146 citations · 241 across the 21 of their papers we have counts for
7 papers · 1 filter
StreamAdapter: Efficient Test Time Adaptation from Contextual Streams
Dilxat Muhtar, Yelong Shen, Yaming Yang +11
In-context learning (ICL) allows large language models (LLMs) to adapt to new tasks directly from the given demonstrations without requiring gradient updates. While recent advances…
Windows Agent Arena: Evaluating Multi-Modal OS Agents at Scale
Rogerio Bonatti, Dan Zhao, Francesco Bonacci +9
Large language models (LLMs) show remarkable potential to act as computer agents, enhancing human productivity and software accessibility in multi-modal tasks that require planning…
Boosting Open-Domain Continual Learning via Leveraging Intra-domain Category-aware Prototype
Yadong Lu, Shitian Zhao, Boxiang Yun +4
Despite recent progress in enhancing the efficacy of Open-Domain Continual Learning (ODCL) in Vision-Language Models (VLM), failing to (1) correctly identify the Task-ID of a test…
OmniParser for Pure Vision Based GUI Agent
Yadong Lu, Jianwei Yang, Yelong Shen +1
The recent success of large vision language models shows great potential in driving the agent system operating on user interfaces. However, we argue that the power multimodal model…
AgentInstruct: Toward Generative Teaching with Agentic Flows
Arindam Mitra, Luciano Del Corro, Guoqing Zheng +11
Synthetic data is becoming increasingly important for accelerating the development of language models, both large and small. Despite several successful use cases, researchers also…
Samba: Simple Hybrid State Space Models for Efficient Unlimited Context Language Modeling
Liliang Ren, Yang Liu, Yadong Lu +3
Efficiently modeling sequences with infinite context length has long been a challenging problem. Previous approaches have either suffered from quadratic computational complexity or…
Multi-LoRA Composition for Image Generation
Ming Zhong, Yelong Shen, Shuohang Wang +6
Low-Rank Adaptation (LoRA) is extensively utilized in text-to-image models for the accurate rendition of specific elements like distinct characters or unique styles in generated im…