NLPExplorer

Ashish Sabharwal

Number of Papers:- 32

Number of Citations:- 36

First ACL Paper:- 2015

Latest ACL Paper:- 2022

Venues:-

ACL

CoNLL

Findings

EMNLP

IJCNLP

NAACL

TACL

Co-Authors:-

Similar Authors:-

Hey AI, Can You Solve Complex Tasks by Talking to Agents? ACL Findings

Tushar Khot | Kyle Richardson | Daniel Khashabi | Ashish Sabharwal |

♫ MuSiQue: Multihop Questions via Single-hop Question Composition TACL

Harsh Trivedi | Niranjan Balasubramanian | Tushar Khot | Ashish Sabharwal |

Prompt Waywardness: The Curious Case of Discretized Interpretation of Continuous Prompts NAACL

Saturated Transformers are Constant-Depth Threshold Circuits TACL

William Merrill | Ashish Sabharwal | Noah A. Smith |

LILA: A Unified Benchmark for Mathematical Reasoning EMNLP

What Makes Instruction Learning Hard? An Investigation and a New Challenge in a Synthetic Environment EMNLP

Matthew Finlayson | Kyle Richardson | Ashish Sabharwal | Peter Clark |

Teaching Broad Reasoning Skills for Multi-Step QA by Generating Hard Contexts EMNLP

Harsh Trivedi | Niranjan Balasubramanian | Tushar Khot | Ashish Sabharwal |

Breakpoint Transformers for Modeling and Tracking Intermediate Beliefs EMNLP

Temporal Reasoning on Implicit Events from Distant Supervision NAACL

Text Modular Networks: Learning to Decompose Tasks in the Language of Existing Models NAACL

GooAQ: Open Question Answering with Diverse Answer Types EMNLP Findings

ReadOnce Transformers: Reusable Representations of Text for Transformers ACL IJCNLP

Shih-Ting Lin | Ashish Sabharwal | Tushar Khot |

How much coffee was consumed during EMNLP 2019? Fermi Problems: A New Reasoning Challenge for AI EMNLP

Ethical-Advice Taker: Do Language Models Understand Natural Language Interventions? Findings

Not All Claims are Created Equal: Choosing the Right Statistical Approach to Assess Hypotheses ACL

Erfan Sadeqi Azer | Daniel Khashabi | Ashish Sabharwal | Dan Roth |

UNIFIEDQA: Crossing Format Boundaries with a Single QA System EMNLP Findings

A Simple Yet Strong Pipeline for HotpotQA EMNLP

Dirk Groeneveld | Tushar Khot | Mausam | Ashish Sabharwal |

UNQOVERing Stereotyping Biases via Underspecified Questions EMNLP Findings

Is Multihop QA in DiRe Condition? Measuring and Reducing Disconnected Reasoning EMNLP

Harsh Trivedi | Niranjan Balasubramanian | Tushar Khot | Ashish Sabharwal |

More Bang for Your Buck: Natural Perturbation for Robust Question Answering EMNLP

Daniel Khashabi | Tushar Khot | Ashish Sabharwal |

What Does My QA Model Know? Devising Controlled Probes Using Expert Knowledge TACL

Kyle Richardson | Ashish Sabharwal |

What’s Missing: A Knowledge Gap Guided Approach for Multi-hop Question Answering EMNLP

Tushar Khot | Ashish Sabharwal | Peter Clark |

Repurposing Entailment for Multi-Hop Question Answering Tasks NAACL

Exploiting Explicit Paths for Multi-hop Reading Comprehension ACL

Souvik Kundu | Tushar Khot | Ashish Sabharwal | Peter Clark |

Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering EMNLP

Todor Mihaylov | Peter Clark | Tushar Khot | Ashish Sabharwal |

Bridging Knowledge Gaps in Neural Entailment via Symbolic Models EMNLP

Dongyeop Kang | Tushar Khot | Ashish Sabharwal | Peter Clark |

AdvEntuRe: Adversarial Training for Textual Entailment with Knowledge-Guided Examples ACL

Dongyeop Kang | Tushar Khot | Ashish Sabharwal | Eduard Hovy |

Knowledge Completion for Generics using Guided Tensor Factorization TACL

Hanie Sedghi | Ashish Sabharwal |

Learning What is Essential in Questions CoNLL

Daniel Khashabi | Tushar Khot | Ashish Sabharwal | Dan Roth |

Answering Complex Questions Using Open Information Extraction ACL

Tushar Khot | Ashish Sabharwal | Peter Clark |

Exploring Markov Logic Networks for Question Answering EMNLP

Parsing Algebraic Word Problems into Equations TACL