๐คReddit r/MachineLearningโขStalecollected in 10h
Refusal Alignment Eval Fails on Routing
๐กFlaws in alignment evals exposed via Chinese LLM censorship
โก 30-Second TL;DR
What Changed
Probes hit 100% even on null/random data; held-out generalization discriminates
Why It Matters
Challenges current alignment evals, urging causal interventions over refusal benchmarks for reliable safety assessment across labs.
What To Do Next
Test held-out probes and ablate routing on your aligned LLMs.
Who should care:Researchers & Academics
Key Points
- โขProbes hit 100% even on null/random data; held-out generalization discriminates
- โขAblation removes censorship in 3/4 models; Qwen3-8B confabulates facts
- โขRouting lab-specific, orthogonal to safety; refusal evals miss steering changes
- โข46-model screen shows censorship in few models; proposes probe evidence hierarchy
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Original source: Reddit r/MachineLearning โ