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Found 9 papers, 4 papers with code
Command A: An Enterprise-Ready Large Language Model
In this report we describe the development of Command A, a powerful large language model purpose-built to excel at real-world enterprise use cases.
Multi-Turn Code Generation Through Single-Step Rewards
We provide analysis of the design choices of the reward models and policy, and show the efficacy of $\mu$Code at utilizing the execution feedback.
Non-Adversarial Inverse Reinforcement Learning via Successor Feature Matching
In inverse reinforcement learning (IRL), an agent seeks to replicate expert demonstrations through interactions with the environment.
Learning Robust Dynamics through Variational Sparse Gating
Learning world models from their sensory inputs enables agents to plan for actions by imagining their future outcomes.
GalaXC: Graph Neural Networks with Labelwise Attention for Extreme Classification
An efficient end-to-end implementation of GalaXC is presented that could be trained on a dataset with 50M labels and 97M training documents in less than 100 hours on 4×V100 GPUs.
Predicting Regional Locust Swarm Distribution with Recurrent Neural Networks
Locust infestation of some regions in the world, including Africa, Asia and Middle East has become a concerning issue that can affect the health and the lives of millions of people.
The Angel is in the Priors: Improving GAN based Image and Sequence Inpainting with Better Noise and Structural Priors
To our knowledge, this is the first demonstration of an unsupervised GAN based sequence inpainting.
Faster Unsupervised Semantic Inpainting: A GAN Based Approach
In this paper, we propose to improve the inference speed and visual quality of contemporary baseline of Generative Adversarial Networks (GAN) based unsupervised semantic inpainting.
Recurrent Memory Addressing for describing videos
In this paper, we introduce Key-Value Memory Networks to a multimodal setting and a novel key-addressing mechanism to deal with sequence-to-sequence models.
