1 citations · 4 across the 28 of their papers we have counts for
12 papers · 1 filter
CoS: Towards Optimal Event Scheduling via Chain-of-Scheduling
Yiming Zhao, Jiwei Tang, Shimin Di +3
Recommending event schedules is a key issue in Event-based Social Networks (EBSNs) in order to maintain user activity. An effective recommendation is required to maximize the user'…
A Survey of Data Agents: Emerging Paradigm or Overstated Hype?
Yizhang Zhu, Liangwei Wang, Chenyu Yang +22
The rapid advancement of large language models (LLMs) has spurred the emergence of data agents, autonomous systems designed to orchestrate Data + AI ecosystems for tackling complex…
MuPlon: Multi-Path Causal Optimization for Claim Verification through Controlling Confounding
Hanghui Guo, Shimin Di, Pasquale De Meo +2
As a critical task in data quality control, claim verification aims to curb the spread of misinformation by assessing the truthfulness of claims based on a wide range of evidence.…
RobustFlow: Towards Robust Agentic Workflow Generation
Shengxiang Xu, Jiayi Zhang, Shimin Di +5
The automated generation of agentic workflows is a promising frontier for enabling large language models (LLMs) to solve complex tasks. However, the empirical study reveals that ex…
Code2MCP: Transforming Code Repositories into MCP Services
Chaoqian Ouyang, Ling Yue, Shimin Di +5
The Model Context Protocol (MCP) aims to create a standard for how Large Language Models use tools. However, most current research focuses on selecting tools from an existing pool.…
E3-Rewrite: Learning to Rewrite SQL for Executability, Equivalence,and Efficiency
Dongjie Xu, Yue Cui, Weijie Shi +9
SQL query rewriting aims to reformulate a query into a more efficient form while preserving equivalence. Most existing methods rely on predefined rewrite rules. However, such rule-…
Towards Self-cognitive Exploration: Metacognitive Knowledge Graph Retrieval Augmented Generation
Xujie Yuan, Shimin Di, Jielong Tang +2
Knowledge Graph-based Retrieval-Augmented Generation (KG-RAG) significantly enhances the reasoning capabilities of LargeLanguage Models by leveraging structured knowledge. However,…
Don't Overthink It: A Survey of Efficient R1-style Large Reasoning Models
Linan Yue, Yichao Du, Yizhi Wang +8
Recently, Large Reasoning Models (LRMs) have gradually become a research hotspot due to their outstanding performance in handling complex tasks. Among them, DeepSeek R1 has garnere…
RemoteReasoner: Towards Unifying Geospatial Reasoning Workflow
Liang Yao, Fan Liu, Hongbo Lu +5
Remote sensing imagery presents vast, inherently unstructured spatial data, necessitating sophisticated reasoning to interpret complex user intents and contextual relationships bey…
RemoteSAM: Towards Segment Anything for Earth Observation
Liang Yao, Fan Liu, Delong Chen +6
We aim to develop a robust yet flexible visual foundation model for Earth observation. It should possess strong capabilities in recognizing and localizing diverse visual targets wh…
DioR: Adaptive Cognitive Detection and Contextual Retrieval Optimization for Dynamic Retrieval-Augmented Generation
Hanghui Guo, Jia Zhu, Shimin Di +3
Dynamic Retrieval-augmented Generation (RAG) has shown great success in mitigating hallucinations in large language models (LLMs) during generation. However, existing dynamic RAG m…
Foam-Agent: A Large Language Model-Based Multi-Agent Framework for Automating Computational Fluid Dynamics Workflows
Ling Yue, Nithin Somasekharan, Tingwen Zhang +4
Computational fluid dynamics (CFD) has been the main workhorse of computational physics, yet its steep learning curve and fragmented, multi-stage workflow create significant barrie…