In this task, you are given a part of an article. Your task is to generate headline (title) for this text. Preferred headlines are under fifteen words.

Input: Consider Input: There are already quite a few tools for solving the Satisfiability Modulo Theories (SMT) problems. In this paper, we present VolCE, a tool for counting the solutions of SMT constraints, or in other words, for computing the volume of the solution space. Its input is essentially a set of Boolean combinations of linear constraints, where the numeric variables are either all integers or all reals, and each variable is bounded. The tool extends SMT solving with integer solution counting and volume computation/estimation for convex polytopes. Effective heuristics are adopted, which enable the tool to deal with high-dimensional problem instances efficiently and accurately.

Output: A Tool for Computing and Estimating the Volume of the Solution Space of SMT(LA) Constraints


Input: Consider Input: Understanding a long document requires tracking how entities are introduced and evolve over time. We present a new type of language model, ENTITYNLM, that can explicitly model entities, dynamically update their representations, and contextually generate their mentions. Our model is generative and flexible; it can model an arbitrary number of entities in context while generating each entity mention at an arbitrary length. In addition, it can be used for several different tasks such as language modeling, coreference resolution, and entity prediction. Experimental results with all these tasks demonstrate that our model consistently outperforms strong baselines and prior work.

Output: Dynamic Entity Representations in Neural Language Models


Input: Consider Input: Americans spend about a third of their time online, with many participating in online conversations on social and political issues. We hypothesize that social media arguments on such issues may be more engaging and persuasive than traditional media summaries, and that particular types of people may be more or less convinced by particular styles of argument, e.g. emotional arguments may resonate with some personalities while factual arguments resonate with others. We report a set of experiments testing at large scale how audience variables interact with argument style to affect the persuasiveness of an argument, an under-researched topic within natural language processing. We show that belief change is affected by personality factors, with conscientious, open and agreeable people being more convinced by emotional arguments.


Output: Argument Strength is in the Eye of the Beholder: Audience Effects in Persuasion