activity
20242026
collaborators

7 papers

cs.GR2026

JoyAI-Image: Awaking Spatial Intelligence in Unified Multimodal Understanding and Generation

Lin Song, Wenbo Li, Guoqing Ma +16

We present JoyAI-Image, a unified multimodal foundation model for visual understanding, text-to-image generation, and instruction-guided image editing. JoyAI-Image couples a spatia…

cs.CV2026

Thinking with Novel Views: A Systematic Analysis of Generative-Augmented Spatial Intelligence

Yanbing Zhang, Bo Wang, Jianhui Liu +9

Current Large Multimodal Models (LMMs) struggle with spatial reasoning tasks requiring viewpoint-dependent understanding, largely because they are confined to a single, static obse…

cs.CL2025

A Controllable Examination for Long-Context Language Models

Yijun Yang, Zeyu Huang, Wenhao Zhu +4

Existing frameworks for evaluating long-context language models (LCLM) can be broadly categorized into real-world applications (e.g, document summarization) and synthetic tasks (e.…

cs.CL2025

Evaluating and Improving Graph to Text Generation with Large Language Models

Jie He, Yijun Yang, Wanqiu Long +3

Large language models (LLMs) have demonstrated immense potential across various tasks. However, research for exploring and improving the capabilities of LLMs in interpreting graph…

cs.AI2024

From An LLM Swarm To A PDDL-Empowered HIVE: Planning Self-Executed Instructions In A Multi-Modal Jungle

Kaustubh Vyas, Damien Graux, Yijun Yang +8

In response to the call for agent-based solutions that leverage the ever-increasing capabilities of the deep models' ecosystem, we introduce Hive -- a comprehensive solution for kn…

cs.CL2024

UniArk: Improving Generalisation and Consistency for Factual Knowledge Extraction through Debiasing

Yijun Yang, Jie He, Pinzhen Chen +2

Several recent papers have investigated the potential of language models as knowledge bases as well as the existence of severe biases when extracting factual knowledge. In this wor…

cs.CL2024

EEE-QA: Exploring Effective and Efficient Question-Answer Representations

Zhanghao Hu, Yijun Yang, Junjie Xu +2

Current approaches to question answering rely on pre-trained language models (PLMs) like RoBERTa. This work challenges the existing question-answer encoding convention and explores…