Titlebook: Database Systems for Advanced Applications; 27th International C Arnab Bhattacharya,Janice Lee Mong Li,Rage Uday Ki Conference proceedings

愉快嗎

custody

Haijun Zeng,Zhisheng Li,Zhuo Zhangdifficult to identify. This not only affects the decision-making of consumers, but also seriously undermines the fairness of the consumption market. Most existing research ignored the abundant metadata in reviews and its effective combination with the review text. In this paper, we firstly collect r

誘導(dǎo)

Jeremy Kearney,Catherine Donovanthe internal and external influence at either element level or fact level. However, the multi-granularity information is essential for TKG modeling and the connection in between is also under-explored. In this paper, we propose the method that .ligning-internal .egularity and external .nfluence of .

aesthetic

Catherine Donovan,Jeremy Kearneyttracted much attention from researchers. Most of these approaches focus on constructing high-quality positives, while only using other in-batch sentences for negatives which are insufficient for training accurate discriminative boundaries. In this paper, we demonstrate that high-quality negative re

愛社交

Servile

Marianna Manca,Cecilia Vergnano. Due to the complex syntax of SQL and matching issues with table content, this task is prone to produce factual errors. In this paper, we propose ., a .ithfu. .trastive generation framework to improve the factual correctness of generated responses. . forces the generation model to identify examples

LEVER

嫻熟

PAEAN

Rational Choice Under Convex Conditions but the shared layers in multi-task learning tend to yield a compromise between the general and the task-specific representation of structural information. To address this issue, we propose a novel .ulti-.ask .earning framework with .hared .ulti-channel .nteractions (MTL-SMI), which is composed of

不能平靜

Vladimir I. Danilov,Alexander I. Sotskovty, some recent research works introduce external text for KBQA. However, such external information is not always readily available. We argue that it is critical for a KBQA system to know whether it lacks the knowledge to answer a given question. In this paper, we present a novel .neration .ssisted