Zobrazeno 1 - 10
of 262
pro vyhledávání: '"Asli Celikyilmaz"'
Autor:
Yuan-Fang Wang, Xin Wang, Dinghan Shen, William Yang Wang, Qiuyuan Huang, Lei Zhang, Asli Celikyilmaz, Jianfeng Gao
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. 43:4205-4216
Vision-language navigation (VLN) is the task of navigating an embodied agent to carry out natural language instructions inside real 3D environments. In this paper, we study how to address three critical challenges for this task: the cross-modal groun
Autor:
Xiangru Tang, Alexander Fabbri, Haoran Li, Ziming Mao, Griffin Adams, Borui Wang, Asli Celikyilmaz, Yashar Mehdad, Dragomir Radev
Current pre-trained models applied to summarization are prone to factual inconsistencies which either misrepresent the source text or introduce extraneous information. Thus, comparing the factual consistency of summaries is necessary as we develop im
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4019491a1cf3fdaa4865a17c001ef0bf
http://arxiv.org/abs/2109.09195
http://arxiv.org/abs/2109.09195
Publikováno v:
AAAI
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. Within our framework, the task of generating a story given a
Autor:
Jianfeng Gao, Paul Smolensky, Asli Celikyilmaz, Yichen Jiang, Caitlin Smith, Mohit Bansal, Sudha Rao, Paul Soulos, Hamid Palangi, Roland Fernandez
Publikováno v:
NAACL-HLT
ive summarization, the task of generating a concise summary of input documents, requires: (1) reasoning over the source document to determine the salient pieces of information scattered across the long document, and (2) composing a cohesive text by r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::02c0746e192f82c6fb2c4cc75ffaccbc
Publikováno v:
ACL/IJCNLP (1)
Recent years have brought about an interest in the challenging task of summarizing conversation threads (meetings, online discussions, etc.). Such summaries help analysis of the long text to quickly catch up with the decisions made and thus improve o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b9fc7c223fe12ef60f51dd34458a090a
Autor:
Yusen Zhang, Ansong Ni, Tao Yu, Rui Zhang, Chenguang Zhu, Budhaditya Deb, Asli Celikyilmaz, Ahmed Hassan Awadallah, Dragomir Radev
Publikováno v:
Findings of the Association for Computational Linguistics: EMNLP 2021.
Publikováno v:
ACL/IJCNLP (Findings)
While neural language models can generate text with remarkable fluency and coherence, controlling for factual correctness in generation remains an open research question. This major discrepancy between the surface-level fluency and the content-level
Publikováno v:
CVPR Workshops
Self-supervised pretraining has become a strong force in both language and vision tasks. Current efforts to improve the effects of pretraining focus on improving network architecture or defining new tasks to extract representations from the data. We
Autor:
Chris Brockett, Elnaz Nouri, Sudha Rao, Angela S. Lin, Asli Celikyilmaz, Debadeepta Dey, Bill Dolan
Publikováno v:
ACL
Many high-level procedural tasks can be decomposed into sequences of instructions that vary in their order and choice of tools. In the cooking domain, the web offers many partially-overlapping text and video recipes (i.e. procedures) that describe ho
Autor:
Kieran McDonald, Yang Li, Asli Celikyilmaz, Keping Bi, Rahul Jha, Mahdi Pakdaman, Ivan Zhiboedov
We describe Artemis (Annotation methodology for Rich, Tractable, Extractive, Multi-domain, Indicative Summarization), a novel hierarchical annotation process that produces indicative summaries for documents from multiple domains. Current summarizatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c930e93b2d97b2ada6a88b950ce95774