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Found 14 papers, 3 papers with code
Quantifying Bias from Decoding Techniques in Natural Language Generation
To this extent, we also analyze the trade-off between bias scores and human-annotated generation quality throughout the decoder space.
COIN: Chance-Constrained Imitation Learning for Uncertainty-aware Adaptive Resource Oversubscription Policy
We address the challenge of learning safe and robust decision policies in presence of uncertainty in context of the real scientific problem of adaptive resource oversubscription to enhance resource efficiency while ensuring safety against resource congestion risk.
Tree DNN: A Deep Container Network
TreeDNN helps in training the model with multiple datasets simultaneously, where each branch of the tree may need a different training dataset.
Human-guided Collaborative Problem Solving: A Natural Language based Framework
We consider the problem of human-machine collaborative problem solving as a planning task coupled with natural language communication.
AutoCoMet: Smart Neural Architecture Search via Co-Regulated Shaping Reinforcement
Designing suitable deep model architectures, for AI-driven on-device apps and features, at par with rapidly evolving mobile hardware and increasingly complex target scenarios is a difficult task.
NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation
Data augmentation is an important component in the robustness evaluation of models in natural language processing (NLP) and in enhancing the diversity of the data they are trained on.
Reinforcement Learning Based Asymmetrical DNN Modularization for Optimal Loading
Latency of DNN (Deep Neural Network) based prediction is the summation of model loading latency and inference latency.
User Friendly Automatic Construction of Background Knowledge: Mode Construction from ER Diagrams
One of the key advantages of Inductive Logic Programming systems is the ability of the domain experts to provide background knowledge as modes that allow for efficient search through the space of hypotheses.
One-Shot Induction of Generalized Logical Concepts via Human Guidance
First, we define a distance measure between candidate concept representations that improves the efficiency of search for target concept and generalization.
Knowledge-augmented Column Networks: Guiding Deep Learning with Advice
Recently, deep models have had considerable success in several tasks, especially with low-level representations.
Human-Guided Column Networks: Augmenting Deep Learning with Advice
While extremely successful in several applications, especially with low-level representations; sparse, noisy samples and structured domains (with multiple objects and interactions) are some of the open challenges in most deep models.
Human-Guided Learning of Column Networks: Augmenting Deep Learning with Advice
Recently, deep models have been successfully applied in several applications, especially with low-level representations.
Preference-Guided Planning: An Active Elicitation Approach
Planning with preferences has been employed extensively to quickly generate high-quality plans.
Towards Problem Solving Agents that Communicate and Learn
Agents that communicate back and forth with humans to help them execute non-linguistic tasks are a long sought goal of AI.
