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08/01/2023
Skills-in-Context Prompting: Unlocking Compositionality in Large Language Models
We consider the problem of eliciting compositional generalization capabi...
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07/19/2023
Thrust: Adaptively Propels Large Language Models with External Knowledge
Although large-scale pre-trained language models (PTLMs) are shown to en...
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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...
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05/24/2023
PIVOINE: Instruction Tuning for Open-world Information Extraction
We consider the problem of Open-world Information Extraction (Open-world...
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05/22/2023
CEO: Corpus-based Open-Domain Event Ontology Induction
Existing event-centric NLP models often only apply to the pre-defined on...
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02/19/2023
Learning Language Representations with Logical Inductive Bias
Transformer architectures have achieved great success in solving natural...
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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...
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10/28/2022
Knowledge-in-Context: Towards Knowledgeable Semi-Parametric Language Models
Fully-parametric language models generally require a huge number of mode...
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10/21/2022
Z-LaVI: Zero-Shot Language Solver Fueled by Visual Imagination
Large-scale pretrained language models have made significant advances in...
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10/13/2022
Explanations from Large Language Models Make Small Reasoners Better
Integrating free-text explanations to in-context learning of large langu...
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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...
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10/01/2022
Zemi: Learning Zero-Shot Semi-Parametric Language Models from Multiple Tasks
Although large language models have achieved impressive zero-shot abilit...
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09/07/2022
Blessing of Class Diversity in Pre-training
This paper presents a new statistical analysis aiming to explain the rec...
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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...
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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 ...
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02/01/2022
Planner-Reasoner Inside a Multi-task Reasoning Agent
We consider the problem of multi-task reasoning (MTR), where an agent ca...
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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...
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09/12/2020
Improving Machine Reading Comprehension with Contextualized Commonsense Knowledge
In this paper, we aim to extract commonsense knowledge to improve machin...
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07/23/2020
Comprehensive Image Captioning via Scene Graph Decomposition
We address the challenging problem of image captioning by revisiting the...
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06/15/2020
On Effective Parallelization of Monte Carlo Tree Search
Despite its groundbreaking success in Go and computer games, Monte Carlo...
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05/16/2020
Recurrent Chunking Mechanisms for Long-Text Machine Reading Comprehension
In this paper, we study machine reading comprehension (MRC) on long text...
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05/16/2020
Recurrent Chunking Mechanisms for Long-Text Machine Reading Comprehensio
In this paper, we study machine reading comprehension (MRC) on long text...
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04/22/2020
Logical Natural Language Generation from Open-Domain Tables
Neural natural language generation (NLG) models have recently shown rema...
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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...
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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...
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07/22/2019
Stochastic Variance Reduced Primal Dual Algorithms for Empirical Composition Optimization
We consider a generic empirical composition optimization problem, where ...
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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...
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05/30/2019
Semantically Conditioned Dialog Response Generation via Hierarchical Disentangled Self-Attention
Semantically controlled neural response generation on limited-domain has...
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02/23/2019
Evidence Sentence Extraction for Machine Reading Comprehension
Recently remarkable success has been achieved in machine reading compreh...
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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...
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12/23/2018
Unsupervised Speech Recognition via Segmental Empirical Output Distribution Matching
We consider the problem of training speech recognition systems without u...
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11/01/2018
Incorporating Structured Commonsense Knowledge in Story Completion
The ability to select an appropriate story ending is the first step towa...
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10/28/2018
P-MCGS: Parallel Monte Carlo Acyclic Graph Search
Recently, there have been great interests in Monte Carlo Tree Search (MC...
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08/19/2018
XL-NBT: A Cross-lingual Neural Belief Tracking Framework
Task-oriented dialog systems are becoming pervasive, and many companies ...
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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...
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12/29/2017
Smoothed Dual Embedding Control
We revisit the Bellman optimality equation with Nesterov's smoothing tec...
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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...
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02/25/2017
Stochastic Variance Reduction Methods for Policy Evaluation
Policy evaluation is a crucial step in many reinforcement-learning proce...
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02/08/2017
Character-level Deep Conflation for Business Data Analytics
Connecting different text attributes associated with the same entity (co...
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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...
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11/14/2015
Deep Reinforcement Learning with a Natural Language Action Space
This paper introduces a novel architecture for reinforcement learning wi...
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09/10/2015
Recurrent Reinforcement Learning: A Hybrid Approach
Successful applications of reinforcement learning in real-world problems...
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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...
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12/30/2013
Distributed Policy Evaluation Under Multiple Behavior Strategies
We apply diffusion strategies to develop a fully-distributed cooperative...
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11/24/2013