b'Jianshu Chen'

research

∙ 08/01/2023

Skills-in-Context Prompting: Unlocking Compositionality in Large Language Models

We consider the problem of eliciting compositional generalization capabi...

0 Jiaao Chen, et al. ∙

research

∙ 07/19/2023

Thrust: Adaptively Propels Large Language Models with External Knowledge

Although large-scale pre-trained language models (PTLMs) are shown to en...

0 Xinran Zhao, et al. ∙

research

∙ 07/08/2023

A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

Recently developed large language models have achieved remarkable succes...

0 Neeraj Varshney, et al. ∙

research

∙ 05/24/2023

PIVOINE: Instruction Tuning for Open-world Information Extraction

We consider the problem of Open-world Information Extraction (Open-world...

0 Keming Lu, et al. ∙

research

∙ 05/22/2023

CEO: Corpus-based Open-Domain Event Ontology Induction

Existing event-centric NLP models often only apply to the pre-defined on...

0 Nan Xu, et al. ∙

research

∙ 02/19/2023

Learning Language Representations with Logical Inductive Bias

Transformer architectures have achieved great success in solving natural...

0 Jianshu Chen, et al. ∙

research

∙ 12/06/2022

ZeroKBC: A Comprehensive Benchmark for Zero-Shot Knowledge Base Completion

Knowledge base completion (KBC) aims to predict the missing links in kno...

0 Pei Chen, et al. ∙

research

∙ 10/28/2022

Knowledge-in-Context: Towards Knowledgeable Semi-Parametric Language Models

Fully-parametric language models generally require a huge number of mode...

0 Xiaoman Pan, et al. ∙

research

∙ 10/21/2022

Z-LaVI: Zero-Shot Language Solver Fueled by Visual Imagination

Large-scale pretrained language models have made significant advances in...

0 Yue Yang, et al. ∙

research

∙ 10/13/2022

Explanations from Large Language Models Make Small Reasoners Better

Integrating free-text explanations to in-context learning of large langu...

12 Shiyang Li, et al. ∙

research

∙ 10/06/2022

Join-Chain Network: A Logical Reasoning View of the Multi-head Attention in Transformer

Developing neural architectures that are capable of logical reasoning ha...

0 Jianyi Zhang, et al. ∙

research

∙ 10/01/2022

Zemi: Learning Zero-Shot Semi-Parametric Language Models from Multiple Tasks

Although large language models have achieved impressive zero-shot abilit...

5 Zhenhailong Wang, et al. ∙

research

∙ 09/07/2022

Blessing of Class Diversity in Pre-training

This paper presents a new statistical analysis aiming to explain the rec...

0 Yulai Zhao, et al. ∙

research

∙ 03/19/2022

Learning-by-Narrating: Narrative Pre-Training for Zero-Shot Dialogue Comprehension

Comprehending a dialogue requires a model to capture diverse kinds of ke...

0 Chao Zhao, et al. ∙

research

∙ 03/16/2022

C-MORE: Pretraining to Answer Open-Domain Questions by Consulting Millions of References

We consider the problem of pretraining a two-stage open-domain question ...

0 Xiang Yue, et al. ∙

research

∙ 02/01/2022

Planner-Reasoner Inside a Multi-task Reasoning Agent

We consider the problem of multi-task reasoning (MTR), where an agent ca...

0 Daoming Lyu, et al. ∙

research

∙ 10/27/2021

Connect-the-Dots: Bridging Semantics between Words and Definitions via Aligning Word Sense Inventories

Word Sense Disambiguation (WSD) aims to automatically identify the exact...

0 Wenlin Yao, et al. ∙

research

∙ 09/12/2020

Improving Machine Reading Comprehension with Contextualized Commonsense Knowledge

In this paper, we aim to extract commonsense knowledge to improve machin...

0 Kai Sun, et al. ∙

research

∙ 07/23/2020

Comprehensive Image Captioning via Scene Graph Decomposition

We address the challenging problem of image captioning by revisiting the...

3 Yiwu Zhong, et al. ∙

research

∙ 06/15/2020

On Effective Parallelization of Monte Carlo Tree Search

Despite its groundbreaking success in Go and computer games, Monte Carlo...

0 Anji Liu, et al. ∙

research

∙ 05/16/2020

Recurrent Chunking Mechanisms for Long-Text Machine Reading Comprehension

In this paper, we study machine reading comprehension (MRC) on long text...

0 Hongyu Gong, et al. ∙

research

∙ 05/16/2020

Recurrent Chunking Mechanisms for Long-Text Machine Reading Comprehensio

In this paper, we study machine reading comprehension (MRC) on long text...

0 Hongyu Gong, et al. ∙

research

∙ 04/22/2020

Logical Natural Language Generation from Open-Domain Tables

Neural natural language generation (NLG) models have recently shown rema...

3 Wenhu Chen, et al. ∙

research

∙ 09/20/2019

Teaching Pretrained Models with Commonsense Reasoning: A Preliminary KB-Based Approach

Recently, pretrained language models (e.g., BERT) have achieved great su...

0 Shiyang Li, et al. ∙

research

∙ 09/05/2019

TabFact: A Large-scale Dataset for Table-based Fact Verification

The problem of verifying whether a textual hypothesis holds the truth ba...

0 Wenhu Chen, et al. ∙

research

∙ 07/22/2019

Stochastic Variance Reduced Primal Dual Algorithms for Empirical Composition Optimization

We consider a generic empirical composition optimization problem, where ...

0 Adithya M. Devraj, 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

∙ 05/30/2019

Semantically Conditioned Dialog Response Generation via Hierarchical Disentangled Self-Attention

Semantically controlled neural response generation on limited-domain has...

0 Wenhu Chen, et al. ∙

research

∙ 02/23/2019

Evidence Sentence Extraction for Machine Reading Comprehension

Recently remarkable success has been achieved in machine reading compreh...

0 Hai Wang, et al. ∙

research

∙ 02/01/2019

DREAM: A Challenge Dataset and Models for Dialogue-Based Reading Comprehension

We present DREAM, the first dialogue-based multiple-choice reading compr...

0 Kai Sun, et al. ∙

research

∙ 12/23/2018

Unsupervised Speech Recognition via Segmental Empirical Output Distribution Matching

We consider the problem of training speech recognition systems without u...

6 Chih-Kuan Yeh, et al. ∙

research

∙ 11/01/2018

Incorporating Structured Commonsense Knowledge in Story Completion

The ability to select an appropriate story ending is the first step towa...

0 Jiaao Chen, et al. ∙

research

∙ 10/28/2018

P-MCGS: Parallel Monte Carlo Acyclic Graph Search

Recently, there have been great interests in Monte Carlo Tree Search (MC...

0 Chen Yu, et al. ∙

research

∙ 08/19/2018

XL-NBT: A Cross-lingual Neural Belief Tracking Framework

Task-oriented dialog systems are becoming pervasive, and many companies ...

0 Wenhu Chen, et al. ∙

research

∙ 02/12/2018

ReinforceWalk: Learning to Walk in Graph with Monte Carlo Tree Search

Learning to walk over a graph towards a target node for a given input qu...

0 Yelong Shen, et al. ∙

research

∙ 12/29/2017

Smoothed Dual Embedding Control

We revisit the Bellman optimality equation with Nesterov's smoothing tec...

0 Bo Dai, et al. ∙

research

∙ 10/21/2017

A Learning-to-Infer Method for Real-Time Power Grid Topology Identification

Identifying arbitrary topologies of power networks in real time is a com...

0 Yue Zhao, et al. ∙

research

∙ 02/25/2017

Stochastic Variance Reduction Methods for Policy Evaluation

Policy evaluation is a crucial step in many reinforcement-learning proce...

0 Simon S. Du, 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

∙ 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

∙ 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

∙ 09/10/2015

Recurrent Reinforcement Learning: A Hybrid Approach

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

0 Xiujun Li, 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

∙ 12/30/2013

Distributed Policy Evaluation Under Multiple Behavior Strategies

We apply diffusion strategies to develop a fully-distributed cooperative...

0 Sergio Valcarcel Macua, 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. ∙

Jianshu Chen

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