activity
20242026
most citedInsQABench: Benchmarking Chinese Insurance Domain Question Answering with Large Language Models

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

cs.AI2026

SIMLIFE: Pattern Understanding for Long-Horizon Human-Agent Partnership

Run Peng, Zinnia Nie, Jing Ding +7

Understanding humans over long horizons requires agents to infer not only what people need in the moment, but also how routines form, why they repeat, and when they change. We intr…

cs.CL2025

BMMR: A Large-Scale Bilingual Multimodal Multi-Discipline Reasoning Dataset

Zhiheng Xi, Guanyu Li, Yutao Fan +13

In this paper, we introduce BMMR, a large-scale bilingual, multimodal, multi-disciplinary reasoning dataset for the community to develop and evaluate large multimodal models (LMMs)…

cs.CL2025

Vision-Language Models Are Not Pragmatically Competent in Referring Expression Generation

Ziqiao Ma, Jing Ding, Xuejun Zhang +6

Referring Expression Generation (REG) is a core task for evaluating the pragmatic competence of vision-language systems, requiring not only accurate semantic grounding but also adh…

cs.CL2025★ 1 cited

InsQABench: Benchmarking Chinese Insurance Domain Question Answering with Large Language Models

Jing Ding, Kai Feng, Binbin Lin +6

The application of large language models (LLMs) has achieved remarkable success in various fields, but their effectiveness in specialized domains like the Chinese insurance industr…

cs.CV2024

PDF-WuKong: A Large Multimodal Model for Efficient Long PDF Reading with End-to-End Sparse Sampling

Xudong Xie, Hao Yan, Liang Yin +6

Multimodal document understanding is a challenging task to process and comprehend large amounts of textual and visual information. Recent advances in Large Language Models (LLMs) h…