Viewing 1-10 of 48 papers
  • Break It Down: A Question Understanding Benchmark

    Tomer Wolfson, Mor Geva, Ankit Gupta, Matt Gardner, Yoav Goldberg, Daniel Deutch, Jonathan BerantTACL2020Understanding natural language questions entails the ability to break down a question into the requisite steps for computing its answer. In this work, we introduce a Question Decomposition Meaning Representation (QDMR) for questions. QDMR constitutes the ordered list of steps, expressed through… more
  • A Formal Hierarchy of RNN Architectures

    William. Merrill, Gail Garfinkel Weiss, Yoav Goldberg, Roy Schwartz, Noah A. Smith, Eran YahavACL2020We develop a formal hierarchy of the expressive capacity of RNN architectures. The hierarchy is based on two formal properties: space complexity, which measures the RNN's memory, and rational recurrence, defined as whether the recurrent update can be described by a weighted finite-state machine. We… more
  • A Two-Stage Masked LM Method for Term Set Expansion

    Guy Kushilevitz, Shaul Markovitch, Yoav GoldbergACL2020We tackle the task of Term Set Expansion (TSE): given a small seed set of example terms from a semantic class, finding more members of that class. The task is of great practical utility, and also of theoretical utility as it requires generalization from few examples. Previous approaches to the TSE… more
  • Injecting Numerical Reasoning Skills into Language Models

    Mor Geva, Ankit Gupta, Jonathan BerantACL2020Large pre-trained language models (LMs) are known to encode substantial amounts of linguistic information. However, high-level reasoning skills, such as numerical reasoning, are difficult to learn from a language-modeling objective only. Consequently, existing models for numerical reasoning have… more
  • Interactive Extractive Search over Biomedical Corpora

    Hillel Taub-Tabib, Micah Shlain, Shoval Sadde, Dan Lahav, Matan Eyal, Yaara Cohen, Yoav GoldbergACL2020We present a system that allows life-science researchers to search a linguistically annotated corpus of scientific texts using patterns over dependency graphs, as well as using patterns over token sequences and a powerful variant of boolean keyword queries. In contrast to previous attempts to… more
  • Nakdan: Professional Hebrew Diacritizer

    Avi Shmidman, Shaltiel Shmidman, Moshe Koppel, Yoav GoldbergACL2020We present a system for automatic diacritization of Hebrew text. The system combines modern neural models with carefully curated declarative linguistic knowledge and comprehensive manually constructed tables and dictionaries. Besides providing state of the art diacritization accuracy, the system… more
  • Null It Out: Guarding Protected Attributes by Iterative Nullspace Projection

    Shauli Ravfogel, Yanai Elazar, Hila Gonen, Michael Twiton, Yoav GoldbergACL2020The ability to control for the kinds of information encoded in neural representation has a variety of use cases, especially in light of the challenge of interpreting these models. We present Iterative Null-space Projection (INLP), a novel method for removing information from neural representations… more
  • Obtaining Faithful Interpretations from Compositional Neural Networks

    Sanjay Subramanian, Ben Bogin, Nitish Gupta, Tomer Wolfson, Sameer Singh, Jonathan Berant, Matt Gardner ACL2020Neural module networks (NMNs) are a popular approach for modeling compositionality: they achieve high accuracy when applied to problems in language and vision, while reflecting the compositional structure of the problem in the network architecture. However, prior work implicitly assumed that the… more
  • pyBART: Evidence-based Syntactic Transformations for IE

    Aryeh Tiktinsky, Yoav Goldberg, Reut TsarfatyACL2020Syntactic dependencies can be predicted with high accuracy, and are useful for both machine-learned and pattern-based information extraction tasks. However, their utility can be improved. These syntactic dependencies are designed to accurately reflect syntactic relations, and they do not make… more
  • Syntactic Search by Example

    Micah Shlain, Hillel Taub-Tabib, Shoval Sadde, Yoav GoldbergACL2020We present a system that allows a user to search a large linguistically annotated corpus using syntactic patterns over dependency graphs. In contrast to previous attempts to this effect, we introduce a light-weight query language that does not require the user to know the details of the underlying… more