b'Li Deng'

research

∙ 08/07/2023

Trusting Language Models in Education

Language Models are being widely used in Education. Even though modern d...

0 Jogi Suda Neto, et al. ∙

research

∙ 07/12/2022

OSLAT: Open Set Label Attention Transformer for Medical Entity Span Extraction

Identifying spans in medical texts that correspond to medical entities i...

38 Raymond Li, et al. ∙

research

∙ 11/17/2021

MEDCOD: A Medically-Accurate, Emotive, Diverse, and Controllable Dialog System

We present MEDCOD, a Medically-Accurate, Emotive, Diverse, and Controlla...

8 Rhys Compton, et al. ∙

research

∙ 12/19/2020

Perturbed Adaptive Belief Propagation Decoding for High-Density Parity-Check Codes

Algebraic codes such as BCH code are receiving renewed interest as their...

0 Li Deng, et al. ∙

research

∙ 11/10/2019

Multimodal Intelligence: Representation Learning, Information Fusion, and Applications

Deep learning has revolutionized speech recognition, image recognition, ...

9 Chao Zhang, et al. ∙

research

∙ 06/06/2019

From Caesar Cipher to Unsupervised Learning: A New Method for Classifier Parameter Estimation

Many important classification problems, such as object classification, s...

3 Yu Liu, et al. ∙

research

∙ 05/31/2019

Table2Vec: Neural Word and Entity Embeddings for Table Population and Retrieval

Tables contain valuable knowledge in a structured form. We employ neural...

0 Li Deng, et al. ∙

research

∙ 02/20/2018

Attentive Tensor Product Learning for Language Generation and Grammar Parsing

This paper proposes a new architecture - Attentive Tensor Product Learni...

0 Qiuyuan Huang, et al. ∙

research

∙ 11/15/2017

BBQ-Networks: Efficient Exploration in Deep Reinforcement Learning for Task-Oriented Dialogue Systems

We present a new algorithm that significantly improves the efficiency of...

0 Zachary Lipton, et al. ∙

research

∙ 10/29/2017

A Neural-Symbolic Approach to Natural Language Tasks

Deep learning (DL) has in recent years been widely used in natural langu...

0 Qiuyuan Huang, et al. ∙

research

∙ 09/26/2017

Tensor Product Generation Networks for Deep NLP Modeling

We present a new approach to the design of deep networks for natural lan...

0 Qiuyuan Huang, et al. ∙

research

∙ 09/26/2017

Tensor Product Generation Networks

We present a new tensor product generation network (TPGN) that generates...

0 Qiuyuan Huang, et al. ∙

research

∙ 06/29/2017

Two-Stage Synthesis Networks for Transfer Learning in Machine Comprehension

We develop a technique for transfer learning in machine comprehension (M...

0 David Golub, et al. ∙

research

∙ 06/17/2017

Towards Neural Phrase-based Machine Translation

In this paper, we present Neural Phrase-based Machine Translation (NPMT)...

0 Po-Sen Huang, et al. ∙

research

∙ 05/23/2017

Question-Answering with Grammatically-Interpretable Representations

We introduce an architecture, the Tensor Product Recurrent Network (TPRN...

0 Hamid Palangi, et al. ∙

research

∙ 02/28/2017

Scaffolding Networks: Incremental Learning and Teaching Through Questioning

We introduce a new paradigm of learning for reasoning, understanding, an...

0 Asli Celikyilmaz, et al. ∙

research

∙ 02/24/2017

Sequence Modeling via Segmentations

Segmental structure is a common pattern in many types of sequences such ...

0 Chong Wang, et al. ∙

research

∙ 02/08/2017

Character-level Deep Conflation for Business Data Analytics

Connecting different text attributes associated with the same entity (co...

0 Zhe Gan, et al. ∙

research

∙ 12/03/2016

End-to-End Joint Learning of Natural Language Understanding and Dialogue Manager

Natural language understanding and dialogue policy learning are both ess...

0 Xuesong Yang, et al. ∙

research

∙ 11/28/2016

MS MARCO: A Human Generated MAchine Reading COmprehension Dataset

This paper presents our recent work on the design and development of a n...

0 Tri Nguyen, et al. ∙

research

∙ 11/23/2016

Semantic Compositional Networks for Visual Captioning

A Semantic Compositional Network (SCN) is developed for image captioning...

0 Zhe Gan, et al. ∙

research

∙ 11/03/2016

Combating Reinforcement Learning's Sisyphean Curse with Intrinsic Fear

To use deep reinforcement learning in the wild, we might hope for an age...

0 Zachary C Lipton, et al. ∙

research

∙ 09/12/2016

Knowledge as a Teacher: Knowledge-Guided Structural Attention Networks

Natural language understanding (NLU) is a core component of a spoken dia...

0 Yun-Nung Chen, et al. ∙

research

∙ 09/03/2016

Towards End-to-End Reinforcement Learning of Dialogue Agents for Information Access

This paper proposes KB-InfoBot -- a multi-turn dialogue agent which help...

0 Bhuwan Dhingra, et al. ∙

research

∙ 08/06/2016

Bi-directional Attention with Agreement for Dependency Parsing

We develop a novel bi-directional attention model for dependency parsing...

0 Hao Cheng, et al. ∙

research

∙ 06/12/2016

Deep Reinforcement Learning with a Combinatorial Action Space for Predicting Popular Reddit Threads

We introduce an online popularity prediction and tracking task as a benc...

0 Ji He, et al. ∙

research

∙ 01/12/2016

Basic Reasoning with Tensor Product Representations

In this paper we present the initial development of a general theory for...

0 Paul Smolensky, et al. ∙

research

∙ 11/19/2015

Reasoning in Vector Space: An Exploratory Study of Question Answering

Question answering tasks have shown remarkable progress with distributed...

0 Moontae Lee, et al. ∙

research

∙ 11/14/2015

Deep Reinforcement Learning with a Natural Language Action Space

This paper introduces a novel architecture for reinforcement learning wi...

0 Ji He, et al. ∙

research

∙ 11/07/2015

Stacked Attention Networks for Image Question Answering

This paper presents stacked attention networks (SANs) that learn to answ...

0 Zichao Yang, et al. ∙

research

∙ 09/10/2015

Recurrent Reinforcement Learning: A Hybrid Approach

Successful applications of reinforcement learning in real-world problems...

0 Xiujun Li, et al. ∙

research

∙ 05/07/2015

Language Models for Image Captioning: The Quirks and What Works

Two recent approaches have achieved state-of-the-art results in image ca...

0 Jacob Devlin, et al. ∙

research

∙ 04/13/2015

Joint Learning of Distributed Representations for Images and Texts

This technical report provides extra details of the deep multimodal simi...

0 Xiaodong He, et al. ∙

research

∙ 02/24/2015

Deep Sentence Embedding Using Long Short-Term Memory Networks: Analysis and Application to Information Retrieval

This paper develops a model that addresses sentence embedding, a hot top...

0 Hamid Palangi, et al. ∙

research

∙ 12/20/2014

Embedding Entities and Relations for Learning and Inference in Knowledge Bases

We consider learning representations of entities and relations in KBs us...

0 Bishan Yang, et al. ∙

research

∙ 11/18/2014

From Captions to Visual Concepts and Back

This paper presents a novel approach for automatically generating image ...

0 Hao Fang, et al. ∙

research

∙ 11/14/2014

Learning Multi-Relational Semantics Using Neural-Embedding Models

In this paper we present a unified framework for modeling multi-relation...

0 Bishan Yang, et al. ∙

research

∙ 11/24/2013

A Primal-Dual Method for Training Recurrent Neural Networks Constrained by the Echo-State Property

We present an architecture of a recurrent neural network (RNN) with a fu...

0 Jianshu Chen, et al. ∙

Li Deng

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