activity
20192026
most citedVision Transformer Pruning

53 citations · 93 across the 11 of their papers we have counts for

collaborators

13 papers

cs.AI2026

Reading is not Reasoning: Bridging the Agentic Policy Gap in Vision-Text Compression

Cheng Fan, Junyi Zhou, Tingzhang Luo +5

Multi-step language-model agents repeatedly process growing interaction histories, leading to substantial context costs. Vision--text compression reduces these costs by rendering h…

cs.CL2026

C-MOP: Integrating Momentum and Boundary-Aware Clustering for Enhanced Prompt Evolution

Binwei Yan, Yifei Fu, Mingjian Zhu +4

Automatic prompt optimization is a promising direction to boost the performance of Large Language Models (LLMs). However, existing methods often suffer from noisy and conflicting u…

cs.CL2025

Pangu Embedded: An Efficient Dual-system LLM Reasoner with Metacognition

Hanting Chen, Yasheng Wang, Kai Han +21

This work presents Pangu Embedded, an efficient Large Language Model (LLM) reasoner developed on Ascend Neural Processing Units (NPUs), featuring flexible fast and slow thinking ca…

cs.CL2025

Saliency-driven Dynamic Token Pruning for Large Language Models

Yao Tao, Yehui Tang, Yun Wang +3

Despite the recent success of large language models (LLMs), LLMs are particularly challenging in long-sequence inference scenarios due to the quadratic computational complexity of…

cs.CV2024

GIM: A Million-scale Benchmark for Generative Image Manipulation Detection and Localization

Yirui Chen, Xudong Huang, Quan Zhang +9

The extraordinary ability of generative models emerges as a new trend in image editing and generating realistic images, posing a serious threat to the trustworthiness of multimedia…

cs.CV2023★ 3 cited

GenDet: Towards Good Generalizations for AI-Generated Image Detection

Mingjian Zhu, Hanting Chen, Mouxiao Huang +4

The misuse of AI imagery can have harmful societal effects, prompting the creation of detectors to combat issues like the spread of fake news. Existing methods can effectively dete…