collaborators

8 papers

cs.CV2026

Seeing Together: Multi-Robot Cooperative Egocentric Spatial Reasoning with Multimodal Large Language Models

Kunyu Peng, Zhikun Zhou, Kailun Yang +9

Multimodal Large Language Models (MLLMs) have made substantial progress in egocentric video understanding, but their ability to reason cooperatively from multiple embodied viewpoin…

cs.CV2026

EPIC-Bench: A Perception-Centric Benchmark for Fine-Grained Embodied Visual Grounding in Vision-Language Models

Haozhe Shan, Xiancong Ren, Han Dong +9

While large vision-language models (VLMs) are increasingly adopted as the perceptual backbone for embodied agents, existing benchmarks often rely on question-answering or multiple-…

cs.MM2026

MSVBench: Towards Human-Level Evaluation of Multi-Shot Video Generation

Haoyuan Shi, Yunxin Li, Nanhao Deng +5

The evolution of video generation toward complex, multi-shot narratives has exposed a critical deficit in current evaluation methods. Existing benchmarks remain anchored to single-…

cs.CL2025

Uni-MoE-2.0-Omni: Scaling Language-Centric Omnimodal Large Model with Advanced MoE, Training and Data

Yunxin Li, Xinyu Chen, Shenyuan Jiang +9

We present Uni-MoE 2.0 from the Lychee family. As a fully open-source omnimodal large model (OLM), it substantially advances Lychee's Uni-MoE series in language-centric multimodal…

cs.SD2025

UniMoE-Audio: Unified Speech and Music Generation with Dynamic-Capacity MoE

Zhenyu Liu, Yunxin Li, Xuanyu Zhang +13

Recent advances in unified multimodal models indicate a clear trend towards comprehensive content generation. However, the auditory domain remains a significant challenge, with mus…

cs.MA2025

AniMaker: Multi-Agent Animated Storytelling with MCTS-Driven Clip Generation

Haoyuan Shi, Yunxin Li, Xinyu Chen +3

Despite rapid advancements in video generation models, generating coherent storytelling videos that span multiple scenes and characters remains challenging. Current methods often r…