SKILL-KD: Contrastive Skill Distillation for LLM Agents
Skill-based prompting has become a practical mechanism for improving large language model (LLM) agents, yet existing skill acquisition methods often treat skills as experience summaries, memory entries, or direct summaries of successful demonstrations. This creates a mismatch for weaker student agents: when a student fails because it lacks task knowledge or operational strategy, its failed trajectory may not contain enough evidence to infer the missing behavior, while the teacher trajectory may
Record details
Published: 3 August 2026
Source: HuggingFace Daily Papers
Category: Research
Topics: Children & education · Agents & autonomy
Retrieved: 6 August 2026
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ethics.ai (3 August 2026), “SKILL-KD: Contrastive Skill Distillation for LLM Agents,” evidence record 16605, https://ethics.ai/record/16605 (originally published by HuggingFace Daily Papers).
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