Search Results for author: Asli Celikyilmaz

Found 43 papers, 16 papers with code

Enriching Transformers with Structured Tensor-Product Representations for Abstractive Summarization

1 code implementation NAACL 2021 Yichen Jiang, Asli Celikyilmaz, Paul Smolensky, Paul Soulos, Sudha Rao, Hamid Palangi, Roland Fernandez, Caitlin Smith, Mohit Bansal, Jianfeng Gao

On several syntactic and semantic probing tasks, we demonstrate the emergent structural information in the role vectors and improved syntactic interpretability in the TPR layer outputs.

Abstractive Text Summarization

QMSum: A New Benchmark for Query-based Multi-domain Meeting Summarization

1 code implementation NAACL 2021 Ming Zhong, Da Yin, Tao Yu, Ahmad Zaidi, Mutethia Mutuma, Rahul Jha, Ahmed Hassan Awadallah, Asli Celikyilmaz, Yang Liu, Xipeng Qiu, Dragomir Radev

As increasing numbers of meetings are recorded and transcribed, meeting summaries have become essential to remind those who may or may not have attended the meetings about the key decisions made and the tasks to be completed.

Meeting Summarization

Data Augmentation for Abstractive Query-Focused Multi-Document Summarization

1 code implementation2 Mar 2021 Ramakanth Pasunuru, Asli Celikyilmaz, Michel Galley, Chenyan Xiong, Yizhe Zhang, Mohit Bansal, Jianfeng Gao

The progress in Query-focused Multi-Document Summarization (QMDS) has been limited by the lack of sufficient largescale high-quality training datasets.

Data Augmentation Document Summarization +1

The Amazing World of Neural Language Generation

no code implementations EMNLP 2020 Yangfeng Ji, Antoine Bosselut, Thomas Wolf, Asli Celikyilmaz

Neural Language Generation (NLG) {--} using neural network models to generate coherent text {--} is among the most promising methods for automated text creation.

Language Modelling Text Generation +1

RMM: A Recursive Mental Model for Dialogue Navigation

no code implementations Findings of the Association for Computational Linguistics 2020 Homero Roman Roman, Yonatan Bisk, Jesse Thomason, Asli Celikyilmaz, Jianfeng Gao

In this paper, we go beyond instruction following and introduce a two-agent task where one agent navigates and asks questions that a second, guiding agent answers.

GO FIGURE: A Meta Evaluation of Factuality in Summarization

no code implementations24 Oct 2020 Saadia Gabriel, Asli Celikyilmaz, Rahul Jha, Yejin Choi, Jianfeng Gao

While neural language models can generate text with remarkable fluency and coherence, controlling for factual correctness in generation remains an open research question.

Common Sense Reasoning Document Summarization +1

Substance over Style: Document-Level Targeted Content Transfer

no code implementations EMNLP 2020 Allison Hegel, Sudha Rao, Asli Celikyilmaz, Bill Dolan

Existing language models excel at writing from scratch, but many real-world scenarios require rewriting an existing document to fit a set of constraints.

Document-level Language Modelling +1

Evaluation of Text Generation: A Survey

no code implementations26 Jun 2020 Asli Celikyilmaz, Elizabeth Clark, Jianfeng Gao

The paper surveys evaluation methods of natural language generation (NLG) systems that have been developed in the last few years.

Text Generation Text Summarization

Reparameterized Variational Divergence Minimization for Stable Imitation

1 code implementation18 Jun 2020 Dilip Arumugam, Debadeepta Dey, Alekh Agarwal, Asli Celikyilmaz, Elnaz Nouri, Bill Dolan

While recent state-of-the-art results for adversarial imitation-learning algorithms are encouraging, recent works exploring the imitation learning from observation (ILO) setting, where trajectories \textit{only} contain expert observations, have not been met with the same success.

Continuous Control Imitation Learning

A Recipe for Creating Multimodal Aligned Datasets for Sequential Tasks

1 code implementation ACL 2020 Angela S. Lin, Sudha Rao, Asli Celikyilmaz, Elnaz Nouri, Chris Brockett, Debadeepta Dey, Bill Dolan

Learning to align these different instruction sets is challenging because: a) different recipes vary in their order of instructions and use of ingredients; and b) video instructions can be noisy and tend to contain far more information than text instructions.

RMM: A Recursive Mental Model for Dialog Navigation

1 code implementation2 May 2020 Homero Roman Roman, Yonatan Bisk, Jesse Thomason, Asli Celikyilmaz, Jianfeng Gao

In this paper, we go beyond instruction following and introduce a two-agent task where one agent navigates and asks questions that a second, guiding agent answers.

PlotMachines: Outline-Conditioned Generation with Dynamic Plot State Tracking

2 code implementations EMNLP 2020 Hannah Rashkin, Asli Celikyilmaz, Yejin Choi, Jianfeng Gao

We propose the task of outline-conditioned story generation: given an outline as a set of phrases that describe key characters and events to appear in a story, the task is to generate a coherent narrative that is consistent with the provided outline.

AREDSUM: Adaptive Redundancy-Aware Iterative Sentence Ranking for Extractive Document Summarization

3 code implementations EACL 2021 Keping Bi, Rahul Jha, W. Bruce Croft, Asli Celikyilmaz

Redundancy-aware extractive summarization systems score the redundancy of the sentences to be included in a summary either jointly with their salience information or separately as an additional sentence scoring step.

Document Summarization Extractive Summarization +1

Working Memory Graphs

no code implementations ICML 2020 Ricky Loynd, Roland Fernandez, Asli Celikyilmaz, Adith Swaminathan, Matthew Hausknecht

Transformers have increasingly outperformed gated RNNs in obtaining new state-of-the-art results on supervised tasks involving text sequences.

Decision Making

Robust Navigation with Language Pretraining and Stochastic Sampling

1 code implementation IJCNLP 2019 Xiujun Li, Chunyuan Li, Qiaolin Xia, Yonatan Bisk, Asli Celikyilmaz, Jianfeng Gao, Noah Smith, Yejin Choi

Core to the vision-and-language navigation (VLN) challenge is building robust instruction representations and action decoding schemes, which can generalize well to previously unseen instructions and environments.

Vision and Language Navigation

Discourse Understanding and Factual Consistency in Abstractive Summarization

no code implementations EACL 2021 Saadia Gabriel, Antoine Bosselut, Jeff Da, Ari Holtzman, Jan Buys, Kyle Lo, Asli Celikyilmaz, Yejin Choi

We introduce a general framework for abstractive summarization with factual consistency and distinct modeling of the narrative flow in an output summary.

Abstractive Text Summarization

Sentence Mover's Similarity: Automatic Evaluation for Multi-Sentence Texts

no code implementations ACL 2019 Elizabeth Clark, Asli Celikyilmaz, Noah A. Smith

For evaluating machine-generated texts, automatic methods hold the promise of avoiding collection of human judgments, which can be expensive and time-consuming.

Semantic Similarity Semantic Textual Similarity +1

Learning Compressed Sentence Representations for On-Device Text Processing

1 code implementation ACL 2019 Dinghan Shen, Pengyu Cheng, Dhanasekar Sundararaman, Xinyuan Zhang, Qian Yang, Meng Tang, Asli Celikyilmaz, Lawrence Carin

Vector representations of sentences, trained on massive text corpora, are widely used as generic sentence embeddings across a variety of NLP problems.

Sentence Embeddings

COMET: Commonsense Transformers for Automatic Knowledge Graph Construction

2 code implementations ACL 2019 Antoine Bosselut, Hannah Rashkin, Maarten Sap, Chaitanya Malaviya, Asli Celikyilmaz, Yejin Choi

We present the first comprehensive study on automatic knowledge base construction for two prevalent commonsense knowledge graphs: ATOMIC (Sap et al., 2019) and ConceptNet (Speer et al., 2017).

graph construction Knowledge Graphs

Efficient Adaptation of Pretrained Transformers for Abstractive Summarization

2 code implementations1 Jun 2019 Andrew Hoang, Antoine Bosselut, Asli Celikyilmaz, Yejin Choi

Large-scale learning of transformer language models has yielded improvements on a variety of natural language understanding tasks.

Abstractive Text Summarization Natural Language Understanding

Cyclical Annealing Schedule: A Simple Approach to Mitigating KL Vanishing

2 code implementations NAACL 2019 Hao Fu, Chunyuan Li, Xiaodong Liu, Jianfeng Gao, Asli Celikyilmaz, Lawrence Carin

Variational autoencoders (VAEs) with an auto-regressive decoder have been applied for many natural language processing (NLP) tasks.

Language Modelling

Hierarchically Structured Reinforcement Learning for Topically Coherent Visual Story Generation

no code implementations21 May 2018 Qiuyuan Huang, Zhe Gan, Asli Celikyilmaz, Dapeng Wu, Jian-Feng Wang, Xiaodong He

We propose a hierarchically structured reinforcement learning approach to address the challenges of planning for generating coherent multi-sentence stories for the visual storytelling task.

Visual Storytelling

Discourse-Aware Neural Rewards for Coherent Text Generation

no code implementations NAACL 2018 Antoine Bosselut, Asli Celikyilmaz, Xiaodong He, Jianfeng Gao, Po-Sen Huang, Yejin Choi

In this paper, we investigate the use of discourse-aware rewards with reinforcement learning to guide a model to generate long, coherent text.

Sentence Ordering Text Generation

Deep Communicating Agents for Abstractive Summarization

no code implementations NAACL 2018 Asli Celikyilmaz, Antoine Bosselut, Xiaodong He, Yejin Choi

We present deep communicating agents in an encoder-decoder architecture to address the challenges of representing a long document for abstractive summarization.

Abstractive Text Summarization

Learning and analyzing vector encoding of symbolic representations

no code implementations10 Mar 2018 Roland Fernandez, Asli Celikyilmaz, Rishabh Singh, Paul Smolensky

We present a formal language with expressions denoting general symbol structures and queries which access information in those structures.

Composite Task-Completion Dialogue Policy Learning via Hierarchical Deep Reinforcement Learning

no code implementations EMNLP 2017 Baolin Peng, Xiujun Li, Lihong Li, Jianfeng Gao, Asli Celikyilmaz, Sungjin Lee, Kam-Fai Wong

Building a dialogue agent to fulfill complex tasks, such as travel planning, is challenging because the agent has to learn to collectively complete multiple subtasks.

Task-Completion Dialogue Policy Learning

End-to-End Task-Completion Neural Dialogue Systems

13 code implementations IJCNLP 2017 Xiujun Li, Yun-Nung Chen, Lihong Li, Jianfeng Gao, Asli Celikyilmaz

One of the major drawbacks of modularized task-completion dialogue systems is that each module is trained individually, which presents several challenges.


Scaffolding Networks: Incremental Learning and Teaching Through Questioning

no code implementations28 Feb 2017 Asli Celikyilmaz, Li Deng, Lihong Li, Chong Wang

We introduce a new paradigm of learning for reasoning, understanding, and prediction, as well as the scaffolding network to implement this paradigm.

Incremental Learning

Associative Adversarial Networks

no code implementations18 Nov 2016 Tarik Arici, Asli Celikyilmaz

In this work, we use Restricted Boltzmann Machines (RBMs) as a higher-level associative memory and learn the probability distribution for the high-level features generated by D. The associative memory samples its underlying probability distribution and G learns how to map these samples to data space.

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