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cs.CL2026

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…

cs.CL2025

Dynamic Scaling of Unit Tests for Code Reward Modeling

Zeyao Ma, Xiaokang Zhang, Jing Zhang +3

Current large language models (LLMs) often struggle to produce accurate responses on the first attempt for complex reasoning tasks like code generation. Prior research tackles this…

cs.CL2024

SpreadsheetBench: Towards Challenging Real World Spreadsheet Manipulation

Zeyao Ma, Bohan Zhang, Jing Zhang +6

We introduce SpreadsheetBench, a challenging spreadsheet manipulation benchmark exclusively derived from real-world scenarios, designed to immerse current large language models (LL…

cs.CL2024

TableLLM: Enabling Tabular Data Manipulation by LLMs in Real Office Usage Scenarios

Xiaokang Zhang, Sijia Luo, Bohan Zhang +12

We introduce TableLLM, a robust large language model (LLM) with 8 billion parameters, purpose-built for proficiently handling tabular data manipulation tasks, whether they are embe…

cs.CL2023

GLM-Dialog: Noise-tolerant Pre-training for Knowledge-grounded Dialogue Generation

Jing Zhang, Xiaokang Zhang, Daniel Zhang-Li +10

We present GLM-Dialog, a large-scale language model (LLM) with 10B parameters capable of knowledge-grounded conversation in Chinese using a search engine to access the Internet kno…