19,086 research outputs found

    One Small Step for Generative AI, One Giant Leap for AGI: A Complete Survey on ChatGPT in AIGC Era

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    OpenAI has recently released GPT-4 (a.k.a. ChatGPT plus), which is demonstrated to be one small step for generative AI (GAI), but one giant leap for artificial general intelligence (AGI). Since its official release in November 2022, ChatGPT has quickly attracted numerous users with extensive media coverage. Such unprecedented attention has also motivated numerous researchers to investigate ChatGPT from various aspects. According to Google scholar, there are more than 500 articles with ChatGPT in their titles or mentioning it in their abstracts. Considering this, a review is urgently needed, and our work fills this gap. Overall, this work is the first to survey ChatGPT with a comprehensive review of its underlying technology, applications, and challenges. Moreover, we present an outlook on how ChatGPT might evolve to realize general-purpose AIGC (a.k.a. AI-generated content), which will be a significant milestone for the development of AGI.Comment: A Survey on ChatGPT and GPT-4, 29 pages. Feedback is appreciated ([email protected]

    Ausubel's meaningful learning re-visited

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    This review provides a critique of David Ausubel’s theory of meaningful learning and the use of advance organizers in teaching. It takes into account the developments in cognition and neuroscience which have taken place in the 50 or so years since he advanced his ideas, developments which challenge our understanding of cognitive structure and the recall of prior learning. These include (i) how effective questioning to ascertain previous knowledge necessitates in-depth Socratic dialogue; (ii) how many findings in cognition and neuroscience indicate that memory may be non-representational, thereby affecting our interpretation of student recollections; (iii) the now recognised dynamism of memory; (iv) usefully regarding concepts as abilities or simulators and skills; (v) acknowledging conscious and unconscious memory and imagery; (vi) how conceptual change involves conceptual coexistence and revision; (vii) noting linguistic and neural pathways as a result of experience and neural selection; and (viii) recommending that wider concepts of scaffolding should be adopted, particularly given the increasing focus on collaborative learning in a technological world

    Exploring the Training Factors that Influence the Role of Teaching Assistants to Teach to Students With SEND in a Mainstream Classroom in England

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    With the implementation of inclusive education having become increasingly valued over the years, the training of Teaching Assistants (TAs) is now more important than ever, given that they work alongside pupils with special educational needs and disabilities (hereinafter SEND) in mainstream education classrooms. The current study explored the training factors that influence the role of TAs when it comes to teaching SEND students in mainstream classrooms in England during their one-year training period. This work aimed to increase understanding of how the training of TAs is seen to influence the development of their personal knowledge and professional skills. The study has significance for our comprehension of the connection between the TAs’ training and the quality of education in the classroom. In addition, this work investigated whether there existed a correlation between the teaching experience of TAs and their background information, such as their gender, age, grade level taught, years of teaching experience, and qualification level. A critical realist theoretical approach was adopted for this two-phased study, which involved the mixing of adaptive and grounded theories respectively. The multi-method project featured 13 case studies, each of which involved a trainee TA, his/her college tutor, and the classroom teacher who was supervising the trainee TA. The analysis was based on using semi-structured interviews, various questionnaires, and non-participant observation methods for each of these case studies during the TA’s one-year training period. The primary analysis of the research was completed by comparing the various kinds of data collected from the participants in the first and second data collection stages of each case. Further analysis involved cross-case analysis using a grounded theory approach, which made it possible to draw conclusions and put forth several core propositions. Compared with previous research, the findings of the current study reveal many implications for the training and deployment conditions of TAs, while they also challenge the prevailing approaches in many aspects, in addition to offering more diversified, enriched, and comprehensive explanations of the critical pedagogical issues

    Quantifying the retention of emotions across story retellings

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    Story retelling is a fundamental medium for the transmission of information between individuals and among social groups. Besides conveying factual information, stories also contain affective information. Though natural language processing techniques have advanced considerably in recent years, the extent to which machines can be trained to identify and track emotions across retellings is unknown. This study leverages the powerful RoBERTa model, based on a transformer architecture, to derive emotion-rich story embeddings from a unique dataset of 25,728 story retellings. The initial stories were centered around five emotional events (joy, sadness, embarrassment, risk, and disgust—though the stories did not contain these emotion words) and three intensities (high, medium, and low). Our results indicate (1) that RoBERTa can identify emotions in stories it was not trained on, (2) that the five emotions and their intensities are preserved when they are transmitted in the form of retellings, (3) that the emotions in stories are increasingly well-preserved as they experience additional retellings, and (4) that among the five emotions, risk and disgust are least well-preserved, compared with joy, sadness, and embarrassment. This work is a first step toward quantifying situation-driven emotions with machines

    The role of alerting in the attentional boost effect

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    Stimuli presented simultaneously with behaviorally relevant events (e.g., targets) are better memorized, an unusual effect defined as the attentional boost effect (ABE). We hypothesized that all types of behaviorally relevant events, including attentional cues, can promote the encoding process for the stimuli paired with them, and the attentional alerting network can amplify the ABE. The two experiments we conducted demonstrated that not all behaviorally relevant events, including alerting cues, benefit the processing of concurrently paired stimuli. We also found that the presence of a cue prior to a target can extend the memory advantage produced by target detection, but this advantage can only be observed within a limited range of time. Overall, our study provides the first evidence that the alerting network plays an important role in the ABE

    Genomic diversity and metabolic potential of marine Pseudomonadaceae

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    Recent changes in the taxonomy of the Pseudomonadaceae family have led to the delineation of three new genera (Atopomonas, Halopseudomonas and Stutzerimonas). However, the genus Pseudomonas remains the most densely populated and displays a broad genetic diversity. Pseudomonas are able to produce a wide variety of secondary metabolites which drives important ecological functions and have a great impact in sustaining their lifestyles. While soilborne Pseudomonas are constantly examined, we currently lack studies aiming to explore the genetic diversity and metabolic potential of marine Pseudomonas spp. In this study, 23 Pseudomonas strains were co-isolated with Vibrio strains from three marine microalgal cultures and rpoD-based phylogeny allowed their assignment to the Pseudomonas oleovorans group (Pseudomonas chengduensis, Pseudomonas toyotomiensis and one new species). We combined whole genome sequencing on three selected strains with an inventory of marine Pseudomonas genomes to assess their phylogenetic assignations and explore their metabolic potential. Our results revealed that most strains are incorrectly assigned at the species level and half of them do not belong to the genus Pseudomonas but instead to the genera Halopseudomonas or Stutzerimonas. We highlight the presence of 26 new species (Halopseudomonas (n = 5), Stutzerimonas (n = 7) and Pseudomonas (n = 14)) and describe one new species, Pseudomonas chaetocerotis sp. nov. (type strain 536T = LMG 31766T = DSM 111343T). We used genome mining to identify numerous BGCs coding for the production of diverse known metabolites (i.e., osmoprotectants, photoprotectants, quorum sensing molecules, siderophores, cyclic lipopeptides) but also unknown metabolites (e.g., ARE, hybrid ARE-DAR, siderophores, orphan NRPS gene clusters) awaiting chemical characterization. Finally, this study underlines that marine environments host a huge diversity of Pseudomonadaceae that can drive the discovery of new secondary metabolites

    Procedure-Aware Pretraining for Instructional Video Understanding

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    Our goal is to learn a video representation that is useful for downstream procedure understanding tasks in instructional videos. Due to the small amount of available annotations, a key challenge in procedure understanding is to be able to extract from unlabeled videos the procedural knowledge such as the identity of the task (e.g., 'make latte'), its steps (e.g., 'pour milk'), or the potential next steps given partial progress in its execution. Our main insight is that instructional videos depict sequences of steps that repeat between instances of the same or different tasks, and that this structure can be well represented by a Procedural Knowledge Graph (PKG), where nodes are discrete steps and edges connect steps that occur sequentially in the instructional activities. This graph can then be used to generate pseudo labels to train a video representation that encodes the procedural knowledge in a more accessible form to generalize to multiple procedure understanding tasks. We build a PKG by combining information from a text-based procedural knowledge database and an unlabeled instructional video corpus and then use it to generate training pseudo labels with four novel pre-training objectives. We call this PKG-based pre-training procedure and the resulting model Paprika, Procedure-Aware PRe-training for Instructional Knowledge Acquisition. We evaluate Paprika on COIN and CrossTask for procedure understanding tasks such as task recognition, step recognition, and step forecasting. Paprika yields a video representation that improves over the state of the art: up to 11.23% gains in accuracy in 12 evaluation settings. Implementation is available at https://github.com/salesforce/paprika.Comment: CVPR 202

    Seer: Language Instructed Video Prediction with Latent Diffusion Models

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    Imagining the future trajectory is the key for robots to make sound planning and successfully reach their goals. Therefore, text-conditioned video prediction (TVP) is an essential task to facilitate general robot policy learning, i.e., predicting future video frames with a given language instruction and reference frames. It is a highly challenging task to ground task-level goals specified by instructions and high-fidelity frames together, requiring large-scale data and computation. To tackle this task and empower robots with the ability to foresee the future, we propose a sample and computation-efficient model, named \textbf{Seer}, by inflating the pretrained text-to-image (T2I) stable diffusion models along the temporal axis. We inflate the denoising U-Net and language conditioning model with two novel techniques, Autoregressive Spatial-Temporal Attention and Frame Sequential Text Decomposer, to propagate the rich prior knowledge in the pretrained T2I models across the frames. With the well-designed architecture, Seer makes it possible to generate high-fidelity, coherent, and instruction-aligned video frames by fine-tuning a few layers on a small amount of data. The experimental results on Something Something V2 (SSv2) and Bridgedata datasets demonstrate our superior video prediction performance with around 210-hour training on 4 RTX 3090 GPUs: decreasing the FVD of the current SOTA model from 290 to 200 on SSv2 and achieving at least 70\% preference in the human evaluation.Comment: 17 pages, 15 figure

    Molecular diagnosis of Mycoplasma bovis

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    Dissertação de Mestrado Integrado em Medicina VeterináriaMycoplasma bovis is a bacteria responsible for different disease presentations in cattle, such as pneumonia, mastitis, otitis, genital disorders, keratoconjuntivitis and arthritis, presently considered as one of the major emerging pathogens affecting cattle. Until this day, it is responsible for losses in animal production of over 150 million euros across Europe. The pathogenesis of Mycoplasma-associated diseases is multifactorial and the highly variable surface lipoproteins allows a fast and efficient dissemination of M. bovis within the host and the herd. Due to its high antigenic plasticity, its ability to survive within multiple host cells and the capacity to establish multiple synergistic interactions with other pathogens, makes M. bovis and associated infections are a major challenge in Veterinary Medicine, since the vaccine is not efficient and antibiotics are almost inefficient. This study aims at developing and validating a quantitative PCR protocol for the diagnosis of M. bovis. 93 milk samples, from 5 different Portuguese farms, were collected, processed and each one’s DNA extracted to be analyzed through a qPCR method targeting the uvrC and uvrC2024 genes. Given the percentage of positivity, which was high, the conclusion we can take from the study is that there is still work to do, in terms of establishing a uniformed practice to tackle the wide presence of M. bovis in farms.RESUMO - Diagnóstico Molecular de M. bovis - Mycoplasma bovis é uma bactéria cuja infecção pode ter diferentes apresentações tais como pneumonia, mastite, otite, afecções genitais, queratoconjuntivite e artrites. É um dos agentes considerados emergentes e que afecta a produção agropecuária, sendo responsável por perdas na ordem dos 150 milhões de euros na Europa. Tem uma patogénese multifactorial e as proteínas membranares à sua superfície conferem uma variabilidade que permite uma rápida e eficiente disseminação no hospedeiro, e no rebanho. Esta variabilidade e capacidade de resistir à imunidade do hospedeiro, assim como as suas interacções sinérgicas com outros agentes patogénicos, tornam as infecções por M. bovis um obstáculo difícil de conter e ultrapassar na Medicina Veterinária, isto porque quer a antibioterapia, quer a vacina, não são eficientes. Este estudo procura desenvolver e contribuir para o estabelecimento de um protocolo de diagnóstico para a detecção de M. bovis. Vindas de 5 produções portuguesas diferentes, 93 amostras foram processadas e analisadas através de um qPCR, com os genes uvrC e uvrC2024 como genes alvo. Dados os resultados, com uma positividade significativa pode-se considerar que ainda há trabalho pela frente em termos de estabelecer e uniformizar uma prática para combater a larga presença de M. bovis nas explorações.N/

    Strategies for Early Learners

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    Welcome to learning about how to effectively plan curriculum for young children. This textbook will address: • Developing curriculum through the planning cycle • Theories that inform what we know about how children learn and the best ways for teachers to support learning • The three components of developmentally appropriate practice • Importance and value of play and intentional teaching • Different models of curriculum • Process of lesson planning (documenting planned experiences for children) • Physical, temporal, and social environments that set the stage for children’s learning • Appropriate guidance techniques to support children’s behaviors as the self-regulation abilities mature. • Planning for preschool-aged children in specific domains including o Physical development o Language and literacy o Math o Science o Creative (the visual and performing arts) o Diversity (social science and history) o Health and safety • Making children’s learning visible through documentation and assessmenthttps://scholar.utc.edu/open-textbooks/1001/thumbnail.jp
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