2.7k citations · 3.2k across the 12 of their papers we have counts for
13 papers
"Sorry, Come Again?" Prompting -- Enhancing Comprehension and Diminishing Hallucination with [PAUSE]-injected Optimal Paraphrasing
Vipula Rawte, S. M Towhidul Islam Tonmoy, S M Mehedi Zaman +4
Hallucination has emerged as the most vulnerable aspect of contemporary Large Language Models (LLMs). In this paper, we introduce the Sorry, Come Again (SCA) prompting, aimed to av…
Towards Artwork Explanation in Large-scale Vision Language Models
Kazuki Hayashi, Yusuke Sakai, Hidetaka Kamigaito +2
Large-scale Vision-Language Models (LVLMs) output text from images and instructions, demonstrating capabilities in text generation and comprehension. However, it has not been clari…
When Benchmarks are Targets: Revealing the Sensitivity of Large Language Model Leaderboards
Norah Alzahrani, Hisham Abdullah Alyahya, Yazeed Alnumay +9
Large Language Model (LLM) leaderboards based on benchmark rankings are regularly used to guide practitioners in model selection. Often, the published leaderboard rankings are take…
Nougat: Neural Optical Understanding for Academic Documents
Lukas Blecher, Guillem Cucurull, Thomas Scialom +1
Scientific knowledge is predominantly stored in books and scientific journals, often in the form of PDFs. However, the PDF format leads to a loss of semantic information, particula…
Llama 2: Open Foundation and Fine-Tuned Chat Models
Hugo Touvron, Louis Martin, Kevin Stone +65
In this work, we develop and release Llama 2, a collection of pretrained and fine-tuned large language models (LLMs) ranging in scale from 7 billion to 70 billion parameters. Our f…
Galactica: A Large Language Model for Science
Ross Taylor, Marcin Kardas, Guillem Cucurull +6
Information overload is a major obstacle to scientific progress. The explosive growth in scientific literature and data has made it ever harder to discover useful insights in a lar…
Pay attention to the activations: a modular attention mechanism for fine-grained image recognition
Pau Rodríguez López, Diego Velazquez Dorta, Guillem Cucurull Preixens +3
Fine-grained image recognition is central to many multimedia tasks such as search, retrieval and captioning. Unfortunately, these tasks are still challenging since the appearance o…
Context-Aware Visual Compatibility Prediction
Guillem Cucurull, Perouz Taslakian, David Vazquez
How do we determine whether two or more clothing items are compatible or visually appealing? Part of the answer lies in understanding of visual aesthetics, and is biased by persona…
Attend and Rectify: a Gated Attention Mechanism for Fine-Grained Recovery
Pau Rodríguez, Josep M. Gonfaus, Guillem Cucurull +2
We propose a novel attention mechanism to enhance Convolutional Neural Networks for fine-grained recognition. It learns to attend to lower-level feature activations without requiri…
On the iterative refinement of densely connected representation levels for semantic segmentation
Arantxa Casanova, Guillem Cucurull, Michal Drozdzal +2
State-of-the-art semantic segmentation approaches increase the receptive field of their models by using either a downsampling path composed of poolings/strided convolutions or succ…
Deep Inference of Personality Traits by Integrating Image and Word Use in Social Networks
Guillem Cucurull, Pau Rodríguez, V. Oguz Yazici +3
Social media, as a major platform for communication and information exchange, is a rich repository of the opinions and sentiments of 2.3 billion users about a vast spectrum of topi…
Graph Attention Networks
Petar Veličković, Guillem Cucurull, Arantxa Casanova +3
We present graph attention networks (GATs), novel neural network architectures that operate on graph-structured data, leveraging masked self-attentional layers to address the short…
Regularizing CNNs with Locally Constrained Decorrelations
Pau Rodríguez, Jordi Gonzàlez, Guillem Cucurull +2
Regularization is key for deep learning since it allows training more complex models while keeping lower levels of overfitting. However, the most prevalent regularizations do not l…