activity
20192026
most citedFine-Grained Semantically Aligned Vision-Language Pre-Training

29 citations · 116 across the 52 of their papers we have counts for

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Showing 2025Show all

15 papers · 1 filter

cs.CV2025

OmniMoGen: Unifying Human Motion Generation via Learning from Interleaved Text-Motion Instructions

Wendong Bu, Kaihang Pan, Yuze Lin +6

Large language models (LLMs) have unified diverse linguistic tasks within a single framework, yet such unification remains unexplored in human motion generation. Existing methods a…

cs.CV2025

WiseEdit: Benchmarking Cognition- and Creativity-Informed Image Editing

Kaihang Pan, Weile Chen, Haiyi Qiu +6

Recent image editing models boast next-level intelligent capabilities, facilitating cognition- and creativity-informed image editing. Yet, existing benchmarks provide too narrow a…

cs.CV2025

Towards Physically Executable 3D Gaussian for Embodied Navigation

Bingchen Miao, Rong Wei, Zhiqi Ge +8

3D Gaussian Splatting (3DGS), a 3D representation method with photorealistic real-time rendering capabilities, is regarded as an effective tool for narrowing the sim-to-real gap. H…

cs.CL2025

Fast Thinking for Large Language Models

Haoyu Zheng, Zhuonan Wang, Yuqian Yuan +7

Reasoning-oriented Large Language Models (LLMs) often rely on generating explicit tokens step by step, and their effectiveness typically hinges on large-scale supervised fine-tunin…

cs.AI2025

Towards Meta-Cognitive Knowledge Editing for Multimodal LLMs

Zhaoyu Fan, Kaihang Pan, Mingze Zhou +7

Knowledge editing enables multimodal large language models (MLLMs) to efficiently update outdated or incorrect information. However, existing benchmarks primarily emphasize cogniti…

cs.CV2025

What Limits Virtual Agent Application? OmniBench: A Scalable Multi-Dimensional Benchmark for Essential Virtual Agent Capabilities

Wendong Bu, Yang Wu, Qifan Yu +10

As multimodal large language models (MLLMs) advance, MLLM-based virtual agents have demonstrated remarkable performance. However, existing benchmarks face significant limitations,…