SCOPE: Signal-Calibrated On-Policy Distillation Enhancement with Dual-Path Adaptive Weighting
On-policy reinforcement learning has become the dominant paradigm for reasoning alignment in large language models, yet its sparse, outcome-level rewards make token-level credit assignment notoriously difficult. On-Policy Distillation (OPD) alleviates this by introducing dense, token-level KL supervision from a teacher model, but typically applies this supervision uniformly across all rollouts, ignoring fundamental differences in signal quality. We propose Signal-Calibrated On-Policy Distillatio
Record details
Published: 12 April 2026
Source: arXiv
Category: Research
Topics: Regulation · Safety & alignment
Retrieved: 14 July 2026
Related evidence
These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.
AI Integrity: A New Paradigm for Verifiable AI Governance
arXiv · 13 April 2026
A Proposed Biomedical Data Policy Framework to Reduce Fragmentation, Improve Quality, and Incentivize Sharing in Indian Healthcare in the era of Artificial Intelligence and Digital Health
arXiv · 13 April 2026
From Reactive to Proactive: A Multi-Regulatory Empirical Analysis of 480 AI Incidents and a Data-Driven Governance Compliance Framework
arXiv · 10 April 2026
AISafetyBenchExplorer: A Metric-Aware Catalogue of AI Safety Benchmarks Reveals Fragmented Measurement and Weak Benchmark Governance
arXiv · 14 April 2026
Layered Mutability: Continuity and Governance in Persistent Self-Modifying Agents
arXiv · 16 April 2026
Decentralized autonomous organization and blockchain-based incentivization framework for community-based facilities management
arXiv · 16 April 2026
How to cite this record
ethics.ai (12 April 2026), “SCOPE: Signal-Calibrated On-Policy Distillation Enhancement with Dual-Path Adaptive Weighting,” evidence record 5993, https://ethics.ai/record/5993 (originally published by arXiv).
Use and limitations
This page is a stable index and citation surface for a source record. ethics.ai did not author the underlying report and has not independently verified every claim. Automatic topics may be imperfect. For consequential use, quote and cite the original publisher.