Can supervised and self-ensembled in-context learning improve task performance and model calibration?

Original title: On Task Performance and Model Calibration with Supervised and Self-Ensembled In-Context Learning Authors: Chengzu Li, Han Zhou, Goran Glavaš, Anna Korhonen, Ivan Vulić In this article, the authors explore the issue of overconfidence…

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Can Multi-Level Contrastive Learning Improve Natural Language Explanation in VQA?

Original title: Towards More Faithful Natural Language Explanation Using Multi-Level Contrastive Learning in VQA Authors: Chengen Lai, Shengli Song, Shiqi Meng, Jingyang Li, Sitong Yan, Guangneng Hu In an article about natural language explanation in…

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Can Mini-GPTs be Efficient Large Language Models using Contextual Pruning?

Original title: Mini-GPTs: Efficient Large Language Models through Contextual Pruning Authors: Tim Valicenti, Justice Vidal, Ritik Patnaik This article explores the optimization of Large Language Models (LLMs) in the field of artificial intelligence (AI). It…

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What is sequential survival process in continuous-time graph representation?

Original title: Continuous-time Graph Representation with Sequential Survival Process Authors: Abdulkadir Celikkanat, Nikolaos Nakis, Morten Mørup The article discusses the growth of representation learning methods for graphs over the past two decades. These methods have…

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Can pre-trained image backbones be unlocked for semantic image synthesis?

Original title: Unlocking Pre-trained Image Backbones for Semantic Image Synthesis Authors: Tariq Berrada, Jakob Verbeek, Camille Couprie, Karteek Alahari In the article, the authors discuss the task of semantic image synthesis, which involves generating images…

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Can PIA create personalized images using plug-and-play modules in text-to-image models?

Original title: PIA: Your Personalized Image Animator via Plug-and-Play Modules in Text-to-Image Models Authors: Yiming Zhang, Zhening Xing, Yanhong Zeng, Youqing Fang, Kai Chen In a recent article, researchers have made exciting advancements in personalized…

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