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Judging LLM-as-a-judge with MT-Bench and Chatbot Arena
Neural Information Processing Systems, 2023Evaluating large language model (LLM) based chat assistants is challenging due to their broad capabilities and the inadequacy of existing benchmarks in measuring human preferences. To address this, we explore using strong LLMs as judges to evaluate these
Lianmin Zheng +12 more
semanticscholar +1 more source
IEEE International Conference on Computer Vision, 2023
We introduce the Segment Anything (SA) project: a new task, model, and dataset for image segmentation. Using our efficient model in a data collection loop, we built the largest segmentation dataset to date (by far), with over 1 billion masks on 11M ...
A. Kirillov +11 more
semanticscholar +1 more source
We introduce the Segment Anything (SA) project: a new task, model, and dataset for image segmentation. Using our efficient model in a data collection loop, we built the largest segmentation dataset to date (by far), with over 1 billion masks on 11M ...
A. Kirillov +11 more
semanticscholar +1 more source
Large Language Models are Zero-Shot Reasoners
Neural Information Processing Systems, 2022Pretrained large language models (LLMs) are widely used in many sub-fields of natural language processing (NLP) and generally known as excellent few-shot learners with task-specific exemplars. Notably, chain of thought (CoT) prompting, a recent technique
Takeshi Kojima +4 more
semanticscholar +1 more source
Computer Vision and Pattern Recognition, 2022
The “Roaring 20s” of visual recognition began with the introduction of Vision Transformers (ViTs), which quickly superseded ConvNets as the state-of-the-art image classification model.
Zhuang Liu +5 more
semanticscholar +1 more source
The “Roaring 20s” of visual recognition began with the introduction of Vision Transformers (ViTs), which quickly superseded ConvNets as the state-of-the-art image classification model.
Zhuang Liu +5 more
semanticscholar +1 more source
Flamingo: a Visual Language Model for Few-Shot Learning
Neural Information Processing Systems, 2022Building models that can be rapidly adapted to novel tasks using only a handful of annotated examples is an open challenge for multimodal machine learning research. We introduce Flamingo, a family of Visual Language Models (VLM) with this ability.
Jean-Baptiste Alayrac +26 more
semanticscholar +1 more source
DeepSeek-R1 incentivizes reasoning in LLMs through reinforcement learning
NatureGeneral reasoning represents a long-standing and formidable challenge in artificial intelligence (AI). Recent breakthroughs, exemplified by large language models (LLMs)1,2 and chain-of-thought (CoT) prompting3, have achieved considerable success on ...
DeepSeek-AI +197 more
semanticscholar +1 more source
Integrative oncology: Addressing the global challenges of cancer prevention and treatment
Ca-A Cancer Journal for Clinicians, 2022Jun J Mao,, Msce +2 more
exaly
Multidisciplinary standards of care and recent progress in pancreatic ductal adenocarcinoma
Ca-A Cancer Journal for Clinicians, 2020Aaron J Grossberg +2 more
exaly
Oral complications of cancer and cancer therapy
Ca-A Cancer Journal for Clinicians, 2012Joel B Epstein +2 more
exaly