4 papers
CoCoDA: Co-evolving Compositional DAG for Tool-Augmented Agents
Ziyang Yu, Qiyue Li, Liang Zhao
Tool-augmented language models can extend small language models with external executable skills, but scaling the tool library creates a coupled challenge: the library must evolve w…
SkillLens: Adaptive Multi-Granularity Skill Reuse for Cost-Efficient LLM Agents
Yongliang Miao, Ziyang Yu, Liang Zhao +2
Skill libraries have become a practical way for LLM agents to reuse procedural experience across tasks. However, existing systems typically treat skills as flat, single-resolution…
Distilling LLM Reasoning into Graph of Concept Predictors
Ziyang Yu, Liang Zhao
Deploying Large Language Models (LLMs) for discriminative workloads is often limited by inference latency, compute, and API costs at scale. Active distillation reduces these costs…
Beyond Efficiency: A Systematic Survey of Resource-Efficient Large Language Models
Guangji Bai, Zheng Chai, Chen Ling +11
The burgeoning field of Large Language Models (LLMs), exemplified by sophisticated models like OpenAI's ChatGPT, represents a significant advancement in artificial intelligence. Th…