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20242026
most citedAPEER: Automatic Prompt Engineering Enhances Large Language Model Reranking

14 citations · 14 across the 15 of their papers we have counts for

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8 papers · 1 filter

cs.CV2026

HIVE: Understanding Post-Hallucination Reasoning in Vision Language Models

Feng He, Zhenting Wang, Qifan Wang +4

Hallucinations in vision language models (VLMs) are commonly treated as semantic errors, yet they often arise from partial or ambiguous visual evidence. Prior work mainly focuses o…

cs.CV2026

UniVL: Unified Vision-Language Embedding for Spatially Grounded Contextual Image Generation

Jiayun Wang, Yu Wang, Weijie Gan +2

We introduce spatially grounded contextual image generation, a controllable image generation task that reframes the conditioning paradigm. Instead of supplying a reference image an…

cs.CV2025

LED: LLM Enhanced Open-Vocabulary Object Detection without Human Curated Data Generation

Yang Zhou, Shiyu Zhao, Yuxiao Chen +3

Large foundation models trained on large-scale vision-language data can boost Open-Vocabulary Object Detection (OVD) via synthetic training data, yet the hand-crafted pipelines oft…

cs.CV2025

Can Large Vision-Language Models Detect Images Copyright Infringement from GenAI?

Qipan Xu, Zhenting Wang, Xiaoxiao He +2

Generative AI models, renowned for their ability to synthesize high-quality content, have sparked growing concerns over the improper generation of copyright-protected material. Whi…

cs.CV2025

The Hidden Life of Tokens: Reducing Hallucination of Large Vision-Language Models via Visual Information Steering

Zhuowei Li, Haizhou Shi, Yunhe Gao +7

Large Vision-Language Models (LVLMs) can reason effectively over both textual and visual inputs, but they tend to hallucinate syntactically coherent yet visually ungrounded content…

cs.CV2025

LoR-VP: Low-Rank Visual Prompting for Efficient Vision Model Adaptation

Can Jin, Ying Li, Mingyu Zhao +6

Visual prompting has gained popularity as a method for adapting pre-trained models to specific tasks, particularly in the realm of parameter-efficient tuning. However, existing vis…

cs.CV2025

MLLM-as-a-Judge for Image Safety without Human Labeling

Zhenting Wang, Shuming Hu, Shiyu Zhao +12

Image content safety has become a significant challenge with the rise of visual media on online platforms. Meanwhile, in the age of AI-generated content (AIGC), many image generati…

cs.CV2024

Accelerating Multimodal Large Language Models by Searching Optimal Vision Token Reduction

Shiyu Zhao, Zhenting Wang, Felix Juefei-Xu +7

Prevailing Multimodal Large Language Models (MLLMs) encode the input image(s) as vision tokens and feed them into the language backbone, similar to how Large Language Models (LLMs)…