5 papers · 1 filter
DoVer: Intervention-Driven Auto Debugging for LLM Multi-Agent Systems
Ming Ma, Jue Zhang, Fangkai Yang +4
Large language model (LLM)-based multi-agent systems are challenging to debug because failures often arise from long, branching interaction traces. The prevailing practice is to le…
From Reasoning to Answer: Empirical, Attention-Based and Mechanistic Insights into Distilled DeepSeek R1 Models
Jue Zhang, Qingwei Lin, Saravan Rajmohan +1
Large Reasoning Models (LRMs) generate explicit reasoning traces alongside final answers, yet the extent to which these traces influence answer generation remains unclear. In this…
AXIS: Efficient Human-Agent-Computer Interaction with API-First LLM-Based Agents
Junting Lu, Zhiyang Zhang, Fangkai Yang +7
Multimodal large language models (MLLMs) have enabled LLM-based agents to directly interact with application user interfaces (UIs), enhancing agents' performance in complex tasks.…
The Vision of Autonomic Computing: Can LLMs Make It a Reality?
Zhiyang Zhang, Fangkai Yang, Xiaoting Qin +6
The Vision of Autonomic Computing (ACV), proposed over two decades ago, envisions computing systems that self-manage akin to biological organisms, adapting seamlessly to changing e…
TaskWeaver: A Code-First Agent Framework
Bo Qiao, Liqun Li, Xu Zhang +16
Large Language Models (LLMs) have shown impressive abilities in natural language understanding and generation, leading to their widespread use in applications such as chatbots and…