1 citations · 2 across the 10 of their papers we have counts for
6 papers · 1 filter
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos
Yuqi Tang, Yang Shi, Zhuoran Zhang +21
Recent video generative models have greatly improved the realism of AI-generated videos, yet their outputs still exhibit artifacts such as temporal inconsistencies, structural dist…
Controlling Decision Drift in Multimodal Sentiment Analysis with Missing Modalities
Chenglizhao Chen, Yuchen Cao, Xinyu Liu +3
Multimodal sentiment analysis relies on textual, acoustic, and visual signals, yet real-world data often suffer from modality missing and quality imbalance. Existing methods genera…
GLM-5V-Turbo: Toward a Native Foundation Model for Multimodal Agents
V Team, Wenyi Hong, Xiaotao Gu +94
We present GLM-5V-Turbo, a step toward native foundation models for multimodal agents. As foundation models are increasingly deployed in real environments, agentic capability depen…
Understanding Real-World Traffic Safety through RoadSafe365 Benchmark
Xinyu Liu, Darryl C. Jacob, Yuxin Liu +4
Although recent traffic benchmarks have advanced multimodal data analysis, they generally lack systematic evaluation aligned with official safety standards. To fill this gap, we in…
Language-Driven Object-Oriented Two-Stage Method for Scene Graph Anticipation
Xiaomeng Zhu, Changwei Wang, Haozhe Wang +2
A scene graph is a structured representation of objects and their spatio-temporal relationships in dynamic scenes. Scene Graph Anticipation (SGA) involves predicting future scene g…
ExAct: A Video-Language Benchmark for Expert Action Analysis
Han Yi, Yulu Pan, Feihong He +4
We present ExAct, a new video-language benchmark for expert-level understanding of skilled physical human activities. Our new benchmark contains 3521 expert-curated video question-…