Beyond task success: A closer look at jointly learning to see, ask, and GuessWhat

We propose a grounded dialogue state encoder which addresses a foundational issue on how to integrate visual grounding with dialogue system components. As a test-bed, we focus on the GuessWhat?! game, a two-player game where the goal is to identify an object in a complex visual scene by asking a sequence of yes/no questions. Our visually-grounded encoder leverages synergies between guessing and asking questions, as it is trained jointly using multi-task learning. We further enrich our model via a cooperative learning regime. We show that the introduction of both the joint architecture and cooperative learning lead to accuracy improvements over the baseline system. We compare our approach to an alternative system which extends the baseline with reinforcement learning. Our in-depth analysis shows that the linguistic skills of the two models differ dramatically, despite approaching comparable performance levels. This points at the importance of analyzing the linguistic output of competing systems beyond numeric comparison solely based on task success.Comment: Accepted to NAACL 201

Ask No More: Deciding when to guess in referential visual dialogue

Our goal is to explore how the abilities brought in by a dialogue manager can be included in end-to-end visually grounded conversational agents. We make initial steps towards this general goal by augmenting a task-oriented visual dialogue model with a decision-making component that decides whether to ask a follow-up question to identify a target referent in an image, or to stop the conversation to make a guess. Our analyses show that adding a decision making component produces dialogues that are less repetitive and that include fewer unnecessary questions, thus potentially leading to more efficient and less unnatural interactions

Collateral capacity assessment : Robustness and interobserver agreement of two grading scales and agreement with quantitative scoring

Background and purpose: Intracranial collateral capacity is conducive to imply parenchymal perfusion of affected territory after acute vessel occlusion. The Tan collateral score is commonly used to assess the intracranial collateral capacity; however, this score is coarsely grained and interobserver agreement is low, which reduces prognostic value and clinical utility. We introduce and evaluate an alternative extended Tan score based on the conventional Tan scale and assess the agreement with a quantitative score. Methods: We included 100 consecutive patients with a proven acute single large vessel occlusion of the proximal anterior circulation. Collaterals were graded with the conventional and extended Tan score and an automated quantitative score. The extended Tan score is a finer 6‑scale manual score based on the conventional 4‑point Tan scale. The quantitative score is calculated by an automatic software package (StrokeViewer). Interobserver agreement of the manual scores was assessed with the weighted kappa. The Spearman correlation coefficient was calculated to determine the agreement between the manual and automated collateral scores. Results: The interobserver agreement was higher for the extended score than for the conventional score with a weighted kappa of 0.70 and 0.65, respectively. For the extended and conventional score, the Spearman correlation coefficient for the agreement with the automated score was 0.78 and 0.76, respectively. Conclusion: Because of the good interobserver agreement and good agreement with quantitative assessment, the extended collateral score is a strong candidate to improve prognostic value of collateral assessment and implementation in clinical practice

Efficacy of live attenuated and inactivated influenza vaccines among children in rural India: A 2-year, randomized, triple-blind, placebo-controlled trial.

BackgroundInfluenza is a cause of febrile acute respiratory infection (FARI) in India; however, few influenza vaccine trials have been conducted in India. We assessed absolute and relative efficacy of live attenuated influenza vaccine (LAIV) and inactivated influenza vaccine (IIV) among children aged 2 to 10 years in rural India through a randomized, triple-blind, placebo-controlled trial conducted over 2 years.Methods and findingsIn June 2015, children were randomly allocated to LAIV, IIV, intranasal placebo, or inactivated polio vaccine (IPV) in a 2:2:1:1 ratio. In June 2016, vaccination was repeated per original allocation. Overall, 3,041 children received LAIV (n = 1,015), IIV (n = 1,010), nasal placebo (n = 507), or IPV (n = 509). Mean age of children was 6.5 years with 20% aged 9 to 10 years. Through weekly home visits, nasal and throat swabs were collected from children with FARI and tested for influenza virus by polymerase chain reaction. The primary outcome was laboratory-confirmed influenza-associated FARI; vaccine efficacy (VE) was calculated using modified intention-to-treat (mITT) analysis by Cox proportional hazards model (PH) for each year. In Year 1, VE was 40.0% (95% confidence interval (CI) 25.2 to 51.9) for LAIV and 59.0% (95% CI 47.8 to 67.9) for IIV compared with controls; relative efficacy of LAIV compared with IIV was -46.2% (95% CI -88.9 to -13.1). In Year 2, VE was 51.9% (95% CI 42.0 to 60.1) for LAIV and 49.9% (95% CI 39.2 to 58.7) for IIV; relative efficacy of LAIV compared with IIV was 4.2% (95% CI -19.9 to 23.5). No serious adverse vaccine-attributable events were reported. Study limitations include differing dosage requirements for children between nasal and injectable vaccines (single dose of LAIV versus 2 doses of IIV) in Year 1 and the fact that immunogenicity studies were not conducted.ConclusionsIn this study, we found that LAIV and IIV vaccines were safe and moderately efficacious against influenza virus infection among Indian children.Trial registrationClinical Trials Registry of India CTRI/2015/06/005902