NeurIPS 2022 Paper "VLMbench: A Compositional Benchmark for Vision-and-Language Manipulation" - eric-ai-lab/VLMbench
Implementation for ECCV 2022 paper Language-Grounded Indoor 3D Semantic Segmentation in the Wild - GitHub - RozDavid/LanguageGroundedSemseg: Implementation for ECCV 2022 paper Language-Grounded Indoor 3D Semantic Segmentation in the Wild
In this paper, the OpenAI team demonstrates that pre-trained language models can be used to solve downstream tasks without any parameter or architecture modifications. They have trained a very big model, a 1.5B-parameter Transformer, on a large and diverse dataset that contains text scraped from ...
This paper aims to explore the field of sports biomechanics in China between 1980 and 2022 in terms of key developments, hot research topics, integration with other disciplines in kinesiology, and future trends by using text mining and natural language processing to analyze abstracts ...
Full Paper: You can publish the manuscript and deliver presentation on ICLMC 2022. Please submit Full-length Manuscript for review before the submission deadline. Abstract: You can deliver a presentation on ICLMC 2022, but the presented manuscript WILL NOT be published. Abstract is necessary to ...
Radford, A., Narasimhan, K., Salimans, T. & Sutskever, I. Improving language understanding by generative pre-training (2018).https://cdn.openai.com/research-covers/language-unsupervised/language_understanding_paper.pdf,. De Angelis, L. et al. ChatGPT and the rise of large language models:...
In this paper, we describe our proposed method for the SemEval 2022 Task 11: Multilingual Complex Named Entity Recognition (MultiCoNER). The goal of this task is to locate and classify named entities in unstructured short complex texts in 11 different languages.After training a variety of contex...
adding explicit visual segmentation may induce better discrimination for certain fashion concepts. While more costly losses are an interesting area at the intersection of grounding and compositionality, given both the narrow generative focus and the magnitude of the improvements in the original paper33, ...
As the capabilities of large language models continue to develop rapidly, future versions of the models examined in this paper may be able to obtain better scores in cognitive and visuospatial tests. However, we believe that our study has shed light on some key differences between human and ...
This is the official PyTorch implementation of the paper: Language Model Pre-Training with Sparse Latent Typing. Liliang Ren*, Zixuan Zhang*, Han Wang, Clare R. Voss, Chengxiang Zhai, Heng Ji. (*Equal Contribution) EMNLP 2022 (Oral) [pdf] [slides] Overview The figure shows the general ar...