Papers
MAGIC: Mastering Physical Adversarial Generation in Context Through Collaborative LLM Agents
Yun Xing, Nhat Chung, Jie Zhang et al.
MAGIC: Multi-Agent Argumentation and Grammar Integrated Critiquer
Joaquín Jordán, Xavier Yin, Melissa Fabros et al.
MagicPaint: Operate Anything for Image Inpainting with Diffusion Model
Qinhong Yang, Dongdong Chen, Qi Chu et al.
MAGIC VFM-Meta-Learning Adaptation for Ground Interaction Control with Visual Foundation Models (Abstract Reprint)
Elena-Sorina Lupu, Fengze Xie, James Preiss et al.
MAGMA: A Multi-Graph based Agentic Memory Architecture for AI Agents
Dongming Jiang, Yi Li, Guanpeng Li et al.
MAGNET: Towards Adaptive GUI Agents with Memory-Driven Knowledge Evolution
Libo Sun, Jiwen Zhang, Siyuan Wang et al.
Magnitude-Modulated Equivariant Adapter for Parameter-Efficient Fine-Tuning of Equivariant Graph Neural Networks
Dian Jin, Yancheng Yuan, Xiaoming Tao
Magnol.AI Copilot: Multimodal LLMs for Conversational Insight Generation
Hui Zhang, Guangchen Ruan, Hui Xiao
MaiBERT: A Pre-training Corpus and Language Model for Low-Resourced Maithili Language
Sumit Yadav, Raju Kumar Yadav, Utsav Maskey et al.
MAISI-v2: Accelerated 3D High-Resolution Medical Image Synthesis with Rectified Flow and Region-specific Contrastive Loss
Can Zhao, Pengfei Guo, Dong Yang et al.
MAJIC: Markovian Adaptive Jailbreaking via Iterative Composition of Diverse Innovative Strategies
Weiwei Qi, Shuo Shao, Wei Gu et al.
Make Foundation Models Trustworthy Again: Causal Fine-Adaptation for Medical Image Segmentation
Hongpeng Yang, Yingxin Chen, Shiqiang Ma et al.
Make LLMs See Like Investigators, Not Just Think More: The Role of Structured Analysis in Investigative Reasoning
Jaewook Lee, Myeong-Cheol Kang, Jong-hun Shin
Make LVLMs Focus: Context-Aware Attention Modulation for Better Multimodal In-Context Learning
Yanshu Li, Jianjiang Yang, Ziteng Yang et al.
Make Mechanistic Interpretability Auditable: A Call to Develop Guidelines via Continuous Collaborative Reviewing
Michael Lan, Narmeen Fatimah Oozeer, Chaithanya Bandi et al.
Make Model Transparent: Brain Network Analysis via Causal and Knowledge Graph Learning
Lingyuan Meng, Ke Liang, Hao Yu et al.
Makespan Investigations of Sequential, Parallel, PO, and POCL Plans
Harrison Oates, Pascal Bercher
Making Every Head Count: Sparse Attention Without the Speed-Performance Trade-off
Mingkuan Zhao, Wentao Hu, Jiayin Wang et al.
Making Large Language Models Efficient Dense Retrievers
Yibin Lei, Shwai He, Ang Li et al.
Making Large Language Models Speak Tulu: Structured Prompting for an Extremely Low-Resource Language
Prathamesh Devadiga, Paras Chopra
Making Sense of LLM Decisions: A Prototype-based Framework for Explainable Classification
Bowen Wei, Mehrdad Fazli, Ziwei Zhu
Making Visual Dialogue More Engaging: A New Task, Method, and Metric
Guanghui Ye, Huan Zhao, Yingxue Gao et al.
MALicious INTent Dataset and Inoculating LLMs for Enhanced Disinformation Detection
Arkadiusz Modzelewski, Witold Sosnowski, Eleni Papadopulos et al.
MalruleLib: Large-Scale Executable Misconception Reasoning with Step Traces for Modeling Student Thinking in Mathematics
Xinghe Chen, Naiming Liu, Shashank Sonkar
MAMA-Memeia! Multi-Aspect Multi-Agent Collaboration for Depressive Symptoms Identification in Memes
Siddhant Agarwal, Adya Dhuler, Polly Ruhnke et al.