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20242026
most citedDataGovBench: Benchmarking LLM Agents for Real-World Data Governance Workflows

1 citations · 1 across the 22 of their papers we have counts for

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cs.AI2026

EngiWorld: What Can Frontier Agents Deliver in Professional Engineering Environments?

Hongcheng Gao, Hailong Qu, Yu Lei +19

Autonomous agents have made rapid progress in general-purpose computer use, yet reliable automation of professional industrial engineering remains out of reach. Engineering workflo…

cs.AI2026

SpatialWorld: Benchmarking Interactive Spatial Reasoning of Multimodal Agents in Real-World Tasks

Hongcheng Gao, Hailong Qu, Jingyi Tang +18

Spatial reasoning is a foundational capability for multimodal large language models (MLLMs) to perceive and operate within the physical world. However, existing benchmarks predomin…

cs.AI2026

M2A: Multimodal Memory Agent with Dual-Layer Hybrid Memory for Long-Term Personalized Interactions

Junyu Feng, Binxiao Xu, Jiayi Chen +8

This work addresses the challenge of personalized question answering in long-term human-machine interactions: when conversational history spans weeks or months and exceeds the cont…

cs.AI2025★ 1 cited

DataGovBench: Benchmarking LLM Agents for Real-World Data Governance Workflows

Zhou Liu, Zhaoyang Han, Guochen Yan +5

Data governance ensures data quality, security, and compliance through policies and standards, a critical foundation for scaling modern AI development. Recently, large language mod…

cs.AI2025

SciAgent: A Unified Multi-Agent System for Generalistic Scientific Reasoning

Xuchen Li, Ruitao Wu, Xuanbo Liu +17

Recent advances in large language models have enabled AI systems to achieve expert-level performance on domain-specific scientific tasks, yet these systems remain narrow and handcr…