research
∙
08/28/2023
MEMORY-VQ: Compression for Tractable Internet-Scale Memory
Retrieval augmentation is a powerful but expensive method to make langua...
share
research
∙
12/21/2022
ImPaKT: A Dataset for Open-Schema Knowledge Base Construction
Large language models have ushered in a golden age of semantic parsing. ...
research
∙
10/18/2022
Arithmetic Sampling: Parallel Diverse Decoding for Large Language Models
Decoding methods for large language models often trade-off between diver...
research
∙
10/09/2020
Improving Local Identifiability in Probabilistic Box Embeddings
Geometric embeddings have recently received attention for their natural ...
research
∙
09/28/2018
Embedded-State Latent Conditional Random Fields for Sequence Labeling
Complex textual information extraction tasks are often posed as sequence...
research
∙
07/13/2018
Hierarchical Losses and New Resources for Fine-grained Entity Typing and Linking
Extraction from raw text to a knowledge base of entities and fine-graine...
research
∙
05/17/2018
Probabilistic Embedding of Knowledge Graphs with Box Lattice Measures
Embedding methods which enforce a partial order or lattice structure ove...
research
∙
11/15/2017
Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases using Reinforcement Learning
Knowledge bases (KB), both automatically and manually constructed, are o...
research
∙
11/15/2017
Finer Grained Entity Typing with TypeNet
We consider the challenging problem of entity typing over an extremely f...
research
∙
10/02/2017
Unsupervised Hypernym Detection by Distributional Inclusion Vector Embedding
Modeling hypernymy, such as poodle is-a dog, is an important generalizat...
research
∙
08/02/2017
Low-Rank Hidden State Embeddings for Viterbi Sequence Labeling
In textual information extraction and other sequence labeling tasks it i...
research
∙
08/01/2017
Improved Representation Learning for Predicting Commonsense Ontologies
Recent work in learning ontologies (hierarchical and partially-ordered s...
research
∙
11/21/2015
Adding Gradient Noise Improves Learning for Very Deep Networks
Deep feedforward and recurrent networks have achieved impressive results...
research
∙
11/19/2015
Generating Sentences from a Continuous Space
The standard recurrent neural network language model (RNNLM) generates s...
research
∙
03/04/2015
Bethe Projections for Non-Local Inference
Many inference problems in structured prediction are naturally solved by...
research
∙
12/20/2014
Word Representations via Gaussian Embedding
Current work in lexical distributed representations maps each word to a ...
research
∙
10/30/2014