Search Results for author:
Found 15 papers, 5 papers with code
Broadcasting Convolutional Network for Visual Relational Reasoning
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.
Towards Governing Agent's Efficacy: Action-Conditional $β$-VAE for Deep Transparent Reinforcement Learning
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.
Genetic-Gated Networks for Deep Reinforcement
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.
Sym-parameterized Dynamic Inference for Mixed-Domain Image Translation
Recent advances in image-to-image translation have led to some ways to generate multiple domain images through a single network.
Genetic-Gated Networks for Deep Reinforcement Learning
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.
SeqHAND:RGB-Sequence-Based 3D Hand Pose and Shape Estimation
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.
Dynamic Iterative Refinement for Efficient 3D Hand Pose Estimation
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.
Depth Estimation with Simplified Transformer
Transformer and its variants have shown state-of-the-art results in many vision tasks recently, ranging from image classification to dense prediction.
WebShop: Towards Scalable Real-World Web Interaction with Grounded Language Agents
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.
Referral Augmentation for Zero-Shot Information Retrieval
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.
Swin-Free: Achieving Better Cross-Window Attention and Efficiency with Size-varying Window
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.
InterCode: Standardizing and Benchmarking Interactive Coding with Execution Feedback
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.
SWE-bench: Can Language Models Resolve Real-World GitHub Issues?
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
DevBench: A Comprehensive Benchmark for Software Development
Recent advancements in large language models (LLMs) have significantly enhanced their coding capabilities.
SeqHAND: RGB-Sequence-Based 3D Hand Pose and Shape Estimation
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.
