6 citations · 16 across the 18 of their papers we have counts for
18 papers
One Prompt Does Not Fit All: Self-Meta-Evolve for Personalized Information Extraction
Hongliang Li, Lu Wang, Yong Xu +6
Large language models (LLMs) are increasingly deployed for enterprise information extraction (IE), where the same document must be reorganized differently for each user. Existing p…
ToolAtlas: Learning Once, Reusing Everywhere with Tool-Side Memory
Yue Fang, Zhibang Yang, Fangkai Yang +5
Large language model (LLM) agents increasingly rely on external tools served by shared providers and accessed by heterogeneous downstream agents. Existing approaches improve tool u…
CI-Work: Benchmarking Contextual Integrity in Enterprise LLM Agents
Wenjie Fu, Xiaoting Qin, Jue Zhang +5
Enterprise LLM agents can dramatically improve workplace productivity, but their core capability, retrieving and using internal context to act on a user's behalf, also creates new…
Privacy in Action: Towards Realistic Privacy Mitigation and Evaluation for LLM-Powered Agents
Shouju Wang, Fenglin Yu, Xirui Liu +5
The increasing autonomy of LLM agents in handling sensitive communications, accelerated by Model Context Protocol (MCP) and Agent-to-Agent (A2A) frameworks, creates urgent privacy…
MEETING DELEGATE: Benchmarking LLMs on Attending Meetings on Our Behalf
Lingxiang Hu, Shurun Yuan, Xiaoting Qin +5
In contemporary workplaces, meetings are essential for exchanging ideas and ensuring team alignment but often face challenges such as time consumption, scheduling conflicts, and in…
Enabling Autonomic Microservice Management through Self-Learning Agents
Fenglin Yu, Fangkai Yang, Xiaoting Qin +8
The increasing complexity of modern software systems necessitates robust autonomic self-management capabilities. While Large Language Models (LLMs) demonstrate potential in this do…
Reason-before-Retrieve: One-Stage Reflective Chain-of-Thoughts for Training-Free Zero-Shot Composed Image Retrieval
Yuanmin Tang, Xiaoting Qin, Jue Zhang +7
Composed Image Retrieval (CIR) aims to retrieve target images that closely resemble a reference image while integrating user-specified textual modifications, thereby capturing user…
Sharingan: Extract User Action Sequence from Desktop Recordings
Yanting Chen, Yi Ren, Xiaoting Qin +7
Video recordings of user activities, particularly desktop recordings, offer a rich source of data for understanding user behaviors and automating processes. However, despite advanc…
Navigating the Unknown: A Chat-Based Collaborative Interface for Personalized Exploratory Tasks
Yingzhe Peng, Xiaoting Qin, Zhiyang Zhang +6
The rise of large language models (LLMs) has revolutionized user interactions with knowledge-based systems, enabling chatbots to synthesize vast amounts of information and assist w…
AI Delegates with a Dual Focus: Ensuring Privacy and Strategic Self-Disclosure
Zhiyang Zhang, Xi Chen, Fangkai Yang +7
Large language model (LLM)-based AI delegates are increasingly utilized to act on behalf of users, assisting them with a wide range of tasks through conversational interfaces. Desp…
Intelligent Router for LLM Workloads: Improving Performance Through Workload-Aware Load Balancing
Kunal Jain, Anjaly Parayil, Ankur Mallick +10
Large Language Model (LLM) workloads have distinct prefill and decode phases with different compute and memory requirements which should ideally be accounted for when scheduling in…
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…
AutoRAG-HP: Automatic Online Hyper-Parameter Tuning for Retrieval-Augmented Generation
Jia Fu, Xiaoting Qin, Fangkai Yang +7
Recent advancements in Large Language Models have transformed ML/AI development, necessitating a reevaluation of AutoML principles for the Retrieval-Augmented Generation (RAG) syst…
Towards Cloud Efficiency with Large-scale Workload Characterization
Anjaly Parayil, Jue Zhang, Xiaoting Qin +4
Cloud providers introduce features (e.g., Spot VMs, Harvest VMs, and Burstable VMs) and optimizations (e.g., oversubscription, auto-scaling, power harvesting, and overclocking) to…
Workload Intelligence: Punching Holes Through the Cloud Abstraction
Lexiang Huang, Anjaly Parayil, Jue Zhang +13
Today, cloud workloads are essentially opaque to the cloud platform. Typically, the only information the platform receives is the virtual machine (VM) type and possibly a decoratio…
AllHands: Ask Me Anything on Large-scale Verbatim Feedback via Large Language Models
Chaoyun Zhang, Zicheng Ma, Yuhao Wu +12
Verbatim feedback constitutes a valuable repository of user experiences, opinions, and requirements essential for software development. Effectively and efficiently extracting valua…
Call Me When Necessary: LLMs can Efficiently and Faithfully Reason over Structured Environments
Sitao Cheng, Ziyuan Zhuang, Yong Xu +9
Large Language Models (LLMs) have shown potential in reasoning over structured environments, e.g., knowledge graph and table. Such tasks typically require multi-hop reasoning, i.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…