-v0](https://huggingface.co/datasets/EXOKERN/contactbench-forge-peginsert-v0) | Fixed-condition dataset for controlled F/T ablations |
 | Clean baseline model | [skill-forge-peginsert-v0](https://huggingface.co/EXOKERN/skill-forge-peginsert-v0) | Baseline skill release with paired `full_ft` and `no_ft` checkpoints |
 | Evaluation tool | [exokern-eval](https://github.com/Exokern/exokern_eval) | Benchmark CLI for reproducing EXOKERN-style rollouts |
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 ## Current Catalog
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 | Category | Repo | What it contains | Status |
 | --- | --- | --- | --- |
 | Model | [skill-forge-peginsert-v0](https://huggingface.co/EXOKERN/skill-forge-peginsert-v0) | Fixed-condition baseline skill pair for clean force/torque ablations | Live |
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 | Dataset | [contactbench-forge-peginsert-v0](https://huggingface.co/datasets/EXOKERN/contactbench-forge-peginsert-v0) | 2,221 episodes / 330,929 frames under mostly fixed conditions | Live |
 | Dataset | [contactbench-forge-peginsert-v0.1](https://huggingface.co/datasets/EXOKERN/contactbench-forge-peginsert-v0.1) | First domain-randomized release, kept for continuity | Legacy |
 | Dataset | [contactbench-forge-peginsert-v0.1.1](https://huggingface.co/datasets/EXOKERN/contactbench-forge-peginsert-v0.1.1) | 5,000 episodes / 745,000 frames, semantic-versioned DR reference release | Live |
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 All public datasets use LeRobot v3.0-compatible parquet exports and include a 6-axis wrench signal at every timestep. Dataset downloads are gated on the Hub.
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 ## What Is Validated Today
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 - On the fixed-condition v0 benchmark, `full_ft` and `no_ft` both reached 100% success across 3 seeds x 100 episodes, while force/torque input reduced average contact force from 5.2 N to 3.2 N.
 - On the domain-randomized v0.1.1 benchmark, both variants again reached 100% success across 600 total rollouts. In this setup, domain randomization largely closed the force gap, so the force/torque benefit is inconclusive for this specific task and tolerance regime.
 - The cards state both the positive result and the boundary condition where a force/torque benefit does not appear. That is deliberate.
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 ## What Makes The Catalog Useful
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 - Every release is paired with an explicit dataset lineage, not a detached checkpoint drop.
 - Baseline and ablation checkpoints are published together when possible.
 - Evaluation claims are tied to concrete seeds, episode counts, and repository artifacts.
 - Cards state simulation-only limitations directly instead of implying production readiness.
 - The catalog is organized around contact-rich robotics rather than generic manipulation marketing.
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 ## Reference Papers Behind The Stack
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 - FORGE: [Force-Guided Exploration for Robust Contact-Rich Manipulation under Uncertainty](https://arxiv.org/abs/2408.04587)
 - Factory: [Factory: Fast Contact for Robotic Assembly](https://arxiv.org/abs/2205.03532)
 - IndustReal: [Transferring Contact-Rich Assembly Tasks from Simulation to Reality](https://arxiv.org/abs/2305.17110)
 - Diffusion Policy: [Visuomotor Policy Learning via Action Diffusion](https://arxiv.org/abs/2303.04137)
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 ## Near-Term Priorities
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 - Harder contact tasks with tighter tolerances, threaded insertion, and snap-fit behavior
 - Richer observations, including point clouds combined with wrench signals
 - Multi-robot evaluation beyond a single arm configuration
 - Real-world validation and safety-bridged deployment studies
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 ## External Links
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 - Website: [exokern.com](https://exokern.com)
 - GitHub: [github.com/Exokern](https://github.com/Exokern)
+- X: [x.com/ludwim_i](https://x.com/ludwim_i)
 - Contact: [exokern@proton.me](mailto:exokern@proton.me)
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-EXOKERN is building a catalog for force-aware manipulation research: documented datasets, reproducible baselines, and claims that stay attached to the evidence.
+EXOKERN is building a catalog for force-aware manipulation research: documented datasets, reproducible baselines, and claims that stay attached to the evidence.