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

14 citations · 14 across the 9 of their papers we have counts for

collaborators

9 papers

cs.AI2026

Evidence Over Plans: Online Trajectory Verification for Skill Distillation

Yang Zhou, Zihan Dong, Zhenting Wang +7

Agent skills can remarkably improve task success rates by using human-written procedural documents, but their quality is difficult to assess without environment-grounded verificati…

cs.LG2026

DARE: Difficulty-Adaptive Reinforcement Learning with Co-Evolved Difficulty Estimation

Yang Zhou, Can Jin, Zihan Dong +7

Reinforcement learning improves the reasoning ability of large language models but remains costly and sample-inefficient, as many rollouts provide weak learning signals. Difficulty…

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

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)…

cs.AI2024★ 14 cited

APEER: Automatic Prompt Engineering Enhances Large Language Model Reranking

Can Jin, Hongwu Peng, Shiyu Zhao +7

Large Language Models (LLMs) have significantly enhanced Information Retrieval (IR) across various modules, such as reranking. Despite impressive performance, current zero-shot rel…

cs.CV2024

AIDE: An Automatic Data Engine for Object Detection in Autonomous Driving

Mingfu Liang, Jong-Chyi Su, Samuel Schulter +4

Autonomous vehicle (AV) systems rely on robust perception models as a cornerstone of safety assurance. However, objects encountered on the road exhibit a long-tailed distribution,…

cs.CV2024

Generating Enhanced Negatives for Training Language-Based Object Detectors

Shiyu Zhao, Long Zhao, Vijay Kumar B. G +4

The recent progress in language-based open-vocabulary object detection can be largely attributed to finding better ways of leveraging large-scale data with free-form text annotatio…