Proof pending. This topic has not reached the minimum paper threshold yet.
Large language models (LLMs) exhibit social biases that reinforce harmful stereotypes, limiting their safe deployment. Most existing debiasing methods adopt a suppressive paradigm by modifying paramet...
Social biases inherent in large language models (LLMs) raise significant fairness concerns. Retrieval-Augmented Generation (RAG) architectures, which retrieve external knowledge sources to enhance the...
Fair decisions require ignoring irrelevant, potentially biasing, information. To achieve this, decision-makers need to approximate what decision they would have made had they not known certain facts, ...
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Canonical route: /topics
Agent Handoff
Canonical ID bias-mitigation-in-ai | Route /topic/bias-mitigation-in-ai
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/topic/bias-mitigation-in-aiMCP example
{
"tool": "search_papers",
"arguments": {
"query": "Bias Mitigation in AI",
"cluster": "Bias Mitigation in AI"
}
}source_context
{
"surface": "topic",
"mode": "topic",
"query": "Bias Mitigation in AI",
"normalized_query": "bias-mitigation-in-ai",
"route": "/topic/bias-mitigation-in-ai",
"paper_ref": null,
"topic_slug": "bias-mitigation-in-ai",
"benchmark_ref": null,
"dataset_ref": null
}Use This Via API or MCP
Topic pages bundle paper counts, viability trends, author concentration, and top questions into one canonical surface your agents can reference before they open Signal Canvas or create a workspace.