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This equation captures one of the core mathematical components of the system. model (LLM) to take a prompt x ∈X , and output a response a = [t1, t2, . . . ], where ti is the
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Evaluating Risks in Weak-to-Strong Alignment: A Bias-Variance Perspective explores Analyzes weak-to-strong AI alignment failures using a bias-variance perspective, identifying strong-model variance as a key predictor of deception.. Commercial viability score: 7/10 in AI Alignment.
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Canonical route: /paper/evaluating-risks-in-weak-to-strong-alignment-a-bias-variance-perspective
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Canonical ID evaluating-risks-in-weak-to-strong-alignment-a-bias-variance-perspective | Route /paper/evaluating-risks-in-weak-to-strong-alignment-a-bias-variance-perspective
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/paper/evaluating-risks-in-weak-to-strong-alignment-a-bias-variance-perspectiveMCP example
{
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}Paper proof page receipt window
/buildability/evaluating-risks-in-weak-to-strong-alignment-a-bias-variance-perspective
Subject: Evaluating Risks in Weak-to-Strong Alignment: A Bias-Variance Perspective
Verdict
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Dimensions overall score 7.0
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This equation captures one of the core mathematical components of the system. model (LLM) to take a prompt x ∈X , and output a response a = [t1, t2, . . . ], where ti is the
Page and bbox are available; crop image is pending.
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Receipt path
/buildability/evaluating-risks-in-weak-to-strong-alignment-a-bias-variance-perspective
Paper ref
evaluating-risks-in-weak-to-strong-alignment-a-bias-variance-perspective
arXiv id
2604.25077
Generated at
2026-04-29T02:32:25.527Z
Evidence freshness
fresh
Last verification
2026-04-29T02:32:25.527Z
Sources
3
References
0
Coverage
50%
Lineage hash
73f5892ecf07c2d944369fefc6a6d3ccc6fec34ee0e6d3cd75a11262037639d3
Canonical opportunity-kernel lineage hash.
External signature
unsigned_external
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Verification
not_verified
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Pending verification refs / 3 sources / Verification pending
repo_url
references
This equation captures one of the core mathematical components of the system. J(π) = Ex∼d0[Ea∼π(·|x)[r∗(x, a)] −ηDKL(π(· | x)||π0(· | x))]
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This equation defines the score or evaluation function that determines model quality.
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