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license: mit |
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%3C!-- HTML_TAG_END --> |
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# Model Card: Agora-4B |
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## Model Summary |
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Agora-4B is a 4-billion parameter, BF16-precision transformer language model, designed for ethical, inclusive, and adaptive dialogue in multi-user domestic environments. Inspired by the research paper ["Plural Voices, Single Agent: Towards Inclusive AI in Multi-User Domestic Spaces"](https://doi.org/10.48550/arXiv.2510.19008), Agora-4B incorporates principles of fairness, value alignment, and accessibility to better serve diverse household users—including children, elderly, and Neurodivergent individuals. |
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**Repository:** [JoydeepC/Agora-4B](https://huggingface.co/JoydeepC/Agora-4B) |
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**Paper:** [Plural Voices, Single Agent](https://doi.org/10.48550/arXiv.2510.19008) |
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**Model size:** 4B parameters |
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**Tensor type:** BF16 |
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**Files:** Safetensors format (2 shards, ~8.07 GB), tokenizer files, configs, chat templates, etc. |
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## Intended Use |
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Agora-4B is intended for use as a core assistant agent in domestic AI deployments, especially in settings with multiple users and overlapping accessibility needs. Typical scenarios include: |
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Domestic voice assistants which must mediate between adult, child, and elderly users |
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Applications where context-sensitive safety, fairness, or ethical intervention is required |
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Research or development in inclusive, privacy-first AI for multi-agent, multi-user environments |
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## Model Architecture & Training |
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**Architecture:** 4B-parameter transformer, trained with curriculum blending human and synthetic dialogue |
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**Objective:** Optimized for fairness, multi-value alignment, ethical compliance, and accessibility-aware conversation |
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**Training Data:** Curated public datasets covering mental health, eldercare, education, and moral reasoning. Enhanced with fairness-aware, multi-user scenarios and privacy-centric synthetic examples. |
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**Ethical Safeguards:** Includes adaptive safety scaffolds (e.g., age-specific explanations, guidance for Neurodivergent users), autonomy sliders, and safe conflict resolution. |
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## Key Features |
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**Real-Time Value Alignment:** Dynamically identifies and negotiates conflicting user needs, values, and accessibility requirements |
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**Inclusive Design:** Special handling for overlooked populations (children, elderly, Neurodivergent), including step-by-step instructions, accessible language, and equitable interaction |
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**Privacy-Focused:** Avoids unnecessary data retention or sharing |
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**Adaptivity:** Safety, autonomy, and guidance dynamically adjusted per user/context |
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**Design Innovations:** Video guidance, autonomy sliders, family hubs, adaptive dashboards |
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**Performance:** Outperforms baselines in compliance, fairness, and safety (see paper for details) |
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- Compliance: 76% (vs 70% baseline) |
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- Fairness: 90% (vs 85% baseline) |
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- Safety violations: 0% (vs 7% baseline) |
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## Citation |
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If you use this model, please cite: |
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```bibtex |
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@misc{chandra2025pluralvoicessingleagent, |
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title={Plural Voices, Single Agent: Towards Inclusive AI in Multi-User Domestic Spaces}, |
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author={Joydeep Chandra and Satyam Kumar Navneet}, |
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year={2025}, |
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eprint={2510.19008}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.HC}, |
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url={https://arxiv.org/abs/2510.19008}, |
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} |
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``` |
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## Further Reading |
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[arXiv:2510.19008](https://arxiv.org/abs/2510.19008) |
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[Project repository (HuggingFace)](https://huggingface.co/JoydeepC/Agora-4B) |
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This model and codebase are open sourced for reproducibility and collaborative research on inclusive, agentic AI. |
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