Implicit Target Research Articles

Chunk Duration Limits the Learning of Multiword Chunks: Behavioral and Electroencephalogram Evidence from Statistical Learning.

Language comprehension involves the grouping of words into larger multiword chunks. This is required to recode information into sparser representations to mitigate memory limitations and counteract forgetting. It has been suggested that electrophysiological processing time windows constrain the formation of these units. Specifically, the period of rhythmic neural activity (i.e., slow-frequency neural oscillations) may set an upper limit of 2-3 sec. Here, we assess whether learning of new multiword chunks is also affected by this neural limit. We applied an auditory statistical learning paradigm of an artificial language while manipulating the duration of to-be-learnt chunks. Participants listened to isochronous sequences of disyllabic pseudowords from which they could learn hidden three-word chunks based on transitional probabilities. We presented chunks of 1.95, 2.55, and 3.15 sec that were created by varying the pause interval between pseudowords. In a first behavioral experiment, we tested learning using an implicit target detection task. We found better learning for chunks of 2.55 sec as compared to longer durations in line with an upper limit of the proposed time constraint. In a second experiment, we recorded participants' electroencephalogram during the exposure phase to use frequency tagging as a neural index of statistical learning. Extending the behavioral findings, results show a significant decline in neural tracking for chunks exceeding 3 sec as compared to both shorter durations. Overall, we suggest that language learning is constrained by endogenous time constraints, possibly reflecting electrophysiological processing windows.

Twin Towers End to End model for aspect-based sentiment analysis

Aspect-based sentiment analysis (ABSA) aims to conduct fine-grained sentiment analysis, necessitating the extraction of three key components: target entity, aspect category and sentiment polarity. These three components collectively form an integrated ABSA task known as TASD (Target-Aspect-Sentiment jointly Detection). Most of existing approaches on ABSA usually employ Recurrent neural networks(RNNs), Convolutional neural networks(CNNs) or pre-training models such as Bidirectional Encoder Representations from Transformers(BERT). However, they have some common weaknesses. First, most of the existing methods focus on one or two sub-tasks instead of triplet detection, thus they do not establish an end-to-end (training a complex learning system represented by a single model) ABSA model and cannot utilize the relevance of multiple ABSA sub-tasks during training. Second, they cannot achieve accuracy and efficiency simultaneously due to the coupling of context and given aspects. Third, they are poor in recognizing implicit targets. To tackle these limitations, this paper proposes a novel method named the Twin Towers End to End model (TTEE) to solve TASD task. It transforms complex TASD task into a simple end-to-end multi-task framework, simultaneously conducting target and aspect-sentiment detection. It builds twin towers system based on BERT or its updated versions to decouple context and given aspects, which can reduce redundant calculation to improve computational efficiency significantly. It offers great advantage to identify implicit target entity and its associated aspect-sentiment in the context without introducing extra model architecture. Experiments on three public datasets in different domains demonstrate that our approach not only achieves better performance on various evaluation metrics, but also has high efficiency in both training and inference phases, over a wide range of sample size and number of aspect categories.

Of words and whistles: Statistical learning operates similarly for identical sounds perceived as speech and non-speech

Statistical learning is an ability that allows individuals to effortlessly extract patterns from the environment, such as sound patterns in speech. Some prior evidence suggests that statistical learning operates more robustly for speech compared to non-speech stimuli, supporting the idea that humans are predisposed to learn language. However, any apparent statistical learning advantage for speech could be driven by signal acoustics, rather than the subjective perception per se of sounds as speech. To resolve this issue, the current study assessed whether there is a statistical learning advantage for ambiguous sounds that are subjectively perceived as speech-like compared to the same sounds perceived as non-speech, thereby controlling for acoustic features. We first induced participants to perceive sine-wave speech (SWS)—a degraded form of speech not immediately perceptible as speech—as either speech or non-speech. After this induction phase, participants were exposed to a continuous stream of repeating trisyllabic nonsense words, composed of SWS syllables, and then completed an explicit familiarity rating task and an implicit target detection task to assess learning. Critically, participants showed robust and equivalent performance on both measures, regardless of their subjective speech perception. In contrast, participants who perceived the SWS syllables as more speech-like showed better detection of individual syllables embedded in speech streams. These results suggest that speech perception facilitates processing of individual sounds, but not the ability to extract patterns across sounds. Our findings suggest that statistical learning is not influenced by the perceived linguistic relevance of sounds, and that it may be conceptualized largely as an automatic, stimulus-driven mechanism.

Development of one translator’s style: A corpus-based investigation of Allan Barr’s style of translating Yu Hua’s works

This paper examines the evolution of translator Allan Barr's style and methodology. Regarded as the primary English translator of Yu Hua's works for fifteen years, Barr's corpus is examined in order to catalogue the development of his translation style. This corpus consists of Yu Hua’s Huanghun li de Nanhai and Siyue Sanri Shijian and their translations Boy in the Twilight: Stories of Hidden China (2003) and The April 3rd Incident: Stories (2018). The mixed-methods approach was applied to analyze Barr's idiosyncrasies in translating Direct Speech (DS) presentations at different stages of his career using the revised S-type model. A quantitative analysis identified a translator’s changing preferences in translating DS. The subsequent qualitative analysis addressed the translation strategies of (Free) Direct Speech and Barr's preferred position of report clauses at different points in time. The results suggest that Barr's translation styles were more influenced by his assumptions and attitude towards the implicit target readers and then dominated his stylistic choices, leading him to be more loyal to the source text and the author in his later translation and more inclined to present the literary world of the source text with less interference and interpretation by the translator. The implications proposed that the development of the translator’s style may be due to the promotion of the author’s familiarity with the literary field of the target language, the influence of the norms of the source language in which the translator is immersed in translation practice, and his increasing knowledge of style.

MOIT: A Novel task for mining opinions towards implicit targets

The extraction of opinions and their corresponding targets has gained significant interest recently, as it offers valuable insights into Opinion Mining (OM) at a granular level. Opinion and target terms to be extracted by existing OM tasks need to be explicitly present in reviews. Targets that are not present but implied in contextual semantics, are neglected by existing OM tasks, even though an investigation reported that about 60% of reviews contain implicit targets. To enable implicit target extraction, a novel task named Mining Opinions towards Implicit Targets (MOIT) under the fine-grained OM, is proposed to extract both opinions and their corresponding implicit targets, enabling a more comprehensive analysis of reviews. To set up the basis for follow-up research on MOIT, two large-scale datasets were constructed as resources in two languages, where the Chinese dataset was built from scratch via a standard human annotation process, and the English dataset was built semi-automatically through machine translation and manual checking. Furthermore, three baseline models adapting three representative paradigms of information extraction, namely sequence labeling, question answering, and text generation, were proposed to solve MOIT. Extensive experiments demonstrated the effectiveness of the models. The proposed MOIT task extends the field of OM research, and the datasets and models establish a foundation for future studies in this area.

‘The friend-making table’: variety and the definition of friendship in Plutarch’sTable Talk

AbstractPlutarch’sTable Talkasserts the ‘friend-making’ (φιλοποιός) character of the symposium seemingly unproblematically (612D, 621C). Yet it is not entirely clear how readers are to understand the dynamics of social variety in the work, or how its presentation of friendship relates to Plutarch’s formal pronouncements elsewhere on the subject. This article explores connections betweenTable Talkand aspects ofOn Having Many FriendsandHow to Tell a Flatterer from a Friend. It also considers some ideas aroundpoikiliain Plutarch in connection to discussions of complexity and simplicity inTable Talk, as a window onto the work’s presentation of amicable variety. I argue that social variety is often the implicit target in discussions of party pragmatics and gastronomic variety. Unlike the moral essays,Table Talkultimately endorses a broad conceptualization of friendship’s and variety’s value, inviting readers to rethink Plutarchan ideas for the sympotic context.

The Effects of Explicit versus Implicit Targets on Worker Performance, Reciprocity, and Trust and the Role of Peer Benchmarking

ABSTRACTWe examine the relative effects of managers using binding targets to reward workers before observing their performance (explicit targets) versus managers deciding whether to reward workers after observing their performance (implicit targets) in the common setting where managers cannot directly observe workers’ effort and ability. In a multiperiod interactive experiment, we find that workers’ performance, positive reciprocity, and trust toward their managers are lower under explicit targets than implicit targets. Evidence suggests that workers under explicit targets withhold effort because managers often set ineffective targets, whereas workers under implicit targets provide close to maximum effort because they trust managers to reward them accordingly. Importantly, providing managers with peer performance benchmark information improves the effectiveness of explicit targets by decreasing target variance and increasing workers’ perceived fairness of the target-setting process. Our results highlight how the type of performance targets and peer performance benchmarking can motivate worker performance and build trust.Data Availability: Data are available upon request.JEL Classifications: D91; J41; M41; M52.

EEG study of attention on an auditory target detection task in dolphins and humans

How do dolphins attend to echos and ignore background noise? Is the process similar to how humans attend to conversations in a crowded room? Studies of human selective attention have highlighted endogenous brain processes modulating the magnitude of early responses to sounds in auditory evoked potentials (AEPs), yet these rely on task-specific instructions difficult to employ in animal studies. We trained an adult male dolphin (Tursiops truncatus) to attend to a stream of rapidly presented tones, and provide a whistle response to a “target” tone while withholding responses to “background” tones in an amplitude discrimination task. The background sounds were designed to function as a tonal mismatch negativity paradigm with two frequencies: a standard tone presented 80% of the time, and a deviant presented 20% of the time. Depending on condition, the target could be the same frequency as the standard or the deviant. We observed an enhanced AEP response to a deviant of the same frequency as the target, while the AEP response to the standard-target condition was reduced. This was not predicted by previous human experiments, and we are currently following up with a pilot a human task modeled after the dolphin implicit target detection task.

Cold shock protein RBM3 is upregulated in the autophagy-deficient brain.

Neural autophagy plays an important role in regulating protein quality control, brain homeostasis, and body temperature. However, the mechanism that links a defect in autophagy to body temperature has not been elucidated. Here, we report that RNA binding motif protein 3 (RBM3) is a potential candidate that regulates body temperature. We found that the body temperatures of Nestin-Cre ; Atg7 f/f conditional KO (cKO) mice were lower than that of wild-type (WT) mice. Moreover, RBM3 was upregulated in the Nestin-Cre ; Atg7 f/f brain. These data suggest that RBM3 is an implicit target that maintains body temperature influenced by neural autophagy.

A Potential Role for Reinforcement Learning in Speech Production.

Reinforcement learning, the ability to change motor behavior based on external reward, has been suggested to play a critical role in early stages of speech motor development and is widely used in clinical rehabilitation for speech motor disorders. However, no current evidence exists that demonstrates the capability of reinforcement to drive changes in human speech behavior. Speech provides a unique test of the universality of reinforcement learning across motor domains: Speech is a complex, high-dimensional motor task whose goals do not specify a task to be performed in the environment but ultimately must be self-generated by each speaker such that they are understood by those around them. Across four experiments, we examine whether reinforcement learning alone is sufficient to drive changes in speech behavior and parametrically test two features known to affect reinforcement learning in reaching: how informative the reinforcement signal is as well as the availability of sensory feedback about the outcomes of one's motor behavior. We show that learning does occur and is more likely when participants receive auditory feedback that gives an implicit target for production, although they do not explicitly imitate that target. Contrary to results from upper limb control, masking feedback about movement outcomes has no effect on speech learning. Together, our results suggest a potential role for reinforcement learning in speech but that it likely operates differently than in other motor domains.

Multi-level knowledge-based approach for implicit aspect identification

Sentiment analysis or opinion mining is the area of research in Natural Language Processing (NLP) and text mining which deals with the systematic identification of subjective information from user generated text. At a more fine-grained level, aspect-based sentiment analysis focuses on the targets of users’ opinions and determining sentiment orientation of these opinions. Among different tasks of aspect-based sentiment analysis, aspect extraction is the key task which includes extraction of both explicit and implicit aspects. Due to the complexity of implicit aspects, not much effort has been put forward to solve the problem while explicit aspects have been studied extensively in the recent past. Existing approaches for implicit aspect extraction have focused on specific type of aspects and have neglected the actual problem. Therefore, in this paper, we have proposed a multi-level approach which identifies implicit aspects using co-occurrence and similarity-based techniques. This research focuses on the extraction of clues for implicit targets of users’ opinions and identification of true targets of users’ opinions with the help of implicit aspect clues. The proposed approach is divided into two phases: first, several rules are crafted to identify clues for implicit aspects in a review sentence. Secondly, aspects are assigned on the basis of extracted clues using proposed multi-level approach. The proposed model can extract not only implicit aspect clues associated with opinion words but also allocate clues to opinion words where no association is identified. This helps to identify implicit aspects with or without co-occurrences of opinion words with explicit aspects. Experimental evaluation elaborates the importance of implicit aspect clues in the identification of targets of users’ opinions. The proposed approach shows better results as compared with the state-of-the-art approaches for the identification of implicit targets of users’ opinions on a dataset of different product reviews.

Target-Aspect-Sentiment Joint Detection for Aspect-Based Sentiment Analysis

Aspect-based sentiment analysis (ABSA) aims to detect the targets (which are composed by continuous words), aspects and sentiment polarities in text. Published datasets from SemEval-2015 and SemEval-2016 reveal that a sentiment polarity depends on both the target and the aspect. However, most of the existing methods consider predicting sentiment polarities from either targets or aspects but not from both, thus they easily make wrong predictions on sentiment polarities. In particular, where the target is implicit, i.e., it does not appear in the given text, the methods predicting sentiment polarities from targets do not work. To tackle these limitations in ABSA, this paper proposes a novel method for target-aspect-sentiment joint detection. It relies on a pre-trained language model and can capture the dependence on both targets and aspects for sentiment prediction. Experimental results on the SemEval-2015 and SemEval-2016 restaurant datasets show that the proposed method achieves a high performance in detecting target-aspect-sentiment triples even for the implicit target cases; moreover, it even outperforms the state-of-the-art methods for those subtasks of target-aspect-sentiment detection that they are competent to.

Dissociable influences of implicit temporal expectation on attentional performance and mind wandering

Mind wandering at critical moments during a cognitive task degrades performance. At other moments, mind wandering could serve to conserve task-relevant resources, allowing a brief mental respite. Recent research has shown that, if target timing is predictable, mind wandering episodes coincide with moments of low target likelihood. Conversely, mind wandering can be avoided at moments when targets are expected. In the current study, we tested whether mind wandering can be guided by implicit temporal expectations when target timing is less predictable. In two experiments (Experiment 1: N = 37, Experiment 2: N = 61), participants performed a sustained attention task in which target events were preceded by a variable pre-target interval (foreperiod). As time passes over the foreperiod duration, implicit target expectation increases, given that it has not yet appeared. In Experiment 1, all foreperiod durations were equally probable (uniform distribution: 2–10 s). This resulted in faster responses when targets were preceded by long compared to short foreperiods (foreperiod-effect). In contrast, mind wandering, assessed by thought probes inserted following short or long foreperiods, did not follow this pattern. In Experiment 2, alterations in the foreperiod distribution (left or right-skewed) resulted in changes in the behavioral foreperiod-effect, but mind wandering was unaffected. Our findings indicate that implicit timing strongly affects behavioral response to target events, but has no bearing on the mind wandering. Contrastingly, mind wandering did correlate with performance deterioration due to fatigue (time-on-task), suggesting that the thought probe method was sufficiently sensitive to behaviorally relevant changes in mental state.

User Preference Adaptive Fitness of Interactive Genetic Algorithm Based Ceramic Disk Pattern Generation Method

Pattern design in real life is a complex optimization challenge that objective function can not express explicitly, and can be classified as an implicit target optimization problem. Owing to the fact that the objective function in implicit target optimization problem can not be completely structured, the traditional intelligent decision optimization method is inapplicable. This paper proposes an interactive genetic algorithm based on user preference adaptive fitness, in which users actively participate in optimization and take their subjective evaluation value as the adaptive fitness of evolutionary individuals. On the basis of adjusting the tone coordination degree of ceramic disc pattern, the improved method gives the calculation of user interest degree and style similarity, and completes the establishment of user preference model. The individual similarity calculation of the algorithm integrates the user preference information, making the calculation result more objective. In the experiment, the grain genes of ceramic disc pattern can be divided into two types: main body and border, both of which can be encoded by 16-bit binary code strings. And the weight values of style, tone collocation and structure were set respectively, and the ceramic disc patterns of modern fashion and fresh styles were obtained. In addition, the algorithm performance comparison is also completed. The experimental results show that with the progress of evolution, the midpoint and average width of the fitness of the population decrease, and the population quality is improved. Our algorithm can generate ceramic disc patterns of different styles, and the algorithm can obtain more satisfactory solutions in less evolutionary generations, which speeds up the algorithm's convergence speed and shows better evolutionary optimization ability.

Adaptive matched filter for implicit-target recognition: application in three-dimensional reconstruction.

The design of matched filters for optical correlators requires explicit knowledge of the shape of the target. This requirement limits its usefulness in applications where the appearance of the target is unspecified or dynamically changing. This research presents the design of an adaptive correlation filter by the optimization of the mean-squared-error criterion when the shape of the target is implicit and embedded on a cluttered background with unknown statistics in the reference image. For this, estimators to obtain the region of support of the target as well as statistical parameters of additive and nonoverlapping noise of the scene are proposed. The performance of the proposed filter is analyzed in terms of detection efficiency and location accuracy of an implicit target in the context of stereo matching and three-dimensional reconstruction.

EMPIRICAL ANALYSIS OF FOREIGN EXCHANGE VOLATILITY AND RATIONAL EXPECTATIONS ON CENTRAL BANK TRANSPARENCY

Today the Central Bank actions are under a big scrutiny from economic agents and government. Thus, it has been raised the question of the reasonable level of regulator’s openness. Under risen volatility in the foreign exchange rateand range of fi nancial variables it has openedthe question of rebuilding a current communication policy of monetary authority with the aim to maintain the confi dence of economic agents that supporting price stability is the prior taskof Central Bank. Also irrational behavior of agents can lead to failure of conducting monetary policy of Central Bank. Therefore, more magnitude of volatility in fi nancial variables evokes less transparent dealing of Central bank, while onepursues monetary policy strategy. Th at is why in this paper empirical relationship between risen volatility magnitude, providing the implicit target, maintaining price stability target on a one hand and openness in economic, political, procedural, monetary and operational aspects of regulator transparency in an another will be considered and discussed.

A Critical Review of the Compulsory Schooling Reform in England and its Lasting Implications for Today

This article aims to examine the implicit and explicit motivations behind the compulsory schooling reform in England as well as its unintended and long–term effects by analysing publicly available policy documents and key scholarly literature. The analysis indicates that even though the 19th century’s schooling project appeared to focus on pursuing some explicit goals, such as creating more qualified and educated labour force and citizens with religious and moral values, in reality it hides several implicit targets, such as controlling the working–class and maintaining the class segregation. Moreover, this article points out the unintended effects of the compulsory schooling reform, including low attendance in schools, low quality of education, increasing demand for higher education and Church resistance, as well as its long–term effects existing in today’s English education system, namely the continuing class segregation and evolving state and Church partnership.

Social Welfare Discourses and Scholars’ Ethical-Political Dilemmas in the Crisis of Neoliberalism

ABSTRACTDiscourse is central in promoting – or hindering – social change. This paper discusses the ethical-political dilemmas that academics face in developing progressive discourses on social welfare in the hegemonic crisis of neoliberalism. A central dilemma concerns the (implicit or explicit) target of their discourse. Speaking to elites reproduces dominant values and interests, reinforcing central elements of neoliberalism such as economisation and de-politicisation. Moreover, this approach remains technocratic (i.e. academics act as experts), thereby failing to address citizens’ distrust towards ‘scientific evidence’ that characterises the hegemonic crisis of neoliberalism. A possible alternative is to work together with civil society and marginalised groups for promoting an oppositional discourse. In this way scholars may contribute to the democratisation of the public sphere but may fail to influence the content of policies, remaining trapped in marginal political positions. The paper illustrates this tension focusing on ‘social investment’. This discourse – which is today the most important framework for welfare reform among academics – emphasises the economic benefits of social policy for promoting alternatives to welfare retrenchment. Building on a research project aimed at re-thinking social investment from Sen's capability perspective, the paper discusses the conditions for developing a post-neoliberal discourse on social welfare.

Capital Flows and Foreign Exchange Intervention

I consider a small open economy model where international financial markets are imperfect and the exchange rate is determined by capital flows. I use this framework to study the effects of portfolio flow shocks, derive the optimal foreign exchange intervention policy, and characterize its interaction with monetary policy. I derive the optimal intervention rule in closed form as a function of three implicit targets. Finally, using Swiss data, I estimate the model to quantify the inefficiencies generated by capital flow shocks and the optimal size of the intervention. (JEL E44, E52, E63, F31, F32, F33, F41)

Cogitor Ergo Sum: The Origin of Self-awareness in Dyadic Interaction

When I see a mountain to be far away, there is non-reflective awareness of myself as that from which distance is measured. Likewise, there is self-awareness when I see a tree as offering shade or a hiding place. In such cases, how can the self I am aware of be the same as I who am aware of it? Can the perceived be its perceiver? Mobilizing infancy research, I offer the following thesis as to how one can be aware of oneself, at a single stroke, as perceiver and as embodied entity. During face-to-face interaction at 2 or 3 months, the infant has a sensuous perception of the caregiver as well as a non-sensuous impression of something she is eyeing and vocalizing toward. This implicit target is the self as it first becomes present to the child. It is shown how the target of her attending is experienced by him as embodied, active, affective, and continuous. After acquiring language, however, the child becomes capable of playing the caregiver toward himself: He can speak in her manner while listening as the one addressed. Thus the relation is internalized. The outcome is the independent and secure self-awareness that typifies post-infancy life. Independence bears a price, which is assessed.