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09/20/2023
You Only Look at Screens: Multimodal Chain-of-Action Agents
Autonomous user interface (UI) agents aim to facilitate task automation ...
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09/18/2023
Multi-turn Dialogue Comprehension from a Topic-aware Perspective
Dialogue related Machine Reading Comprehension requires language models ...
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06/21/2023
Modeling Hierarchical Reasoning Chains by Linking Discourse Units and Key Phrases for Reading Comprehension
Machine reading comprehension (MRC) poses new challenges over logical re...
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05/10/2023
Decker: Double Check with Heterogeneous Knowledge for Commonsense Fact Verification
Commonsense fact verification, as a challenging branch of commonsense qu...
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02/08/2023
Is ChatGPT a General-Purpose Natural Language Processing Task Solver?
Spurred by advancements in scale, large language models (LLMs) have demo...
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02/02/2023
Multimodal Chain-of-Thought Reasoning in Language Models
Large language models (LLMs) have shown impressive performance on comple...
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01/10/2023
Channel-aware Decoupling Network for Multi-turn Dialogue Comprehension
Training machines to understand natural language and interact with human...
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12/16/2022
Self-Prompting Large Language Models for Open-Domain QA
Open-Domain Question Answering (ODQA) requires models to answer factoid ...
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12/01/2022
Language Model Pre-training on True Negatives
Discriminative pre-trained language models (PLMs) learn to predict origi...
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10/23/2022
Retrieval Augmentation for Commonsense Reasoning: A Unified Approach
A common thread of retrieval-augmented methods in the existing literatur...
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10/13/2022
Towards End-to-End Open Conversational Machine Reading
In open-retrieval conversational machine reading (OR-CMR) task, machines...
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10/07/2022
Automatic Chain of Thought Prompting in Large Language Models
Large language models (LLMs) can perform complex reasoning by generating...
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08/23/2022
Learning Better Masking for Better Language Model Pre-training
Masked Language Modeling (MLM) has been widely used as the denoising obj...
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04/18/2022
Back to the Future: Bidirectional Information Decoupling Network for Multi-turn Dialogue Modeling
Multi-turn dialogue modeling as a challenging branch of natural language...
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03/19/2022
Distinguishing Non-natural from Natural Adversarial Samples for More Robust Pre-trained Language Model
Recently, the problem of robustness of pre-trained language models (PrLM...
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10/15/2021
Structural Modeling for Dialogue Disentanglement
Tangled multi-party dialogue context leads to challenges for dialogue re...
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10/15/2021
Tracing Origins: Coref-aware Machine Reading Comprehension
Machine reading comprehension is a heavily-studied research and test fie...
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10/14/2021
Representation Decoupling for Open-Domain Passage Retrieval
Training dense passage representations via contrastive learning (CL) has...
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10/07/2021
Multi-tasking Dialogue Comprehension with Discourse Parsing
Multi-party dialogue machine reading comprehension (MRC) raises an even ...
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09/09/2021
Enhanced Speaker-aware Multi-party Multi-turn Dialogue Comprehension
Multi-party multi-turn dialogue comprehension brings unprecedented chall...
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08/29/2021
Span Fine-tuning for Pre-trained Language Models
Pre-trained language models (PrLM) have to carefully manage input units ...
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08/28/2021
Smoothing Dialogue States for Open Conversational Machine Reading
Conversational machine reading (CMR) requires machines to communicate wi...
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07/25/2021
Graph-free Multi-hop Reading Comprehension: A Select-to-Guide Strategy
Multi-hop reading comprehension (MHRC) requires not only to predict the ...
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06/04/2021
BO-DBA: Query-Efficient Decision-Based Adversarial Attacks via Bayesian Optimization
Decision-based attacks (DBA), wherein attackers perturb inputs to spoof ...
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05/23/2021
Structural Pre-training for Dialogue Comprehension
Pre-trained language models (PrLMs) have demonstrated superior performan...
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05/21/2021
Fact-driven Logical Reasoning
Logical reasoning, which is closely related to human cognition, is of vi...
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03/04/2021
Advances in Multi-turn Dialogue Comprehension: A Survey
Training machines to understand natural language and interact with human...
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02/11/2021
Text Compression-aided Transformer Encoding
Text encoding is one of the most important steps in Natural Language Pro...
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02/10/2021
Multi-turn Dialogue Reading Comprehension with Pivot Turns and Knowledge
Multi-turn dialogue reading comprehension aims to teach machines to read...
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02/04/2021
SAFELearning: Enable Backdoor Detectability In Federated Learning With Secure Aggregation
For model privacy, local model parameters in federated learning shall be...
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12/30/2020
Accurate Word Representations with Universal Visual Guidance
Word representation is a fundamental component in neural language unders...
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12/30/2020
Enhancing Pre-trained Language Model with Lexical Simplification
For both human readers and pre-trained language models (PrLMs), lexical ...
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12/29/2020
Dialogue Graph Modeling for Conversational Machine Reading
Conversational Machine Reading (CMR) aims at answering questions in a co...
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12/27/2020
SG-Net: Syntax Guided Transformer for Language Representation
Understanding human language is one of the key themes of artificial inte...
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12/07/2020
Reference Knowledgeable Network for Machine Reading Comprehension
Multi-choice Machine Reading Comprehension (MRC) is a major and challeng...
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09/26/2020
Topic-Aware Multi-turn Dialogue Modeling
In the retrieval-based multi-turn dialogue modeling, it remains a challe...
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09/15/2020
Multi-span Style Extraction for Generative Reading Comprehension
Generative machine reading comprehension (MRC) requires a model to gener...
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09/14/2020
Filling the Gap of Utterance-aware and Speaker-aware Representation for Multi-turn Dialogue
A multi-turn dialogue is composed of multiple utterances from two or mor...
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09/14/2020
Composing Answer from Multi-spans for Reading Comprehension
This paper presents a novel method to generate answers for non-extractio...
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09/10/2020
Task-specific Objectives of Pre-trained Language Models for Dialogue Adaptation
Pre-trained Language Models (PrLMs) have been widely used as backbones i...
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05/13/2020
Machine Reading Comprehension: The Role of Contextualized Language Models and Beyond
Machine reading comprehension (MRC) aims to teach machines to read and c...
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04/29/2020
Multi-choice Dialogue-Based Reading Comprehension with Knowledge and Key Turns
Multi-choice machine reading comprehension (MRC) requires models to choo...
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01/27/2020
Retrospective Reader for Machine Reading Comprehension
Machine reading comprehension (MRC) is an AI challenge that requires mac...
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12/27/2019
Explicit Sentence Compression for Neural Machine Translation
State-of-the-art Transformer-based neural machine translation (NMT) syst...
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11/07/2019
Probing Contextualized Sentence Representations with Visual Awareness
We present a universal framework to model contextualized sentence repres...
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10/31/2019
LIMIT-BERT : Linguistic Informed Multi-Task BERT
In this paper, we present a Linguistic Informed Multi-Task BERT (LIMIT-B...
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09/05/2019
Semantics-aware BERT for Language Understanding
The latest work on language representations carefully integrates context...
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09/03/2019
Modeling Named Entity Embedding Distribution into Hypersphere
This work models named entity distribution from a way of visualizing top...
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09/03/2019
A Smart Sliding Chinese Pinyin Input Method Editor on Touchscreen
This paper presents a smart sliding Chinese pinyin Input Method Editor (...
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08/30/2019
