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

14 citations · 29 across the 44 of their papers we have counts for

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18 papers · 1 filter

cs.CV2026

Knossos and Ariadne: Benchmarking and Learning Complete Diagram Topology Extraction with Vision-Language Models

Bangwei Guo, Xujiang Zhao, Shengyu Chen +6

Structural diagrams are widely used to represent complex systems and relational information across scientific, engineering, procedural, and spatial domains. Recent vision-language…

cs.CV2026

TopoAgent: A Structure-Aware Perception-to-Reasoning Framework for Diagram-to-Graph Topology Extraction with Large Vision-Language Models

Bangwei Guo, Xujiang Zhao, Yanchi Liu +7

Diagram-to-graph topology extraction aims to extract a graph of entities and their connections from a structural diagram. This task remains challenging for current vision-language…

cs.CV2026

ES-VP : Energy-Shaped Dynamic Visual Prompting for Efficient Model Adaptation

Can Jin, Ying Li, Jingchen Sun +5

Visual prompting (VP) has emerged as a parameter-efficient method for adapting pre-trained models to downstream tasks. However, existing approaches encounter a trade-off between fl…

cs.CV2026

MemEye: A Visual-Centric Evaluation Framework for Multimodal Agent Memory

Minghao Guo, Qingyue Jiao, Zeru Shi +14

Long-term agent memory is increasingly multimodal, yet existing evaluations rarely test whether agents preserve the visual evidence needed for later reasoning. In prior work, many…

cs.CV2026

Improving Visual Reasoning with Iterative Evidence Refinement

Zeru Shi, Kai Mei, Yihao Quan +2

Vision language models (VLMs) are increasingly capable of reasoning over images, but robust visual reasoning often requires re-grounding intermediate steps in the underlying visual…

cs.CV2025

PrefGen: Multimodal Preference Learning for Preference-Conditioned Image Generation

Wenyi Mo, Tianyu Zhang, Yalong Bai +3

Preference-conditioned image generation seeks to adapt generative models to individual users, producing outputs that reflect personal aesthetic choices beyond the given textual pro…

cs.CV2025

MHB: Multimodal Handshape-aware Boundary Detection for Continuous Sign Language Recognition

Mingyu Zhao, Zhanfu Yang, Yang Zhou +4

This paper employs a multimodal approach for continuous sign recognition by first using ML for detecting the start and end frames of signs in videos of American Sign Language (ASL)…

cs.CV2025

Test-Time Spectrum-Aware Latent Steering for Zero-Shot Generalization in Vision-Language Models

Konstantinos M. Dafnis, Dimitris N. Metaxas

Vision-Language Models (VLMs) excel at zero-shot inference but often degrade under test-time domain shifts. For this reason, episodic test-time adaptation strategies have recently…

cs.CV2025

SignX: Continuous Sign Recognition in Compact Pose-Rich Latent Space

Sen Fang, Yalin Feng, Chunyu Sui +5

The complexity of Sign Language (SL) data processing brings many challenges. The current approach to recognition of SL signs aims to translate RGB sign language videos through pose…

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

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★ 1 cited

RadAlign: Advancing Radiology Report Generation with Vision-Language Concept Alignment

Difei Gu, Yunhe Gao, Yang Zhou +2

Automated chest radiographs interpretation requires both accurate disease classification and detailed radiology report generation, presenting a significant challenge in the clinica…

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★ 1 cited

Learning to Localize Actions in Instructional Videos with LLM-Based Multi-Pathway Text-Video Alignment

Yuxiao Chen, Kai Li, Wentao Bao +4

Learning to localize temporal boundaries of procedure steps in instructional videos is challenging due to the limited availability of annotated large-scale training videos. Recent…

cs.CV2024

New Capability to Look Up an ASL Sign from a Video Example

Carol Neidle, Augustine Opoku, Carey Ballard +4

Looking up an unknown sign in an ASL dictionary can be difficult. Most ASL dictionaries are organized based on English glosses, despite the fact that (1) there is no convention for…

cs.CV2024

Aligning Human Knowledge with Visual Concepts Towards Explainable Medical Image Classification

Yunhe Gao, Difei Gu, Mu Zhou +1

Although explainability is essential in the clinical diagnosis, most deep learning models still function as black boxes without elucidating their decision-making process. In this s…

cs.CV2024

How to Trace Latent Generative Model Generated Images without Artificial Watermark?

Zhenting Wang, Vikash Sehwag, Chen Chen +3

Latent generative models (e.g., Stable Diffusion) have become more and more popular, but concerns have arisen regarding potential misuse related to images generated by these models…

cs.CV2024★ 1 cited

Score-Guided Diffusion for 3D Human Recovery

Anastasis Stathopoulos, Ligong Han, Dimitris Metaxas

We present Score-Guided Human Mesh Recovery (ScoreHMR), an approach for solving inverse problems for 3D human pose and shape reconstruction. These inverse problems involve fitting…