activity
20232026
most citedFerret: Refer and Ground Anything Anywhere at Any Granularity

43 citations · 61 across the 25 of their papers we have counts for

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9 papers · 1 filter

cs.CV2025

PRISM-Bench: A Benchmark of Puzzle-Based Visual Tasks with CoT Error Detection

Yusu Qian, Cheng Wan, Chao Jia +3

Multimodal large language models (MLLMs) have achieved remarkable progress on vision-language tasks, yet their reasoning processes remain sometimes unreliable. We introduce PRISM-B…

cs.CV2025

UniGen-1.5: Enhancing Image Generation and Editing through Reward Unification in Reinforcement Learning

Rui Tian, Mingfei Gao, Haiming Gang +5

We present UniGen-1.5, a unified multimodal large language model (MLLM) for advanced image understanding, generation and editing. Building upon UniGen, we comprehensively enhance t…

cs.CV2025

SO-Bench: A Structural Output Evaluation of Multimodal LLMs

Di Feng, Kaixin Ma, Feng Nan +9

Multimodal large language models (MLLMs) are increasingly deployed in real-world, agentic settings where outputs must not only be correct, but also conform to predefined data schem…

cs.CV2025

Pico-Banana-400K: A Large-Scale Dataset for Text-Guided Image Editing

Yusu Qian, Eli Bocek-Rivele, Liangchen Song +5

Recent advances in multimodal models have demonstrated remarkable text-guided image editing capabilities, with systems like GPT-4o and Nano-Banana setting new benchmarks. However,…

cs.CV2025

DeepMMSearch-R1: Empowering Multimodal LLMs in Multimodal Web Search

Kartik Narayan, Yang Xu, Tian Cao +7

Multimodal Large Language Models (MLLMs) in real-world applications require access to external knowledge sources and must remain responsive to the dynamic and ever-changing real-wo…

cs.CV2025

MANZANO: A Simple and Scalable Unified Multimodal Model with a Hybrid Vision Tokenizer

Yanghao Li, Rui Qian, Bowen Pan +24

Unified multimodal Large Language Models (LLMs) that can both understand and generate visual content hold immense potential. However, existing open-source models often suffer from…