New Research Release: AetherMind_SRL — Self-Reflective Learning for Robust Natural Language Inference (NLI)
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New Research Release: AetherMind_SRL — Self-Reflective Learning for Robust Natural Language Inference (NLI)
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By: Sameer S. Najm
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By: Sameer S. Najm
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After more than a year of continuous work, experimentation, and refinement, I am proud to officially publish AetherMind_SRL, a self-improving Transformer model trained using Self-Reflective Learning (SRL) — a technique that enables the model to learn from its own mistakes.
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After more than a year of continuous work, experimentation, and refinement, I am proud to officially publish AetherMind_SRL, a self-improving Transformer model trained using Self-Reflective Learning (SRL) — a technique that enables the model to learn from its own mistakes.
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This research integrates:
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This research integrates:
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🔹 Knowledge Distillation from DeBERTa-v3-base
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🔹 Knowledge Distillation from DeBERTa-v3-base
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🔹 Self-Reflective Learning loops
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🔹 Self-Reflective Learning loops
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🔹 Adversarial ANLI training
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🔹 Adversarial ANLI training
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🔹 Clinical Alzheimer’s reasoning (ADNI)
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🔹 Clinical Alzheimer’s reasoning (ADNI)
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🔹 SMART Error Buffers for hard-example mining
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🔹 SMART Error Buffers for hard-example mining
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  What makes it unique?
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  What makes it unique?
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AetherMind_SRL continuously improves through structured error logs, balanced correction buffers, and clinical-domain adaptation. It achieves strong performance across general NLI benchmarks, adversarial datasets, and Alzheimer’s-focused reasoning tasks.
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AetherMind_SRL continuously improves through structured error logs, balanced correction buffers, and clinical-domain adaptation. It achieves strong performance across general NLI benchmarks, adversarial datasets, and Alzheimer’s-focused reasoning tasks.
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 Official Research Preprint (Zenodo DOI):
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 Official Research Preprint (Zenodo DOI):
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https://doi.org/10.5281/zenodo.17670971
https://doi.org/10.5281/zenodo.17670971
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Model Repository (Hugging Face):
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Model Repository (Hugging Face):
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https://huggingface.co/samerzaher80/AetherMind_SRL
samerzaher80/AetherMind_SRL
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https://huggingface.co/samerzaher80/AetherMind_SRL
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Full community article (Hugging Face Blog):
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Full community article (Hugging Face Blog):
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https://huggingface.co/blog/samerzaher80/aethermind-srl
https://huggingface.co/blog/samerzaher80/aethermind-srl
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New Research Release: AetherMind_SRL — Self-Reflective Learning for Robust Natural Language Inference (NLI)
By: Sameer S. Najm

After more than a year of continuous work, experimentation, and refinement, I am proud to officially publish AetherMind_SRL, a self-improving Transformer model trained using Self-Reflective Learning (SRL) — a technique that enables the model to learn from its own mistakes.

This research integrates:

🔹 Knowledge Distillation from DeBERTa-v3-base
🔹 Self-Reflective Learning loops
🔹 Adversarial ANLI training
🔹 Clinical Alzheimer’s reasoning (ADNI)
🔹 SMART Error Buffers for hard-example mining

  What makes it unique?
AetherMind_SRL continuously improves through structured error logs, balanced correction buffers, and clinical-domain adaptation. It achieves strong performance across general NLI benchmarks, adversarial datasets, and Alzheimer’s-focused reasoning tasks.

 Official Research Preprint (Zenodo DOI):
 https://doi.org/10.5281/zenodo.17670971
Model Repository (Hugging Face):
https://huggingface.co/samerzaher80/AetherMind_SRL
Full community article (Hugging Face Blog):
https://huggingface.co/blog/samerzaher80/aethermind-srl
🚀
YatharthS John6666