William W. Cohen

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Google ∙ Carnegie Mellon University

Professor, Machine Learning Department and Language Technology Institute, Director of the Undergraduate Minor in Machine Learning and Co-Director of the Master of Science in Machine Learning program

Reasoning Over Virtual Knowledge Bases With Open Predicate Relations

We present the Open Predicate Query Language (OPQL); a method for constr...
02/14/2021 ∙ by Haitian Sun, et al. ∙ 0 ∙ share

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Evaluating Explanations: How much do explanations from the teacher aid students?

While many methods purport to explain predictions by highlighting salien...
12/01/2020 ∙ by Danish Pruthi, et al. ∙ 8 ∙ share

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Open Question Answering over Tables and Text

In open question answering (QA), the answer to a question is produced by...
10/20/2020 ∙ by Wenhu Chen, et al. ∙ 0 ∙ share

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Facts as Experts: Adaptable and Interpretable Neural Memory over Symbolic Knowledge

Massive language models are the core of modern NLP modeling and have bee...
07/02/2020 ∙ by Pat Verga, et al. ∙ 0 ∙ share

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Guessing What's Plausible But Remembering What's True: Accurate Neural Reasoning for Question-Answering

Neural approaches to natural language processing (NLP) often fail at the...
04/07/2020 ∙ by Haitian Sun, et al. ∙ 7 ∙ share

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Differentiable Reasoning over a Virtual Knowledge Base

We consider the task of answering complex multi-hop questions using a co...
02/25/2020 ∙ by Bhuwan Dhingra, et al. ∙ 0 ∙ share

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Scalable Neural Methods for Reasoning With a Symbolic Knowledge Base

We describe a novel way of representing a symbolic knowledge base (KB) c...
02/14/2020 ∙ by William W. Cohen, et al. ∙ 0 ∙ share

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Game Design for Eliciting Distinguishable Behavior

The ability to inferring latent psychological traits from human behavior...
12/12/2019 ∙ by Fan Yang, et al. ∙ 6 ∙ share

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Instance-based Transfer Learning for Multilingual Deep Retrieval

Perhaps the simplest type of multilingual transfer learning is instance-...
11/08/2019 ∙ by Andrew O. Arnold, et al. ∙ 0 ∙ share

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PubMedQA: A Dataset for Biomedical Research Question Answering

We introduce PubMedQA, a novel biomedical question answering (QA) datase...
09/13/2019 ∙ by Qiao Jin, et al. ∙ 0 ∙ share

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Handling Divergent Reference Texts when Evaluating Table-to-Text Generation

Automatically constructed datasets for generating text from semi-structu...
06/03/2019 ∙ by Bhuwan Dhingra, et al. ∙ 0 ∙ share

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Differentiable Representations For Multihop Inference Rules

We present efficient differentiable implementations of second-order mult...
05/24/2019 ∙ by William W. Cohen, et al. ∙ 0 ∙ share

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Neural Query Language: A Knowledge Base Query Language for Tensorflow

Large knowledge bases (KBs) are useful for many AI tasks, but are diffic...
05/15/2019 ∙ by William W. Cohen, et al. ∙ 0 ∙ share

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PullNet: Open Domain Question Answering with Iterative Retrieval on Knowledge Bases and Text

We consider open-domain queston answering (QA) where answers are drawn f...
04/21/2019 ∙ by Haitian Sun, et al. ∙ 0 ∙ share

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Probing Biomedical Embeddings from Language Models

Contextualized word embeddings derived from pre-trained language models ...
04/03/2019 ∙ by Qiao Jin, et al. ∙ 0 ∙ share

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Incremental Reading for Question Answering

Any system which performs goal-directed continual learning must not only...
01/15/2019 ∙ by Samira Abnar, et al. ∙ 0 ∙ share

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Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context

Transformer networks have a potential of learning longer-term dependency...
01/09/2019 ∙ by Zihang Dai, et al. ∙ 2 ∙ share

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HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering

Existing question answering (QA) datasets fail to train QA systems to pe...
09/25/2018 ∙ by Zhilin Yang, et al. ∙ 0 ∙ share

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Open Domain Question Answering Using Early Fusion of Knowledge Bases and Text

Open Domain Question Answering (QA) is evolving from complex pipelined s...
09/04/2018 ∙ by Haitian Sun, et al. ∙ 0 ∙ share

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GLoMo: Unsupervisedly Learned Relational Graphs as Transferable Representations

Modern deep transfer learning approaches have mainly focused on learning...
06/14/2018 ∙ by Zhilin Yang, et al. ∙ 0 ∙ share

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Semi-Supervised Learning with Declaratively Specified Entropy Constraints

We propose a technique for declaratively specifying strategies for semi-...
04/24/2018 ∙ by Haitian Sun, et al. ∙ 0 ∙ share

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Neural Models for Reasoning over Multiple Mentions using Coreference

Many problems in NLP require aggregating information from multiple menti...
04/16/2018 ∙ by Bhuwan Dhingra, et al. ∙ 0 ∙ share

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Learning to Organize Knowledge with N-Gram Machines

Deep neural networks (DNNs) had great success on NLP tasks such as langu...
11/17/2017 ∙ by Fan Yang, et al. ∙ 0 ∙ share

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Breaking the Softmax Bottleneck: A High-Rank RNN Language Model

We formulate language modeling as a matrix factorization problem, and sh...
11/10/2017 ∙ by Zhilin Yang, et al. ∙ 0 ∙ share

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TensorLog: Deep Learning Meets Probabilistic DBs

We present an implementation of a probabilistic first-order logic called...
07/17/2017 ∙ by William W. Cohen, et al. ∙ 0 ∙ share

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Quasar: Datasets for Question Answering by Search and Reading

We present two new large-scale datasets aimed at evaluating systems desi...
07/12/2017 ∙ by Bhuwan Dhingra, et al. ∙ 0 ∙ share

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Good Semi-supervised Learning that Requires a Bad GAN

Semi-supervised learning methods based on generative adversarial network...
05/27/2017 ∙ by Zihang Dai, et al. ∙ 0 ∙ share

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Transfer Learning for Sequence Tagging with Hierarchical Recurrent Networks

Recent papers have shown that neural networks obtain state-of-the-art pe...
03/18/2017 ∙ by Zhilin Yang, et al. ∙ 0 ∙ share

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Linguistic Knowledge as Memory for Recurrent Neural Networks

Training recurrent neural networks to model long term dependencies is di...
03/07/2017 ∙ by Bhuwan Dhingra, et al. ∙ 0 ∙ share

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Using Graphs of Classifiers to Impose Declarative Constraints on Semi-supervised Learning

We propose a general approach to modeling semi-supervised learning (SSL)...
03/05/2017 ∙ by Lidong Bing, et al. ∙ 0 ∙ share

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A Comparative Study of Word Embeddings for Reading Comprehension

The focus of past machine learning research for Reading Comprehension ta...
03/02/2017 ∙ by Bhuwan Dhingra, et al. ∙ 0 ∙ share

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Differentiable Learning of Logical Rules for Knowledge Base Reasoning

We study the problem of learning probabilistic first-order logical rules...
02/27/2017 ∙ by Fan Yang, et al. ∙ 0 ∙ share

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Semi-Supervised QA with Generative Domain-Adaptive Nets

We study the problem of semi-supervised question answering----utilizing ...
02/07/2017 ∙ by Zhilin Yang, et al. ∙ 0 ∙ share

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Words or Characters? Fine-grained Gating for Reading Comprehension

Previous work combines word-level and character-level representations us...
11/06/2016 ∙ by Zhilin Yang, et al. ∙ 0 ∙ share

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Bootstrapping Distantly Supervised IE using Joint Learning and Small Well-structured Corpora

We propose a framework to improve performance of distantly-supervised re...
06/10/2016 ∙ by Lidong Bing, et al. ∙ 0 ∙ share

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Gated-Attention Readers for Text Comprehension

In this paper we study the problem of answering cloze-style questions ov...
06/05/2016 ∙ by Bhuwan Dhingra, et al. ∙ 0 ∙ share

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Review Networks for Caption Generation

We propose a novel extension of the encoder-decoder framework, called a ...
05/25/2016 ∙ by Zhilin Yang, et al. ∙ 0 ∙ share

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Tweet2Vec: Character-Based Distributed Representations for Social Media

Text from social media provides a set of challenges that can cause tradi...
05/11/2016 ∙ by Bhuwan Dhingra, et al. ∙ 0 ∙ share

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Semantic Scan: Detecting Subtle, Spatially Localized Events in Text Streams

Early detection and precise characterization of emerging topics in text ...
02/13/2016 ∙ by Abhinav Maurya, et al. ∙ 0 ∙ share

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Distant IE by Bootstrapping Using Lists and Document Structure

Distant labeling for information extraction (IE) suffers from noisy trai...
01/04/2016 ∙ by Lidong Bing, et al. ∙ 0 ∙ share

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Grounded Discovery of Coordinate Term Relationships between Software Entities

We present an approach for the detection of coordinate-term relationship...
05/01/2015 ∙ by Dana Movshovitz-Attias, et al. ∙ 0 ∙ share

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Efficient Inference and Learning in a Large Knowledge Base: Reasoning with Extracted Information using a Locally Groundable First-Order Probabilistic Logic

One important challenge for probabilistic logics is reasoning with very ...
04/12/2014 ∙ by William Yang Wang, et al. ∙ 0 ∙ share

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The Effect of Biased Communications On Both Trusting and Suspicious Voters

In recent studies of political decision-making, apparently anomalous beh...
06/11/2013 ∙ by William W. Cohen, et al. ∙ 0 ∙ share

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Programming with Personalized PageRank: A Locally Groundable First-Order Probabilistic Logic

In many probabilistic first-order representation systems, inference is p...
05/10/2013 ∙ by William Yang Wang, et al. ∙ 0 ∙ share

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William W. Cohen

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