6 papers · 1 filter
LARY: A Latent Action Representation Yielding Benchmark for Generalizable Vision-to-Action Alignment
Dujun Nie, Fengjiao Chen, Qi Lv +4
While the shortage of explicit action data limits Vision-Language-Action (VLA) models, human action videos offer a scalable yet unlabeled data source. A critical challenge in utili…
LongCat-Next: Lexicalizing Modalities as Discrete Tokens
Meituan LongCat Team, Bin Xiao, Chao Wang +86
The prevailing Next-Token Prediction (NTP) paradigm has driven the success of large language models through discrete autoregressive modeling. However, contemporary multimodal syste…
EvalTalker: Learning to Evaluate Real-Portrait-Driven Multi-Subject Talking Humans
Yingjie Zhou, Xilei Zhu, Siyu Ren +11
Speech-driven Talking Human (TH) generation, commonly known as "Talker," currently faces limitations in multi-subject driving capabilities. Extending this paradigm to "Multi-Talker…
Q-REAL: Towards Realism and Plausibility Evaluation for AI-Generated Content
Shushi Wang, Zicheng Zhang, Chunyi Li +7
Quality assessment of AI-generated content is crucial for evaluating model capability and guiding model optimization. However, most existing quality assessment datasets and models…
ViC-Bench: Benchmarking Visual-Interleaved Chain-of-Thought Capability in MLLMs with Free-Style Intermediate State Representations
Xuecheng Wu, Jiaxing Liu, Danlei Huang +8
Visual-Interleaved Chain-of-Thought (VI-CoT) enables Multi-modal Large Language Models (MLLMs) to continually update their understanding and decision space based on step-wise inter…
Q-Eval-100K: Evaluating Visual Quality and Alignment Level for Text-to-Vision Content
Zicheng Zhang, Tengchuan Kou, Shushi Wang +9
Evaluating text-to-vision content hinges on two crucial aspects: visual quality and alignment. While significant progress has been made in developing objective models to assess the…