works on

From the 1 of 13 linked papers with an AI index.

activity
20242026
collaborators

13 papers

cs.CV2026

OmniPhys: Knowledge-Graph-Driven Benchmarking and Collective Optimization for Physical Commonsense in Text-to-Image Generation

Yajing Xu, Yarong Lan, Jiaoyan Chen +6

The paper presents OmniPhys, a knowledge-graph-based benchmark for evaluating physical commonsense in text-to-image models, and OmniPrompt, an iterative optimization framework that…

cs.CV2026

Structured and Abstractive Reasoning on Multi-modal Relational Knowledge Images

Yichi Zhang, Zhuo Chen, Lingbing Guo +2

Understanding and reasoning with abstractive information from the visual modality presents significant challenges for current multi-modal large language models (MLLMs). Among the v…

cs.CL2026

Collaboration of Fusion and Independence: Hypercomplex-driven Robust Multi-Modal Knowledge Graph Completion

Zhiqiang Liu, Yichi Zhang, Mengshu Sun +2

Multi-modal knowledge graph completion (MMKGC) aims to discover missing facts in multi-modal knowledge graphs (MMKGs) by leveraging both structural relationships and diverse modali…

cs.CV2026

Seedance 2.0: Advancing Video Generation for World Complexity

Team Seedance, De Chen, Liyang Chen +168

Seedance 2.0 is a new native multi-modal audio-video generation model, officially released in China in early February 2026. Compared with its predecessors, Seedance 1.0 and 1.5 Pro…

cs.CL2026

Every Little Helps: Building Knowledge Graph Foundation Model with Fine-grained Transferable Multi-modal Tokens

Yichi Zhang, Zhuo Chen, Lingbing Guo +2

Multi-modal knowledge graph reasoning (MMKGR) aims to predict the missing links by exploiting both graph structure information and multi-modal entity contents. Most existing works…

cs.CV2025

Abstractive Visual Understanding of Multi-modal Structured Knowledge: A New Perspective for MLLM Evaluation

Yichi Zhang, Zhuo Chen, Lingbing Guo +4

Multi-modal large language models (MLLMs) incorporate heterogeneous modalities into LLMs, enabling a comprehensive understanding of diverse scenarios and objects. Despite the proli…