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20232026
most citedInjecting Domain-Specific Knowledge into Large Language Models: A Comprehensive Survey

10 citations · 17 across the 35 of their papers we have counts for

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cs.CV2026

MULTITEXTEDIT: Benchmarking Cross-Lingual Degradation in Text-in-Image Editing

Liwei Cheng, Shibo Feng, Lunjie Zhou +2

Text-in-image editing has become a key capability for visual content creation, yet existing benchmarks remain overwhelmingly English-centric and often conflate visual plausibility…

cs.CV2026

TextAlign: Preference Alignment for Text Rendering with Hierarchical Rewards

Mingxuan Cui, Jingpu Yang, Fengxian Ji +7

Faithful text rendering remains a persistent weakness of large text-to-image generative models, as it requires both semantic instruction following and fine-grained glyph-level stru…

cs.CV2026

FineState-Bench: Benchmarking State-Conditioned Grounding for Fine-grained GUI State Setting

Fengxian Ji, Jingpu Yang, Zirui Song +5

Despite the rapid progress of large vision-language models (LVLMs), fine-grained, state-conditioned GUI interaction remains challenging. Current evaluations offer limited coverage,…

cs.CV2026

ServImage: An Image Generation and Editing Benchmark from Real-world Commercial Imaging Services

Fengxian Ji, Jingpu Yang, Zirui Song +5

Recent image generation and editing models demonstrate robust adherence to instructions and high visual quality on academic benchmarks. However, their performance on paid, real-wor…

cs.CV2026

FlashSign: Pose-Free Guidance for Efficient Sign Language Video Generation

Liuzhou Zhang, Zeyu Zhang, Biao Wu +10

Sign language plays a crucial role in bridging communication gaps between the deaf and hard-of-hearing communities. However, existing sign language video generation models often re…

cs.CV2025

FineState-Bench: A Comprehensive Benchmark for Fine-Grained State Control in GUI Agents

Fengxian Ji, Jingpu Yang, Zirui Song +6

With the rapid advancement of generative artificial intelligence technology, Graphical User Interface (GUI) agents have demonstrated tremendous potential for autonomously managing…

cs.CV2025★ 1 cited

Motion Anything: Any to Motion Generation

Zeyu Zhang, Yiran Wang, Wei Mao +7

Conditional motion generation has been extensively studied in computer vision, yet two critical challenges remain. First, while masked autoregressive methods have recently outperfo…

cs.CV2025

PedDet: Adaptive Spectral Optimization for Multimodal Pedestrian Detection

Rui Zhao, Zeyu Zhang, Yi Xu +6

Pedestrian detection in intelligent transportation systems has made significant progress but faces two critical challenges: (1) insufficient fusion of complementary information bet…

cs.CV2025

Geolocation with Real Human Gameplay Data: A Large-Scale Dataset and Human-Like Reasoning Framework

Zirui Song, Jingpu Yang, Yuan Huang +6

Geolocation, the task of identifying an image's location, requires complex reasoning and is crucial for navigation, monitoring, and cultural preservation. However, current methods…

cs.CV2023

BenchLMM: Benchmarking Cross-style Visual Capability of Large Multimodal Models

Rizhao Cai, Zirui Song, Dayan Guan +4

Large Multimodal Models (LMMs) such as GPT-4V and LLaVA have shown remarkable capabilities in visual reasoning with common image styles. However, their robustness against diverse s…