Learning to Infer from Unlabeled Data: A Semi-supervised Learning Approach for Robust Natural Language Inference

Natural Language Inference (NLI) or Recognizing Textual Entailment (RTE) aims at predicting the relation between a pair of sentences (premise and hypothesis) as entailment, contradiction or semantic independence. Although deep learning models have shown promising performance for NLI in recent years, they rely on large scale expensive human-annotated datasets. Semi-supervised learning (SSL) is a popular technique for reducing the reliance on human annotation by leveraging unlabeled data for training. However, despite its substantial success on single sentence classification tasks where the challenge in making use of unlabeled data is to assign "good enough" pseudo-labels, for NLI tasks, the nature of unlabeled data is more complex: one of the sentences in the pair (usually the hypothesis) along with the class label are missing from the data and require human annotations, which makes SSL for NLI more challenging. In this paper, we propose a novel way to incorporate unlabeled data in SSL for NLI where we use a conditional language model, BART to generate the hypotheses for the unlabeled sentences (used as premises). Our experiments show that our SSL framework successfully exploits unlabeled data and substantially improves the performance of four NLI datasets in low-resource settings. We release our code at: https://github.com/msadat3/SSL_for_NLI.Comment: Accepted in EMNLP 2022 (Findings

Hierarchical Multi-Label Classification of Scientific Documents

Automatic topic classification has been studied extensively to assist managing and indexing scientific documents in a digital collection. With the large number of topics being available in recent years, it has become necessary to arrange them in a hierarchy. Therefore, the automatic classification systems need to be able to classify the documents hierarchically. In addition, each paper is often assigned to more than one relevant topic. For example, a paper can be assigned to several topics in a hierarchy tree. In this paper, we introduce a new dataset for hierarchical multi-label text classification (HMLTC) of scientific papers called SciHTC, which contains 186,160 papers and 1,233 categories from the ACM CCS tree. We establish strong baselines for HMLTC and propose a multi-task learning approach for topic classification with keyword labeling as an auxiliary task. Our best model achieves a Macro-F1 score of 34.57% which shows that this dataset provides significant research opportunities on hierarchical scientific topic classification. We make our dataset and code available on Github.Comment: Accepted in EMNLP 2022 main conferenc

Prevalence of Fimeria funduli (Protozoa: Eimeriidae) in the Longnose Killifish Fundulus similis from Horn Island, Mississippi

Eimeria funduli occurred in Fundulus similis from Horn Island, Mississippi, during 1980, in contrast with its apparent absence during 1978 and 1979. Prevalence of the parasite appears to be related to the unusually low salinity in Mississippi Sound, and in ponds and off the beaches of Horn Island. The low salinity may have promoted the migration of infective intermediate hosts from inshore waters to the island

A Selected Bibliography on the Mass Propagation of Rotifers with Emphasis on the Biology and Culture of Brachionus plicatilis

The rotifer Brachionus plicatilis has shown great promise as food for artificially reared fish and crustacean larvae. A list of references on mass propagation of rotifers is presented alphabetically by author. Citations cover and are indexed as culture, diet, ecology, physiology, population dynamics, reproduction, systematics, geographical distribution, food, and biology of rotifers with emphasis on Brachionus plicatilis

Evaluation of Flow-Through, Static, and Recirculating Systems for the Intensive Culture of the Gulf Killifish Fundulus grandis with Observations on a Solar-Heated Recirculating System for the Bait Industry

Three systems (flow-through, static, and recirculating) for intensive culture of the Gulf killifish (Fundulus grandis) for bait were evaluated. The outdoor recirculating system proved most successful. Killifish maintained in this system attained an average weight of over 2.0 gm in 42 days, an acceptable market size. Whereas the solar-heated recirculating system sustained fish densities equivalent to 1,000,000/ha and a survival rate of 86%, growth of killifish in this system was less than that observed in both the static and outdoor recirculating systems. Algae appeared to be an important nutritional component of the diet of juvenile killifish. Individuals of F. grandis fed diets supplemented with algae grew better than those maintained without them

Preliminary Observations of the Effect of Eimeria funduli (Protozoa: Eimeriidae) on the Gulf Killifish Fundulus grandis and Its Potential Impact on the Killifish Bait Industry

Liver infections of Eimeria funduli, a pathogenic coccidium, greatly affected growth of Fundulus grandis (Gulf killifish) maintained in an aquaculture facility for 55 days. At termination of the experiment, average weight gained by uninfected killifish was 877.5% compared to 308.0% in diseased fish. There appeared to be no correlation between mortality and disease in this study

Prevalence of Fimeria funduli (Protozoa: Eimeriidae) in the Longnose Killifish Fundulus similis from Horn Island, Mississippi

Eimeria funduli occurred in Fundulus similis from Horn Island, Mississippi, during 1980, in contrast with its apparent absence during 1978 and 1979. Prevalence of the parasite appears to be related to the unusually low salinity in Mississippi Sound, and in ponds and off the beaches of Horn Island. The low salinity may have promoted the migration of infective intermediate hosts from inshore waters to the island

Hesitant Probabilistic Fuzzy Preference Relations in Decision Making

Preference of an alternative over another alternative is a useful way to express the opinion of decision maker. In the process of group decision making, preference relations are used in preference modelling of the alternatives under given criteria. The probability is an important tool to deal with uncertainty; in many scenarios of decision making probabilities of different events affect the decision making process directly. In order to deal with this issue, in this paper, hesitant probabilistic fuzzy preference relation (HPFPR) is defined. Furthermore, consistency of HPFPR and consensus among decision makers are studied in the hesitant probabilistic fuzzy environment. In this respect, many novel algorithms are developed to achieve consistency of HPFPRs and reasonable consensus between decision makers and a final algorithm is proposed comprehending all other algorithms, presenting a complete decision support model for group decision making. Lastly, we present a case study with complete illustration of the proposed model and discussed the effects of probabilities on decision making validating the importance of the introduction of probability in hesitant fuzzy preference relation

Epikrise i hånden: Bedre enn 10 i systemet?

Bakgrunn/emne: Brukermedvirkning og samhandling er viktige satsningsområder i arbeidet for å sikre god pasientsikkerhet og kvalitet i helsevesenet. Å involvere pasienten i egen sykdom og behandling, samt sikre at denne informasjonen raskt formidles mellom første- og annenlinjetjenesten, er nødvendig for å kunne bedre pasientsikkerheten. Epikrisen er et sentralt verktøy for å oppnå dette. Vi ønsker å undersøke hvordan innføring av ”epikrise i hånden” (EIH) til pasienten ved utskrivelse fra sykehusavdeling påvirker epikrisetid og pasienttilfredshet, og se på hvilke tiltak som kan være aktuelle for å gjennomføre dette. Kunnskapsgrunnlag: Ved litteratursøk fant vi gode erfaringer fra gjennomføring av EIH i Norge. Pasientene ønsker å motta informasjonen som er i epikrisen, de fleste opplever bedre egenhelse, og er mer fornøyde med behandlingen. Epikrisetiden har gjennomgående blitt betraktelig redusert og kommunikasjonen med andrelinjetjenesten har blitt styrket. Begrunnet tiltak og metode: Vi søkte i tilgjengelig litteratur, intervjuet leger i kliniske avdelinger og benyttet oss av egne erfaringer fra praksisperioden i 10.semester. Avhengig av avdelingens eksisterende rutiner og arbeidsverktøy, vil vi foreslå flere mindre tiltak. Både talegjenkjenning, digital diktering, omorganisering av sekretærtjenesten og endring av arbeidsflyten i avdelingen kan være aktuelt, sammen eller hver for seg, tilpasset de ulike avdelingers rammevilkår. Organisering: Forslaget vårt er at det i den aktuelle avdelingen nedsettes en tverrfaglig prosjektgruppe, som etter et PDSA-mønster implementerer EIH som utskrivelsespraksis i en prøveperiode. Etter prøveperioden må arbeidsgruppen vurdere effektene av tiltaket, og vurdere om det er ønskelig å implementere EIH som fast praksis. Resultater/vurdering: Målet med å innføre EIH er todelt: at pasienten blir mer involvert i egen helse og behandling, samt å øke andelen epikriser som sendes ut i løpet av den nasjonale syvdagersfristen slik at kommunikasjonen mellom ulike nivåer i helsetjenesten bedres. Begge delmål bidrar til økt pasientsikkerhet. Mål på førstnevnte vil være økt pasienttilfredshet, målt kvalitativt ved et strukturert spørreskjema. Epikrisetiden kan raskt kontrolleres ved å sjekke utsendelsesdatoen opp mot utskrivelsesdato, noe som er et indirekte mål på hvorvidt EIH er gjennomført