Training Agents to Evolve with Their Harness: TaoLive Digital Avatar Agent Technical Report
AI-powered digital avatar streamers must answer product questions, engage viewers, and execute marketing strategies in real time, demanding low latency, frequent strategy updates, and accurate yet effective responses. Evolvable Harnesses, whose Skills, Hooks, prompts, and tools can be updated independently of model weights, enable rapid iteration but expose a trade-off: large models adapt zero-shot yet are too slow, whereas compact models meet latency targets but overfit to fixed Harness configurations. We propose Harness-Aware Training (HAT), which trains compact models to adapt to changing Harnesses. Its key component, Harness-State Augmentation (HSA), applies task-preserving transforma...
| Authors | TaoLive AIGC LLM Team, Yuhan Sun, Wenhao Lin et al. |
|---|---|
| Primary category | cs.CL |
| Published | 16 August 2026 |
| Last updated at source | 4 October 2026 |
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