650 research outputs found
Answering Unanswered Questions through Semantic Reformulations in Spoken QA
Spoken Question Answering (QA) is a key feature of voice assistants, usually
backed by multiple QA systems. Users ask questions via spontaneous speech which
can contain disfluencies, errors, and informal syntax or phrasing. This is a
major challenge in QA, causing unanswered questions or irrelevant answers, and
leading to bad user experiences. We analyze failed QA requests to identify core
challenges: lexical gaps, proposition types, complex syntactic structure, and
high specificity. We propose a Semantic Question Reformulation (SURF) model
offering three linguistically-grounded operations (repair, syntactic reshaping,
generalization) to rewrite questions to facilitate answering. Offline
evaluation on 1M unanswered questions from a leading voice assistant shows that
SURF significantly improves answer rates: up to 24% of previously unanswered
questions obtain relevant answers (75%). Live deployment shows positive impact
for millions of customers with unanswered questions; explicit relevance
feedback shows high user satisfaction.Comment: Accepted by ACL 2023 Industry Trac
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History Modeling for Conversational Information Retrieval
Conversational search is an embodiment of an iterative and interactive approach to information retrieval (IR) that has been studied for decades. Due to the recent rise of intelligent personal assistants, such as Siri, Alexa, AliMe, Cortana, and Google Assistant, a growing part of the population is moving their information-seeking activities to voice- or text-based conversational interfaces. One of the major challenges of conversational search is to leverage the conversation history to understand and fulfill the users\u27 information needs. In this dissertation work, we investigate history modeling approaches for conversational information retrieval. We start from history modeling for user intent prediction. We analyze information-seeking conversations by user intent distribution, co-occurrence, and flow patterns, followed by a study of user intent prediction in an information-seeking setting with both feature-based methods and deep learning methods. We then move to history modeling for conversational question answering (ConvQA), which can be considered as a simplified setting of conversational search. We first propose a positional history answer embedding (PosHAE) method to seamlessly integrate conversation history into a ConvQA model based on BERT. We then build upon this method and design a history attention mechanism (HAM) to conduct a ``soft selection\u27\u27 for conversation history. After this, we extend the previous ConvQA task to an open-retrieval (ORConvQA) setting to emphasize the fundamental role of retrieval in conversational search. In this setting, we learn to retrieve evidence from a large collection before extracting answers. We build an end-to-end system for ORConvQA, featuring a learnable dense retriever. We conduct experiments with both fully-supervised and weakly-supervised approaches to tackle the training challenges of ORConvQA. Finally, we study history modeling for conversational re-ranking. Given a history of user feedback behaviors, such as issuing a query, clicking a document, and skipping a document, we propose to introduce behavior awareness to a neural ranker. Our experimental results show that the history modeling approaches proposed in this dissertation can effectively improve the performance of different conversation tasks and provide new insights into conversational information retrieval
Big Leagues: Specters of Milton and Republican International Justice between Shakespeare and Marx
Through Jacques Derrida’s extended discussion in Specters of Marx: The State of the Debt, the Work of Mourning and the New International, Shakespeare’s Hamlet has become “an exemplary text for thinking together about the current state of the world” (Royle). This article concerns Shakespeare’s Hamlet alongside Milton’s Paradise Lost as texts central to writing the “literary history of the International.” Whereas Derrida and Marx placed Hamlet at the center of their influential international visions, this article argues that the role of republicanism in forging international solidarity from the seventeenth-century onwards suggests that any literary history of the International ought also to include that key republican touchstone, Milton’s Paradise Lost. Against current critical consensus, however, it also argues that Paradise Lost’s republican internationalism developed through Milton’s own reading of Hamlet, and that Shakespeare himself may have been Milton’s “old mole.
Leveraging Feedback in Conversational Question Answering Systems
172 p.Tesi honen helburua martxan jarri eta geroko sistemek gizakiekin duten elkarregina erabiltzeada, gizakien feedbacka sistementzako ikasketa eta egokitzapen seinale bezala erabiliz.Elkarrizketa sistemek martxan jartzerakoan jasaten duten domeinu aldaketan jartzen dugufokua. Helburu honetarako, feedback bitar esplizituaren kasua aztertzen dugu, hau baitagizakientzat feedbacka emateko seinale errazena.Sistemak martxan jarri eta gero hobetzeko, lehenik eta behin DoQA izeneko galdera-erantzunmotako elkarriketez osatutako datu multzo bat eraiki dugu. Datu multzo honekcrowdsourcing bidez jasotako 2.437 dialogo ditu. Aurreko lanekin konparatuz gero, DoQAkbenetazko informazio beharrak islatzen ditu, datu multzo barneko elkarrizketak naturalagoaketa koherenteagoak izanik. Datu multzo sortu eta gero, feedback-weighted learning (FWL)izeneko algoritmo bat diseinatu dugu, feedback bitarra bakarrik erabiliz aurretikentrenatutako sistema gainbegiratu bat hobetzeko gai dena. Azkenik, algoritmo honen mugakaztertzen ditugu jasotako feedbacka zaratatsua den kasuetarako eta FWL moldatzen dugueszenatoki zaratsuari aurre egiteko. Kasu honetan lortzen ditugun emaitza negatiboakerakusten dute erabiltzaileetatik jasotako feedback zaratsua modelatzearen erronka, hauebaztea oraindik ikerkuntza galdera ireki bat delarik
Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language
Large foundation models can exhibit unique capabilities depending on the
domain of data they are trained on. While these domains are generic, they may
only barely overlap. For example, visual-language models (VLMs) are trained on
Internet-scale image captions, but large language models (LMs) are further
trained on Internet-scale text with no images (e.g. from spreadsheets, to SAT
questions). As a result, these models store different forms of commonsense
knowledge across different domains. In this work, we show that this model
diversity is symbiotic, and can be leveraged to build AI systems with
structured Socratic dialogue -- in which new multimodal tasks are formulated as
a guided language-based exchange between different pre-existing foundation
models, without additional finetuning. In the context of egocentric perception,
we present a case study of Socratic Models (SMs) that can provide meaningful
results for complex tasks such as generating free-form answers to contextual
questions about egocentric video, by formulating video Q&A as short story Q&A,
i.e. summarizing the video into a short story, then answering questions about
it. Additionally, SMs can generate captions for Internet images, and are
competitive with state-of-the-art on zero-shot video-to-text retrieval with
42.8 R@1 on MSR-VTT 1k-A. SMs demonstrate how to compose foundation models
zero-shot to capture new multimodal functionalities, without domain-specific
data collection. Prototypes are available at socraticmodels.github.io.Comment: https://socraticmodels.github.io
Analyzing Authentic Texts for Language Learning: Web-based Technology for Input Enrichment and Question Generation
Acquisition of a language largely depends on the learner's exposure to and interaction with it. Our research goal is to explore and implement automatic techniques that help create a richer grammatical intake from a given text input and engage learners in making form-meaning connections during reading.
A starting point for addressing this issue is the automatic input enrichment method, which aims to ensure that a target structure is richly represented in a given text.
We demonstrate the high performance of our rule-based algorithm, which is able to detect 87 linguistic forms contained in an official curriculum for the English language. Showcasing the algorithm's capability to differentiate between the various functions of the same linguistic form, we establish the task of tense sense disambiguation, which we approach by leveraging machine learning and rule-based methods.
Using the aforementioned technology, we develop an online information retrieval system FLAIR that prioritizes texts with a rich representation of selected linguistic forms. It is implemented as a web search engine for language teachers and learners and provides effective input enrichment in a real-life teaching setting. It can also serve as a foundation for empirical research on input enrichment and input enhancement.
The input enrichment component of the FLAIR system is evaluated in a web-based study that demonstrates that English teachers prefer automatic input enrichment to standard web search when selecting reading material for class.
We then explore automatic question generation for facilitating and testing reading comprehension as well as linguistic knowledge.
We give an overview of the types of questions that are usually asked and can be automatically generated from text in the language learning context. We argue that questions can facilitate the acquisition of different linguistic forms by providing functionally driven input enhancement, i.e., by ensuring that the learner notices and processes the form.
The generation of well-established and novel types of questions is discussed and examples are provided; moreover, the results from a crowdsourcing study show that automatically generated questions are comparable to human-written ones
Othello: A guide to the text and the play in performance
Othello is one of Shakespeare's most theatrically striking plays. This Handbook focuses on Othello as a dramatic work which exploits the resources of the early modern stage and yet still challenges contemporary theatres. Exploring race and gender as performance issues throughout the study, Stuart Hampton-Reeves:
• examines the play's earliest performances and the problem of staging darkness on Shakespeare's stage
• analyses the play from a performance point of view scene by scene, line by line
• surveys key productions and films, tracing the play's move away from mainstream theatres
• draws together the latest criticism on Othello's treatment of identity and sexuality
Blood Relations: Collective Memory, Cultural Trauma, & the Prosecution & Execution of Timothy McVeigh
In the aftermath of the Oklahoma City bombing, processes of reconstruction - remembering victims, caring for family members and survivors, and punishing the perpetrators - began even as debris from the Murrah Federal Building was being cleared. Based on conclusions obtained from intensive interviews with 27 victims\u27 family members and survivors, this article explores how memory of the bombing as a culturally traumatic event was constructed through participation in groups formed after the bombing and participation in the legal proceedings against perpetrators Timothy McVeigh and Terry Nichols. These acts cultivated the formation of various relationships - between family members and survivors as well as between these victimized populations and the perpetrators - that both helped and hindered individual and communal reconstructions of meaning. This article will first address the efficacy of a collective memory and cultural trauma perspective for analyzing two collective processes of sense-making - group membership and legal proceedings - in the aftermath of the Oklahoma City bombing. It will then briefly describe the mental context in which family members and survivors joined groups in the wake of the bombing, and the functions those groups played in trauma recovery, after which it will summarize the impact of group membership on punishment expectations. Next, it will discuss the involuntary relationship that formed between McVeigh and family members and survivors predicated on the social and media representations of McVeigh; due to this relationship, McVeigh was felt to be a constant presence in victims\u27 lives until his 2001 execution. Finally, this article will examine family members\u27 and survivors\u27 perceptions of communicative interchange with McVeigh in the venues of the trial and execution. The implications of this case study illustrate in what ways concepts such as victimhood and justice are continually being expanded, with the implication that law is not only a social institution that mediates cultural trauma and cultivates collective memory, but also is manifestly conscious of these roles
The structure of discussion: a discourse analytical approach to the identification of structure in the text type 'discussion'
This study is concerned with the structural analysis of a corpus of discussive data. The data, mainly taken from CANCODE, the Cambridge and Nottingham Corpus of Discourse in English, was taken from a range of situational contexts, along a cline of formality from informal �chat� to public broadcast material. The data was analysed using a version of the Sinclair and Coulthard (1975) model of discourse, which was adapted to deal with spoken discussion, and the resultant analytical framework was described in detail.
Previous studies of discussion and argumentation have looked either at intra-turn structure, or at the local management of disagreement between turns. This study aims to provide an overall analysis of the structure of discussion, with a view to elucidating the argumentative and persuasive strategies used by interactants involved in spontaneous spoken discussion. It is argued that discourse acts can be identified through the study of certain lexico-grammatical items which typically realise them, and that both at act level and at move level elements of structure combine to form a type of patterning which is typical to discussive texts. It is further argued that this patterning reflects various aspects of the �nature� of discussion, such as its combativeness, and the way that interpersonal objectives become less important in this type of interaction. Also the emergent nature of opinion in discussion is reflected in interactants� use of focussing moves and summarising acts, and points of convergence between interactants can be identified through their use of responding moves
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