We’ve just published a public demo Space for AERIS, a cognitive inference layer designed to enhance reasoning quality in large language models — without any fine-tuning.
AERIS Chatbox: AERIS Chatbox - a Hugging Face Space by AERIS-Framework
Compare outputs (Gemma-3-27B-it with vs. without AERIS): https://huggingface.co/spaces/AERIS-Framework/aeris-public-demo/file/compare.html
What is AERIS?
AERIS (Adaptive Emergent Relational Intelligence System) is a lightweight reasoning layer that modulates the inference process of LLMs in real time by injecting dialectical structures, ambiguity resolution cues, and conceptual scaffolding.
Unlike fine-tuning or prompt engineering, AERIS reconfigures the reasoning path of the model dynamically — with no modification of model weights, and no external memory.
This space is a direct interface to Gemma-3-27B-it accessed via OpenRouter, showing how conceptual tension and dialectical modulation can produce deeper, more adaptive reasoning patterns in open-ended queries.
Why it matters
We believe that evaluation benchmarks alone do not capture what reasoning feels like for humans. This public demo allows anyone to test AERIS on open-ended or ambiguous prompts, and compare them directly to the raw model baseline.
Constructive feedback is highly welcome.
Feel free to challenge the system — edge cases and criticism are part of the experiment.
For scientific details, refer to our recent publications on Zenodo:
- AERIS: A Minimalist Framework for Enhancing Emergent Reasoning in LLMs
DOI: 10.5281/zenodo.15206925 - Beyond Reference Similarity: Why Current Metrics Fail to Capture Dialectical Reasoning in LLMs
DOI: 10.5281/zenodo.15206984