2 citations · 4 across the 8 of their papers we have counts for
8 papers · 1 filter
DV-World: Benchmarking Data Visualization Agents in Real-World Scenarios
Jinxiang Meng, Shaoping Huang, Fangyu Lei +17
Real-world data visualization (DV) requires native environmental grounding, cross-platform evolution, and proactive intent alignment. Yet, existing benchmarks often suffer from cod…
DAComp: Benchmarking Data Agents across the Full Data Intelligence Lifecycle
Fangyu Lei, Jinxiang Meng, Yiming Huang +14
Real-world enterprise data intelligence workflows encompass data engineering that turns raw sources into analytical-ready tables and data analysis that convert those tables into de…
Reasoning-Table: Exploring Reinforcement Learning for Table Reasoning
Fangyu Lei, Jinxiang Meng, Yiming Huang +5
Table reasoning, encompassing tasks such as table question answering, fact verification, and text-to-SQL, requires precise understanding of structured tabular data, coupled with nu…
GATE: Graph-based Adaptive Tool Evolution Across Diverse Tasks
Jianwen Luo, Yiming Huang, Jinxiang Meng +7
Large Language Models (LLMs) have shown great promise in tool-making, yet existing frameworks often struggle to efficiently construct reliable toolsets and are limited to single-ta…
DA-Code: Agent Data Science Code Generation Benchmark for Large Language Models
Yiming Huang, Jianwen Luo, Yan Yu +8
We introduce DA-Code, a code generation benchmark specifically designed to assess LLMs on agent-based data science tasks. This benchmark features three core elements: First, the ta…
Neeko: Leveraging Dynamic LoRA for Efficient Multi-Character Role-Playing Agent
Xiaoyan Yu, Tongxu Luo, Yifan Wei +4
Large Language Models (LLMs) have revolutionized open-domain dialogue agents but encounter challenges in multi-character role-playing (MCRP) scenarios. To address the issue, we pre…
TableQAKit: A Comprehensive and Practical Toolkit for Table-based Question Answering
Fangyu Lei, Tongxu Luo, Pengqi Yang +8
Table-based question answering (TableQA) is an important task in natural language processing, which requires comprehending tables and employing various reasoning ways to answer the…
S3Eval: A Synthetic, Scalable, Systematic Evaluation Suite for Large Language Models
Fangyu Lei, Qian Liu, Yiming Huang +3
The rapid development of Large Language Models (LLMs) has led to great strides in model capabilities like long-context understanding and reasoning. However, as LLMs are able to pro…