activity
20232026
most citedLoRA-Composer: Leveraging Low-Rank Adaptation for Multi-Concept Customization in Training-Free Diffusion Models

16 citations · 22 across the 16 of their papers we have counts for

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7 papers · 1 filter

cs.CV2026

LoopTrack: A Simple Baseline for Parameter-Efficient Transformer Tracking

Liang Peng, Chenxiao Li, Libo Zhang +2

Current Transformer-based tracking methods typically stack multiple Transformer blocks with separate parameters to model interactions between the target template and the search reg…

cs.CV2026

Qwen-Image-2.0-RL Technical Report

Yixian Xu, Kaiyuan Gao, Yuxiang Chen +25

We present Qwen-Image-2.0-RL, a post-training pipeline that applies reinforcement learning from human feedback (RLHF) and on-policy distillation (OPD) to improve both the visual qu…

cs.CL2026

REALISTA: Realistic Latent Adversarial Attacks that Elicit LLM Hallucinations

Buyun Liang, Jinqi Luo, Liangzu Peng +6

Large language models (LLMs) achieve strong performance across many tasks but remain vulnerable to hallucinations, making it important to systematically evaluate their reliability…

cs.CV2026

Qwen-Image-VAE-2.0 Technical Report

Zekai Zhang, Deqing Li, Kuan Cao +27

We present Qwen-Image-VAE-2.0, a suite of high-compression Variational Autoencoders (VAEs) that achieve significant advances in both reconstruction fidelity and diffusability. To a…

cs.CV2026

Qwen-Image-2.0 Technical Report

Bing Zhao, Chenfei Wu, Deqing Li +72

We present Qwen-Image-2.0, an omni-capable image generation foundation model that unifies high-fidelity generation and precise image editing within a single framework. Despite rece…

cs.CL2026

MedTextWeaver: Procedural Knowledge Evolution in Agentic Medical Text Editing

Ziyan Xiao, Yinghao Zhu, Liang Peng +2

Medical text editing is essential for improving communication among diverse stakeholders in clinical settings. However, adapting LLM agents to this task remains challenging because…

cs.AI2026

RISER: Orchestrating Latent Reasoning Skills for Adaptive Activation Steering

Wencheng Ye, Xiaoyang Yuan, Yi Bin +4

Recent work on domain-specific reasoning with large language models (LLMs) often relies on training-intensive approaches that require parameter updates. While activation steering h…