activity
20232026
most citedExtending Multi-modal Contrastive Representations

2 citations · 4 across the 13 of their papers we have counts for

collaborators

13 papers

cs.AI2026

ForesightSafety Bench: A Frontier Risk Evaluation and Governance Framework towards Safe AI

Haibo Tong, Feifei Zhao, Linghao Feng +18

Rapidly evolving AI exhibits increasingly strong autonomy and goal-directed capabilities, accompanied by derivative systemic risks that are more unpredictable, difficult to control…

cs.CV2026

WorldCompass: Reinforcement Learning for Long-Horizon World Models

Zehan Wang, Tengfei Wang, Haiyu Zhang +9

This work presents WorldCompass, a novel Reinforcement Learning (RL) post-training framework for the long-horizon, interactive video-based world models, enabling them to explore th…

cs.CV2026

Unified Thinker: A General Reasoning Modular Core for Image Generation

Sashuai Zhou, Qiang Zhou, Jijin Hu +9

Despite impressive progress in high-fidelity image synthesis, generative models still struggle with logic-intensive instruction following, exposing a persistent reasoning--executio…

cs.CV2025

UnicEdit-10M: A Dataset and Benchmark Breaking the Scale-Quality Barrier via Unified Verification for Reasoning-Enriched Edits

Keming Ye, Zhipeng Huang, Canmiao Fu +7

With the rapid advances of powerful multimodal models such as GPT-4o, Nano Banana, and Seedream 4.0 in Image Editing, the performance gap between closed-source and open-source mode…

cs.CV2025

PSR: Scaling Multi-Subject Personalized Image Generation with Pairwise Subject-Consistency Rewards

Shulei Wang, Longhui Wei, Xin He +4

Personalized generation models for a single subject have demonstrated remarkable effectiveness, highlighting their significant potential. However, when extended to multiple subject…

cs.HC2025

F.A.C.U.L.: Language-Based Interaction with AI Companions in Gaming

Wenya Wei, Sipeng Yang, Qixian Zhou +12

In cooperative video games, traditional AI companions are deployed to assist players, who control them using hotkeys or command wheels to issue predefined commands such as ``attack…

cs.RO2025

Open-Vocabulary Spatio-Temporal Scene Graph for Robot Perception and Teleoperation Planning

Yi Wang, Zeyu Xue, Mujie Liu +5

Teleoperation via natural-language reduces operator workload and enhances safety in high-risk or remote settings. However, in dynamic remote scenes, transmission latency during bid…

eess.AS2025

ThinkSound: Chain-of-Thought Reasoning in Multimodal Large Language Models for Audio Generation and Editing

Huadai Liu, Kaicheng Luo, Jialei Wang +4

While end-to-end video-to-audio generation has greatly improved, producing high-fidelity audio that authentically captures the nuances of visual content remains challenging. Like p…

cs.CL2025

Command A: An Enterprise-Ready Large Language Model

Team Cohere, :, Aakanksha +227

In this report we describe the development of Command A, a powerful large language model purpose-built to excel at real-world enterprise use cases. Command A is an agent-optimised…

cs.CV2024★ 1 cited

FADA: Fast Diffusion Avatar Synthesis with Mixed-Supervised Multi-CFG Distillation

Tianyun Zhong, Chao Liang, Jianwen Jiang +3

Diffusion-based audio-driven talking avatar methods have recently gained attention for their high-fidelity, vivid, and expressive results. However, their slow inference speed limit…

cs.CV2023★ 1 cited

Unsupervised Discovery of Interpretable Directions in h-space of Pre-trained Diffusion Models

Zijian Zhang, Luping Liu, Zhijie Lin +2

We propose the first unsupervised and learning-based method to identify interpretable directions in h-space of pre-trained diffusion models. Our method is derived from an existing…

cs.MM2023

Weakly-Supervised Video Moment Retrieval via Regularized Two-Branch Proposal Networks with Erasing Mechanism

Haoyuan Li, Zhou Zhao, Zhu Zhang +1

Video moment retrieval is to identify the target moment according to the given sentence in an untrimmed video. Due to temporal boundary annotations of the video are extremely time-…

cs.CV2023★ 2 cited

Extending Multi-modal Contrastive Representations

Zehan Wang, Ziang Zhang, Luping Liu +4

Multi-modal contrastive representation (MCR) of more than three modalities is critical in multi-modal learning. Although recent methods showcase impressive achievements, the high d…