The authors represent each objective constraint through three independent components: Scope, the response segment governed by the rule; Target, the feature being constrained; and Range, the permitted values.
Graded rewards improve language models’ control over scoped instructions
ScopeIF trains models to satisfy constraints attached to specific response segments by measuring how severely each constraint is violated.
Chinese Tech
Bosi Wen · Yilin Niu · Xiaoying Ning · Ying Zhang · Hongning Wang · Minlie Huang
Tsinghua University · Zhipu AI
Research Digest··2 min read
Thread:Agent Rule Compliance
Wen et al.
Why this paper
From Zhipu AI and Tsinghua University · Part of Agent Rule Compliance, now 24 papers
In one line
ScopeIF uses graded rewards and a unified constraint schema to improve LLMs' precise instruction following on scope-aware constraints.
What we could check
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