Reading Wikipedia to Answer Open-Domain Questions

This paper proposes to tackle open- domain question answering using Wikipedia as the unique knowledge source: the answer to any factoid question is a text span in a Wikipedia article. This task of machine reading at scale combines the challenges of document retrieval (finding the relevant articles) with that of machine comprehension of text (identifying the answer spans from those articles). Our approach combines a search component based on bigram hashing and TF-IDF matching with a multi-layer recurrent neural network model trained to detect answers in Wikipedia paragraphs. Our experiments on multiple existing QA datasets indicate that (1) both modules are highly competitive with respect to existing counterparts and (2) multitask learning using distant supervision on their combination is an effective complete system on this challenging task.Comment: ACL2017, 10 page

Working Hard or Hardly Working: Challenges of Integrating Typology into Neural Dependency Parsers

This paper explores the task of leveraging typology in the context of cross-lingual dependency parsing. While this linguistic information has shown great promise in pre-neural parsing, results for neural architectures have been mixed. The aim of our investigation is to better understand this state-of-the-art. Our main findings are as follows: 1) The benefit of typological information is derived from coarsely grouping languages into syntactically-homogeneous clusters rather than from learning to leverage variations along individual typological dimensions in a compositional manner; 2) Typology consistent with the actual corpus statistics yields better transfer performance; 3) Typological similarity is only a rough proxy of cross-lingual transferability with respect to parsing.Comment: EMNLP 201

Attorneys as Arbitrators

We study the role of attorneys as arbitrators in securities arbitration conducted by the National Association of Securities Dealers (NASD, n/k/a FINRA), using a dataset of 422 randomly selected arbitrators and their 6724 arbitration awards from 1992 to 2006. We find that arbitrators who also represent brokerage firms or brokers in other arbitrations award significantly less compensation to investor-claimants than other arbitrators. We find no significant effect for attorney-arbitrators who represent investors or both investors and brokerage firms. The relation between representing brokerage firms and arbitration awards remains significant even when we control for political outlook. We report that ideology correlates significantly with arbitration awards – arbitrators who donate money to Democratic political candidates award greater compensation than arbitrators who donate to Republican candidates. Because the arbitration award is the product of the panel, not a single arbitrator, we also study the dynamics of panel interaction. We find that the position of chair is an important factor in assessing the arbitrator’s influence, although the financial relationships of other arbitrators may also affect arbitration awards. Coalitions with the other arbitrators are also important. If the chair and another panelist possess a common attribute, the effect on the arbitration award increases. Finally, we provide evidence that the 1998 reforms to the arbitration process – which introduced party control over the composition of panels – ameliorated, but did not eliminate, the effect that attorneys who represent brokers have on outcomes. We find no significant effect from the NASD’s 2004 reforms

Few-shot Conformal Prediction with Auxiliary Tasks

We develop a novel approach to conformal prediction when the target task has limited data available for training. Conformal prediction identifies a small set of promising output candidates in place of a single prediction, with guarantees that the set contains the correct answer with high probability. When training data is limited, however, the predicted set can easily become unusably large. In this work, we obtain substantially tighter prediction sets while maintaining desirable marginal guarantees by casting conformal prediction as a meta-learning paradigm over exchangeable collections of auxiliary tasks. Our conformalization algorithm is simple, fast, and agnostic to the choice of underlying model, learning algorithm, or dataset. We demonstrate the effectiveness of this approach across a number of few-shot classification and regression tasks in natural language processing, computer vision, and computational chemistry for drug discovery.Comment: ICML camera read

Do Institutions Matter? The Impact of the Lead Plaintiff Provision of the Private Securities Litigation Reform Act

When Congress enacted the Private Securities Litigation Reform Act in 1995 ( PSLRA ), the Act\u27s lead plaintiff\u27 provision was the centerpiece of its efforts to increase investor control over securities fraud class actions. The lead plaintiff provision alters the balance of power between investors and class counsel by creating a presumption that the investor with the largest financial stake in the case will serve as lead plaintiff. The lead plaintiff then chooses class counsel and, at least in theory, negotiates the terms of counsel\u27s compensation. Congress\u27s stated purpose in enacting the lead plaintiff provision was to encourage institutional investors-pension funds, mutual funds, hedge funds, etc.-to come forward to serve as lead plaintiff. The theory was that an institutional investor with a substantial damages claim would have the incentive to bargain hard with class counsel on behalf of the class, reducing the percentage of the recovery awarded to class counsel. Congress also expected institutions to play an oversight role, monitoring to make sure that class counsel was vigorously pursuing claims on behalf of the class and not settling claims on the cheap. Our study offers evidence on the extent to which the lead plaintiff provision furthers these goals. We have collected two samples of securities class actions-one from 1991 to 1995 (pre-PSLRA) and one from 1996 to 2000 (post-PSLRA). We compare the class representatives from the two periods to determine if institutional investors are stepping forward in significantly greater numbers. We also sort the institutional investors distinguishing public from private-to see what types of investors have stepped forward to serve as lead plaintiff. Consistent with other research, we find a significant difference only in the number of public institutions serving as lead plaintiff. Our sample also allows us to analyze the impact of the lead plaintiff provision: Does the presence of an institutional investor increase the likelihood of a high-value settlement? Despite the visible participation of institutions in several high-profile cases, we find no systematic evidence that private institutional lead plaintiffs are associated with larger class recoveries. Public pension fund lead plaintiffs, on the other hand, are correlated with higher class recoveries as a fraction of the potential damage award in the post-PSLRA period. Our results are, however, consistent with the possibility that public pensions cherry-pick the actions in which they seek to become lead plaintiff, selecting only the cases with the largest potential damages and the strongest evidence of fraud. Further analysis is needed to evaluate this possibility. We also evaluate the effect of lead plaintiffs on the selection of attorneys and attorneys\u27 fees. We find that, for the time period of our study, institutional investors tended to avoid the Milberg Weiss plaintiffs\u27 attorney firm. On the more fundamental issue of whether the presence of an institutional investor as a lead plaintiff reduces the fees paid to the lawyers, after controlling for the size of the case, we find no systematic evidence that institutional involvement correlates with lower fee awards

Attorneys as Arbitrators

We study the role of attorneys as arbitrators in securities arbitration. We find that arbitrators who also represent brokerage firms or brokers in other arbitrations award significantly less compensation to investor-claimants than do other arbitrators. We find no significant effect for attorney-arbitrators who represent investors or both investors and brokerage firms. The relation between representing brokerage firms and arbitration awards remains significant even when we control for political outlook. Arbitrators who donate money to Democratic political candidates award greater compensation than do arbitrators who donate to Republican can-didates. We also study the dynamics of panel interaction. We find that the position of chair is an important factor in assessing an arbitrator’s influence, although the financial relationships of other arbitrators may also affect arbitration awards. Coalitions with the other arbitrators are also important. If the chair and another panelist possess a common attribute, the effect on the arbitration award increases

Attorneys as Arbitrators

We study the role of attorneys as arbitrators in securities arbitration. We find that arbitrators who also represent brokerage firms or brokers in other arbitrations award significantly less compensation to investor-claimants than do other arbitrators. We find no significant effect for attorney-arbitrators who represent investors or both investors and brokerage firms. The relation between representing brokerage firms and arbitration awards remains significant even when we control for political outlook. Arbitrators who donate money to Democratic political candidates award greater compensation than do arbitrators who donate to Republican can-didates. We also study the dynamics of panel interaction. We find that the position of chair is an important factor in assessing an arbitrator’s influence, although the financial relationships of other arbitrators may also affect arbitration awards. Coalitions with the other arbitrators are also important. If the chair and another panelist possess a common attribute, the effect on the arbitration award increases