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07/13/2023
Generating Benchmarks for Factuality Evaluation of Language Models
Before deploying a language model (LM) within a given domain, it is impo...
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05/31/2023
Human or Not? A Gamified Approach to the Turing Test
We present "Human or Not?", an online game inspired by the Turing test, ...
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04/19/2023
Fundamental Limitations of Alignment in Large Language Models
An important aspect in developing language models that interact with hum...
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03/14/2023
The Learnability of In-Context Learning
In-context learning is a surprising and important phenomenon that emerge...
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01/31/2023
In-Context Retrieval-Augmented Language Models
Retrieval-Augmented Language Modeling (RALM) methods, that condition a l...
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12/21/2022
Parallel Context Windows Improve In-Context Learning of Large Language Models
For applications that require processing large amounts of text at infere...
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05/01/2022
MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning
Huge language models (LMs) have ushered in a new era for AI, serving as ...
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04/06/2022
Sub-Task Decomposition Enables Learning in Sequence to Sequence Tasks
The field of Natural Language Processing (NLP) has experienced a dramati...
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10/09/2021
The Inductive Bias of In-Context Learning: Rethinking Pretraining Example Design
Pretraining Neural Language Models (NLMs) over a large corpus involves c...
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05/09/2021
Which transformer architecture fits my data? A vocabulary bottleneck in self-attention
After their successful debut in natural language processing, Transformer...
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10/05/2020
PMI-Masking: Principled masking of correlated spans
Masking tokens uniformly at random constitutes a common flaw in the pret...
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06/22/2020
Limits to Depth Efficiencies of Self-Attention
Self-attention architectures, which are rapidly pushing the frontier in ...
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08/15/2019
SenseBERT: Driving Some Sense into BERT
Self-supervision techniques have allowed neural language models to advan...
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02/11/2019
Deep autoregressive models for the efficient variational simulation of many-body quantum systems
Artificial Neural Networks were recently shown to be an efficient repres...
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03/26/2018
Bridging Many-Body Quantum Physics and Deep Learning via Tensor Networks
The harnessing of modern computational abilities for many-body wave-func...
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10/25/2017
Benefits of Depth for Long-Term Memory of Recurrent Networks
The key attribute that drives the unprecedented success of modern Recurr...
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05/05/2017
Analysis and Design of Convolutional Networks via Hierarchical Tensor Decompositions
The driving force behind convolutional networks - the most successful de...
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04/05/2017