APPA: Adaptive Preference Pluralistic Alignment for Fair Federated RLHF of LLMs explores A framework for fair federated reinforcement learning from human feedback that dynamically reweights group rewards to prioritize under-aligned groups without degrading overall alignment.. Commercial viability score: 4/10 in LLM Alignment.
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Canonical route: /paper/appa-adaptive-preference-pluralistic-alignment-for-fair-federated-rlhf-of-llms
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Agent Handoff
Canonical ID appa-adaptive-preference-pluralistic-alignment-for-fair-federated-rlhf-of-llms | Route /paper/appa-adaptive-preference-pluralistic-alignment-for-fair-federated-rlhf-of-llms
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/paper/appa-adaptive-preference-pluralistic-alignment-for-fair-federated-rlhf-of-llmsMCP example
{
"tool": "get_paper",
"arguments": {
"arxiv_id": "2604.04261"
}
}source_context
{
"surface": "paper",
"mode": "paper",
"query": "APPA: Adaptive Preference Pluralistic Alignment for Fair Federated RLHF of LLMs",
"normalized_query": "2604.04261",
"route": "/paper/appa-adaptive-preference-pluralistic-alignment-for-fair-federated-rlhf-of-llms",
"paper_ref": "appa-adaptive-preference-pluralistic-alignment-for-fair-federated-rlhf-of-llms",
"topic_slug": null,
"benchmark_ref": null,
"dataset_ref": null
}Constellation, claims, and market context stay visible on the paper proof page even when commercialization rails are held back for incomplete proof receipts.
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