no code implementations • ECCV 2020 • John Yang, Hyung Jin Chang, Seungeui Lee, Nojun Kwak
In this paper, we attempt to not only consider the appearance of a hand but incorporate the temporal movement information of a hand in motion into the learning framework for better 3D hand pose estimation performance, which leads to the necessity of a large scale dataset with sequential RGB hand images.
1 code implementation • 13 Mar 2024 • Bowen Li, Wenhan Wu, Ziwei Tang, Lin Shi, John Yang, Jinyang Li, Shunyu Yao, Chen Qian, Binyuan Hui, Qicheng Zhang, Zhiyin Yu, He Du, Ping Yang, Dahua Lin, Chao Peng, Kai Chen
Recent advancements in large language models (LLMs) have significantly enhanced their coding capabilities.
no code implementations • 10 Oct 2023 • Carlos E. Jimenez, John Yang, Alexander Wettig, Shunyu Yao, Kexin Pei, Ofir Press, Karthik Narasimhan
We find real-world software engineering to be a rich, sustainable, and challenging testbed for evaluating the next generation of language models.
Ranked #2 on Bug fixing on SWE-bench
2 code implementations • NeurIPS 2023 • John Yang, Akshara Prabhakar, Karthik Narasimhan, Shunyu Yao
Our framework is language and platform agnostic, uses self-contained Docker environments to provide safe and reproducible execution, and is compatible out-of-the-box with traditional seq2seq coding methods, while enabling the development of new methods for interactive code generation.
no code implementations • 23 Jun 2023 • Jinkyu Koo, John Yang, Le An, Gwenaelle Cunha Sergio, Su Inn Park
To mitigate this issue, we propose Swin-Free in which we apply size-varying windows across stages, instead of shifting windows, to achieve cross-connection among local windows.
1 code implementation • 24 May 2023 • Michael Tang, Shunyu Yao, John Yang, Karthik Narasimhan
We propose Referral-Augmented Retrieval (RAR), a simple technique that concatenates document indices with referrals, i. e. text from other documents that cite or link to the given document, to provide significant performance gains for zero-shot information retrieval.
1 code implementation • 4 Jul 2022 • Shunyu Yao, Howard Chen, John Yang, Karthik Narasimhan
Existing benchmarks for grounding language in interactive environments either lack real-world linguistic elements, or prove difficult to scale up due to substantial human involvement in the collection of data or feedback signals.
no code implementations • 28 Apr 2022 • John Yang, Le An, Anurag Dixit, Jinkyu Koo, Su Inn Park
Transformer and its variants have shown state-of-the-art results in many vision tasks recently, ranging from image classification to dense prediction.
no code implementations • 11 Nov 2021 • John Yang, Yash Bhalgat, Simyung Chang, Fatih Porikli, Nojun Kwak
While hand pose estimation is a critical component of most interactive extended reality and gesture recognition systems, contemporary approaches are not optimized for computational and memory efficiency.
no code implementations • 10 Jul 2020 • John Yang, Hyung Jin Chang, Seungeui Lee, Nojun Kwak
In this paper, we attempt to not only consider the appearance of a hand but incorporate the temporal movement information of a hand in motion into the learning framework for better 3D hand pose estimation performance, which leads to the necessity of a large scale dataset with sequential RGB hand images.
no code implementations • NeurIPS 2018 • Simyung Chang, John Yang, Jaeseok Choi, Nojun Kwak
We introduce the Genetic-Gated Networks (G2Ns), simple neural networks that combine a gate vector composed of binary genetic genes in the hidden layer(s) of networks.
1 code implementation • ICCV 2019 • Simyung Chang, SeongUk Park, John Yang, Nojun Kwak
Recent advances in image-to-image translation have led to some ways to generate multiple domain images through a single network.
no code implementations • 26 Nov 2018 • Simyung Chang, John Yang, Jae-Seok Choi, Nojun Kwak
We introduce the Genetic-Gated Networks (G2Ns), simple neural networks that combine a gate vector composed of binary genetic genes in the hidden layer(s) of networks.
no code implementations • 11 Nov 2018 • John Yang, Gyujeong Lee, Minsung Hyun, Simyung Chang, Nojun Kwak
We tackle the blackbox issue of deep neural networks in the settings of reinforcement learning (RL) where neural agents learn towards maximizing reward gains in an uncontrollable way.
no code implementations • ECCV 2018 • Simyung Chang, John Yang, SeongUk Park, Nojun Kwak
In this paper, we propose the Broadcasting Convolutional Network (BCN) that extracts key object features from the global field of an entire input image and recognizes their relationship with local features.