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What is the capital of Australia and when was it founded?
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The capital of Australia is Canberra. It was formally founded and named in 1913. The creation of Canberra followed a lengthy dispute over whether Sydney or Melbourne should be the capital. The word "Canberra" is derived from the name of the indigenous Ngunnawal clan who have resided on the land for over 21,000 years.
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When building a piece of furniture, categorize each of the following as either "useful" or "not useful": Hammer, Asphalt, Gym, Wood, Nails, Tequila, Measuring Tape, Burrito
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Hammer: Useful
Asphalt: Not Useful
Gym: Not Useful
Wood: Useful
Nails: Useful
Tequila: Not Useful
Measuring Tape: Useful
Burrito: Not Useful
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Think of a bunch of different ways you could lift weights at home without any dumbbells or gym equipment.
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1. Bodyweight training: Bodyweight training (calisthenics) is the easiest way to train at home without any gym equipment. It can help you build muscle mass and increase your strength.
2. Backpack: You can fill a backpack with books or other heavy things at home and use it instead of weights.
3. Plastic bottles: fill plastic bottles with water and duck tape them together. With a box of 6 x 2 L plastic bottles fully filled with water, you will have 12 KG of weights.
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What are the boroughs of New York City?
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There are five boroughs in New York City (NYC). The five boroughs are Manhattan, Brooklyn, Queens, the Bronx, and Staten Island.
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2001.08051
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It is worth mentioning that the collected texts contain a large quantity of errors of several types: orthographic, syntactic, code-switched words (i.e. words not in the required language), jokes, etc. Hence, the original written sentences have been processed in order to produce “cleaner” versions, in order to make the data usable for some research purposes (e.g. to train language models, to extract features for proficiency assessment, ...).
It is worth mentioning that the collected texts contain a large quantity of errors of several types: orthographic, syntactic, code-switched words (i.e. words not in the required language), jokes, etc. Hence, the original written sentences have been processed in order to produce “cleaner” versions, in order to make the data usable for some research purposes (e.g. to train language models, to extract features for proficiency assessment, ...).
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Are any of the utterances ungrammatical?
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Yes.
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Best sports in the world
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F1. F1 is best sport in the world because it has most adrenaline rush and people like Pace and speed.
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Dried fruit is fruit from which the majority of the original water content has been removed either naturally, through sun drying, or through the use of specialized dryers or dehydrators. Dried fruit has a long tradition of use dating back to the fourth millennium BC in Mesopotamia, and is prized because of its sweet taste, nutritive value and long shelf life.
Today, dried fruit consumption is widespread. Nearly half of the dried fruits sold are raisins, followed by dates, prunes, figs, apricots, peaches, apples, and pears. These are referred to as "conventional" or "traditional" dried fruits: fruits that have been dried in the sun or in heated wind tunnel dryers. Many fruits such as cranberries, blueberries, cherries, strawberries, and mango are infused with a sweetener (e.g. sucrose syrup) prior to drying. Some products sold as dried fruit, like papaya, kiwifruit and pineapple, are most often candied fruit.
Dried fruits retain most of the nutritional value of fresh fruits. The specific nutrient content of the different dried fruits reflects their fresh counterpart and the processing method.
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Which fruits are often infused with a sweetener prior to drying?
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Many fruits such as cranberries, blueberries, cherries, strawberries, and mango are infused with a sweetener (e.g. sucrose syrup) prior to drying.
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Hera (Ἥρα, Hḗra)
Queen of the gods, and goddess of women, marriage, childbirth, heirs, kings, and empires. She is the goddess of the sky, the wife and sister of Zeus, and the daughter of Cronus and Rhea. She was usually depicted as a regal woman in the prime of her life, wearing a diadem and veil and holding a lotus-tipped staff. Although she is the goddess of marriage, Zeus's many infidelities drive her to jealousy and vengefulness. Her sacred animals include the heifer, the peacock, and the cuckoo. Her Roman counterpart is Juno.
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From the passage identify the sacred animals of Hera. Display the results in a comma separated format.
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heifer, the peacock, the cuckoo
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Which one is good for health coffee or tea
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Both coffee and tea are not good for health but overall when you compare coffee with tea, tea is little better than coffee as coffee contains more caffeine content than tea. Drinking both should be limited to 1-2 times per day as anything over consuming is not good for health.
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Classify each country as Nordic or Iberian: Spain, Norway, Sweden, Denmark, Portugal
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Spain: Iberian
Norway: Nordic
Sweden: Nordic
Denmark: Nordic
Portugal: Iberian
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Chromosomal deletion syndromes result from deletion of parts of chromosomes. Depending on the location, size, and whom the deletion is inherited from, there are a few known different variations of chromosome deletions. Chromosomal deletion syndromes typically involve larger deletions that are visible using karyotyping techniques. Smaller deletions result in Microdeletion syndrome, which are detected using fluorescence in situ hybridization (FISH)
Examples of chromosomal deletion syndromes include 5p-Deletion (cri du chat syndrome), 4p-Deletion (Wolf–Hirschhorn syndrome), Prader–Willi syndrome, and Angelman syndrome.
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What is Chromosomal Deletion Syndrome?
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Chromosomal deletion syndromes result from deletion of parts of chromosomes. Depending on the location, size, and whom the deletion is inherited from, there are a few known different variations of chromosome deletions. Chromosomal deletion syndromes typically involve larger deletions that are visible using karyotyping techniques. Smaller deletions result in Microdeletion syndrome, which are detected using fluorescence in situ hybridization (FISH)
Examples of chromosomal deletion syndromes include 5p-Deletion (cri du chat syndrome), 4p-Deletion (Wolf–Hirschhorn syndrome), Prader–Willi syndrome, and Angelman syndrome.
The chromosomal basis of Cri du chat syndrome consists of a deletion of the most terminal portion of the short arm of chromosome 5. 5p deletions, whether terminal or interstitial, occur at different breakpoints; the chromosomal basis generally consists of a deletion on the short arm of chromosome 5. The variability seen among individuals may be attributed to the differences in their genotypes. With an incidence of 1 in 15,000 to 1 in 50,000 live births, it is suggested to be one of the most common contiguous gene deletion disorders. 5p deletions are most common de novo occurrences, which are paternal in origin in 80–90% of cases, possibly arising from chromosome breakage during gamete formation in males.
Some examples of the possible dysmorphic features include: downslanting palpebral fissures, broad nasal bridge, microcephaly, low-set ears, preauricular tags, round faces, short neck, micrognathia, and dental malocclusionhypertelorism, epicanthal folds, downturned corners of the mouth. There is no specific correlation found between size of deletion and severity of clinical features because the results vary so widely.
The chromosomal basis of Wolf-Hirschhorn syndrome (WHS) consists of a deletion of the most terminal portion of the short arm of chromosome 4. The deleted segment of reported individuals represent about one half of the p arm, occurring distal to the bands 4p15.1-p15.2. The proximal boundary of the WHSCR was defined by a 1.9 megabase terminal deletion of 4p16.3. This allele includes the proposed candidate genes LEMT1 and WHSC1. This was identified by two individuals that exhibited all 4 components of the core WHS phenotype, which allowed scientists to trace the loci of the deleted genes. Many reports are particularly striking in the appearance of the craniofacial structure (prominent forehead, hypertelorism, the wide bridge of the nose continuing to the forehead) which has led to the descriptive term “Greek warrior helmet appearance".
There is wide evidence that the WHS core phenotype (growth delay, intellectual disability, seizures, and distinctive craniofacial features) is due to haploinsufficiency of several closely linked genes as opposed to a single gene. Related genes that impact variation include:
WHSC1 spans a 90-kb genomic region, two-thirds of which maps in the telomeric end of the WHCR; WHSC1 may play a significant role in normal development. Its deletion likely contributes to the WHS phenotype. However, variation in severity and phenotype of WHS suggests possible roles for genes that lie proximally and distally to the WHSCR.
WHSC2 (also known as NELF-A) is involved in multiple aspects of mRNA processing and the cell cycle
SLBP, a gene encoding Stem Loop Binding Protein, resides telomeric to WHSC2, and plays a crucial role in regulating histone synthesis and availability during S phase.
LETM1 has initially been proposed as a candidate gene for seizures; it functions in ion exchange with potential roles in cell signaling and energy production.
FGFRL1, encoding a putative fibroblast growth factor decoy receptor, has been implicated in the craniofacial phenotype and potentially other skeletal features, and short stature of WHS.
CPLX1 has lately been suggested as a potential candidate gene for epilepsy in WHS.
Prader–Willi (PWS) and Angelman syndrome (AS) are distinct neurogenetic disorders caused by chromosomal deletions, uniparental disomy or loss of the imprinted gene expression in the 15q11-q13 region. Whether an individual exhibits PWS or AS depends on if there is a lack of the paternally expressed gene to contribute to the region.[citation needed]
PWS is frequently found to be the reason for secondary obesity due to early onset hyperphagia - the abnormal increase in appetite for consumption of food. There are known three molecular causes of Prader–Willi syndrome development. One of them consists in micro-deletions of the chromosome region 15q11–q13. 70% of patients present a 5–7-Mb de novo deletion in the proximal region of the paternal chromosome 15. The second frequent genetic abnormality (~ 25–30% of cases) is maternal uniparental disomy of chromosome 15. The mechanism is due to maternal meiotic non-disjunction followed by mitotic loss of the paternal chromosome 15 after fertilization. The third cause for PWS is the disruption of the imprinting process on the paternally inherited chromosome 15 (epigenetic phenomena). This disruption is present in approximately 2–5% of affected individuals. Less than 20% of individuals with an imprinting defect are found to have a very small deletion in the PWS imprinting centre region, located at the 5′ end of the SNRPN gene.
AS is a severe debilitating neurodevelopmental disorder characterized by mental retardation, speech impairment, seizures, motor dysfunction, and a high prevalence of autism. The paternal origin of the genetic material that is affected in the syndrome is important because the particular region of chromosome 15 involved is subject to parent-of-origin imprinting, meaning that for a number of genes in this region, only one copy of the gene is expressed while the other is silenced through imprinting. For the genes affected in PWS, it is the maternal copy that is usually imprinted (and thus is silenced), while the mutated paternal copy is not functional.
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Make a list, using dot points, of the last five cities who hosted the Olympics.
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The last five cities to host the Olympic Games were:
- Tokyo, Japan (2021),
- Rio, Brazil (2016),
- London, England (2012),
- Beijing, China (2008),
- Athens, Greece (2004).
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Nnedimma Nkemdili Okorafor was born in Cincinnati, Ohio, in 1974 to Igbo Nigerian parents who travelled to America in 1969 to attend school but purportedly could not return to Nigeria due to the Nigerian Civil War. Okorafor is the third child in a family of four children and grew up in Chicago, Illinois, and would often travel to Nigeria to spend her holidays with her extended family. Her first name is Igbo for "mother is good".
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Is Nnedi Okorafor an American?
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Yes, Nnedi Okorafor is an America, of Nigerian origin.
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What are some melee weapons I can use for role playing?
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Melee weapons include the knife, axe, mace and whip.
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Give me a list of the last five european golden boots winner.
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1. Robert Lewandowski, 2022-2021
2. Robert Lewandowski, 2021-2020
3. Ciro Immobile, 2020-2019
4. Lionel Messi, 2019-2018
5. Lionel Messi, 2018-2017
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Write a summary of the outdoor activities to do in Colorado
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There are many outdoor activities that you can do in Colorado year around. It is best to determine whether you want to participate in those activities during summer or winter. For summer outdoor activities, there are adventurous activities like hiking, mountain biking, whitewater rafting and fly-fishing. There are also many outdoor activities in the winter like downhill skiing, cross-country skiing, snowboarding, snowshoeing and snowmobiling. Regardless of the time of year, there are many outdoor activities that you can do in Colorado.
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Who has been named as Kid of the year by Time Magazine?
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Gitanjali Rao(Indian American)
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null | false
| 158
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In this paper, we introduce Query-based Attention CNN(QACNN) for Text Similarity Map, an end-to-end neural network for question answering. This network is composed of compare mechanism, two-staged CNN architecture with attention mechanism, and a prediction layer. First, the compare mechanism compares between the given passage, query, and multiple answer choices to build similarity maps. Then, the two-staged CNN architecture extracts features through word-level and sentence-level. At the same time, attention mechanism helps CNN focus more on the important part of the passage based on the query information. Finally, the prediction layer find out the most possible answer choice. We conduct this model on the MovieQA dataset using Plot Synopses only, and achieve 79.99% accuracy which is the state of the art on the dataset.
We conduct this model on the MovieQA [1] dataset using Plot Synopses only, and achieve 79.99% accuracy which is the state of the art on the dataset.
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What accuracy does the model achieve on the MovieQA [1] dataset?
|
0.7999.
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The brown eared pheasant (Crossoptilon mantchuricum) is a large, 96– to 100-cm-long, dark brown pheasant endemic to the mountain forests of northeastern China (Shanxi and nearby provinces). The species was first described by Robert Swinhoe in 1863. It has stiff white ear coverts behind the eyes, which look like a moustache. The crown is black with red bare facial skin and its tail of 22 elongated, white feathers is curved, loose and dark-tipped. Both sexes are similar in plumage.
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What is a brown eared pheasant?
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The brown eared pheasant is a large dark brown pheasant native to the mountain forests of northeastern China. It has distinctive white ear covert behind the eyes that look like a moustache. It's crown is black with red bare facial skin, and it has a tail with long, white, curve, loose, dark-tipped feathers.
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What are some quick vegan meals to make?
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Peanut butter and jelly sandwich, rice and beans, smashed chickpea avocado sandwich, hummus wrap with veggies, pasta salad, spaghetti, burrito bowl, salad, curry, roasted veggies and tofu
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Why did you take so long to get home last night?
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On my home from work, I decided that I should go by the grocery store to pick up some water, cheese and other groceries for breakfast. As I was getting off of the freeway I saw something out of the corner of my eye running across the sidewalk. When I stopped at the traffic light, I was able to see that there was a puppy that appeared to be lost and wandering around. I was a hurry but the pup seemed really cold and shivering. I saw that it was going into a nearby parking lot that was on my way so I pulled over. I got out of my car and carefully walked up to the puppy to see if it had a tag or any identification. Suddenly, I saw a shadow pass behind me and someone grabbed me from behind and tried to wrestle my keys away from me.
Too bad for him, he didn't realize that I'm a UFC champion. Lucky for him, he only ended up with a missing tooth. It took a while for the police to show up so that's why I was late.
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Harry Potter is a series of seven fantasy novels written by British author J. K. Rowling. The novels chronicle the lives of a young wizard, Harry Potter, and his friends Hermione Granger and Ron Weasley, all of whom are students at Hogwarts School of Witchcraft and Wizardry. The main story arc concerns Harry's conflict with Lord Voldemort, a dark wizard who intends to become immortal, overthrow the wizard governing body known as the Ministry of Magic and subjugate all wizards and Muggles (non-magical people).
The series was originally published in English by Bloomsbury in the United Kingdom and Scholastic Press in the United States. All versions around the world are printed by Grafica Veneta in Italy. A series of many genres, including fantasy, drama, coming-of-age fiction, and the British school story (which includes elements of mystery, thriller, adventure, horror, and romance), the world of Harry Potter explores numerous themes and includes many cultural meanings and references. According to Rowling, the main theme is death. Other major themes in the series include prejudice, corruption, and madness.
Since the release of the first novel, Harry Potter and the Philosopher's Stone, on 26 June 1997, the books have found immense popularity, positive reviews, and commercial success worldwide. They have attracted a wide adult audience as well as younger readers and are widely considered cornerstones of modern literature. As of February 2023, the books have sold more than 600 million copies worldwide, making them the best-selling book series in history, and have been available in 85 languages. The last four books consecutively set records as the fastest-selling books in history, with the final instalment selling roughly 2.7 million copies in the United Kingdom and 8.3 million copies in the United States within twenty-four hours of its release.
The original seven books were adapted into an eight-part namesake film series by Warner Bros. Pictures. In 2016, the total value of the Harry Potter franchise was estimated at $25 billion, making Harry Potter one of the highest-grossing media franchises of all time. Harry Potter and the Cursed Child is a play based on a story co-written by Rowling.
The success of the books and films has allowed the Harry Potter franchise to expand with numerous derivative works, a travelling exhibition that premiered in Chicago in 2009, a studio tour in London that opened in 2012, a digital platform on which J. K. Rowling updates the series with new information and insight, and a pentalogy of spin-off films premiering in November 2016 with Fantastic Beasts and Where to Find Them, among many other developments. Themed attractions, collectively known as The Wizarding World of Harry Potter, have been built at several Universal Destinations & Experiences amusement parks around the world.
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Give me the main facts about the book series about Harry Potter.
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Here are the most important facts about the book series Harry Potter:
1. Harry Potter is a series of seven books written by British author J. K. Rowling.
2. The first book, Harry Potter and the Philosopher's Stone was published on June 26, 1997.
3. As of February 2023, more than 600 million copies of books were sold worldwide, making it the best-selling book series in history.
4. Although the book is aimed at a younger audience, the main themes of the series are death, prejudice, corruption, and madness.
5. Warner Bros. Pictures has taken the book and released a series of eight films.
6. In 2016, the total value of the Harry Potter franchise was estimated at $25 billion making Harry Potter one of the highest-grossing media franchises of all time.
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What is reserve requirement?
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Reserve requirements are central bank regulations that set the minimum amount that a commercial bank must hold in liquid assets. This minimum amount, commonly referred to as the commercial bank's reserve, is generally determined by the central bank on the basis of a specified proportion of deposit liabilities of the bank. This rate is commonly referred to as the reserve ratio. Though the definitions vary, the commercial bank's reserves normally consist of cash held by the bank and stored physically in the bank vault (vault cash), plus the amount of the bank's balance in that bank's account with the central bank. A bank is at liberty to hold in reserve sums above this minimum requirement, commonly referred to as excess reserves.
The reserve ratio is sometimes used by a country’s monetary authority as a tool in monetary policy, to influence the country's money supply by limiting or expanding the amount of lending by the banks. Monetary authorities increase the reserve requirement only after careful consideration because an abrupt change may cause liquidity problems for banks with low excess reserves; they generally prefer to use open market operations (buying and selling government-issued bonds) to implement their monetary policy. In the United States and many other countries (except Brazil, China, India, Russia), reserve requirements are generally not altered frequently in implementing a country's monetary policy because of the short-term disruptive effect on financial markets.
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You are on vacation and your newborn leaves something behind in the hotel room. Which of the following items would be something your newborn would have left behind: pacifier, blanket, 747 Jet, golf clubs, vodka, milk, iPad, cell phone
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items a newborn could leave behind: pacifier, blanket, milk
items a newborn would not leave behind: 747 Jet, golf clubs, vodka, iPad, cell phone
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1709.10217
| false
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It is worth noting that besides the released data for training and developing, we also allow to collect external data for training and developing. To considering that, the task 1 is indeed includes two sub tasks. One is a closed evaluation, in which only the released data can be used for training and developing. The other is an open evaluation that allow to collect external data for training and developing. For task 1, we use F1-score as evaluation metric.
We use manual evaluation for task 2. For each system and each complete user intent, the initial sentence, which is used to start the dialogue, is the same. The tester then begin to converse to each system. A dialogue is finished if the system successfully returns the information which the user inquires or the number of dialogue turns is larger than 30 for a single task. For building the dialogue systems of participants, we release an example set of complete user intent and three data files of flight, train and hotel in JSON format. There are five evaluation metrics for task 2 as following.
Task completion ratio: The number of completed tasks divided by the number of total tasks.
User satisfaction degree: There are five scores -2, -1, 0, 1, 2, which denote very dissatisfied, dissatisfied, neutral, satisfied and very satisfied, respectively.
Response fluency: There are three scores -1, 0, 1, which indicate nonfluency, neutral, fluency.
Number of dialogue turns: The number of utterances in a task-completed dialogue.
Guidance ability for out of scope input: There are two scores 0, 1, which represent able to guide or unable to guide.
For task 1, we use F1-score as evaluation metric.
We use manual evaluation for task 2.
There are five evaluation metrics for task 2 as following.
Task completion ratio: The number of completed tasks divided by the number of total tasks.
User satisfaction degree: There are five scores -2, -1, 0, 1, 2, which denote very dissatisfied, dissatisfied, neutral, satisfied and very satisfied, respectively.
Response fluency: There are three scores -1, 0, 1, which indicate nonfluency, neutral, fluency.
Number of dialogue turns: The number of utterances in a task-completed dialogue.
Guidance ability for out of scope input: There are two scores 0, 1, which represent able to guide or unable to guide.
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What metrics are used in the evaluation?
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The answers are shown as follows:
* For task 1, we use F1-score
* Task completion ratio
* User satisfaction degree
* Response fluency
* Number of dialogue turns
* Guidance ability for out of scope input
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Classify each of the following as either a liquid or a solid: puddle, cup, house, dog, bowl, water, juice
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A puddle, water, and juice are liquids. Cups, houses, dogs, and bowls are solids.
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What are three uses of a sheet besides bedding?
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A sheet can be used as a ghost costume, a room divider for additional privacy, and as rags for cleaning the house.
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1910.07181
| false
| null |
Results on WNLaMPro rare and medium are shown in Table TABREF34, where the mean reciprocal rank (MRR) is reported for BERT, Attentive Mimicking and Bertram. As can be seen, supplementing BERT with any of the proposed relearning methods results in noticeable improvements for the rare subset, with add clearly outperforming replace. Moreover, the add and add-gated variants of Bertram perform surprisingly well for more frequent words, improving the score for WNLaMPro-medium by 50% compared to BERT$_\text{base}$ and 31% compared to Attentive Mimicking. This makes sense considering that compared to Attentive Mimicking, the key enhancement of Bertram lies in improving context representations and interconnection of form and context; naturally, the more contexts are given, the more this comes into play. Noticeably, despite being both based on and integrated into a BERT$_\text{base}$ model, our architecture even outperforms a standalone BERT$_\text{large}$ model by a large margin.
Noticeably, despite being both based on and integrated into a BERT$_\text{base}$ model, our architecture even outperforms a standalone BERT$_\text{large}$ model by a large margin.
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What models other than standalone BERT is new model compared to?
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Only Bert base and Bert large are compared to proposed approach.
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Egypt, officially the Arab Republic of Egypt, is a transcontinental country spanning the northeast corner of Africa and southwest corner of Asia via a land bridge formed by the Sinai Peninsula. It is bordered by the Mediterranean Sea to the north, the Gaza Strip of Palestine and Israel to the northeast, the Red Sea to the east, Sudan to the south, and Libya to the west. The Gulf of Aqaba in the northeast separates Egypt from Jordan and Saudi Arabia. Cairo is the capital and largest city of Egypt, while Alexandria, the second-largest city, is an important industrial and tourist hub at the Mediterranean coast. At approximately 100 million inhabitants, Egypt is the 14th-most populated country in the world.
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Extract a name of a water passage that separates Egypt form Jordan and Saudi Arabia
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The Gulf of Aqaba in the northeast separates Egypt from Jordan and Saudi Arabia.
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What was the first modern trading card game created?
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On August 5th 1993, Magic: The Gathering was released to the world as the first modern trading card game. The game was published by Wizards of the Coast and created by Richard Garfield. Magic: The Gathering is a card game where two wizards battle casting spells, summoning creatures, and use magical objects to defeat their opponents. The Limited Edition Alpha set was the first set Magic: The Gathering set ever released.
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| 40
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We have shown that ERP components can be predicted from neural networks pretrained as language models and fine-tuned to directly predict those components. To the best of our knowledge, prior work has not successfully used statistical models to predict all of these components. Furthermore, we have shown that multitask learning benefits the prediction of ERP components and can suggest how components relate to each other. At present, these joint-training benefit relationships are only suggestive, but if these relationships ultimately lead to insights about what drives each ERP component, then the components become more useful tools for studying human language comprehension. By using multitask learning as a method of characterization, we have found some expected relationships (LAN+P600 and ELAN+P600) and several more surprising relationships. We believe that this is exactly the kind of finding that makes multitask learning an interesting exploratory technique in this area. Additionally, we have shown that information can be shared between heterogeneous types of data (eye-tracking, self-paced reading, and ERP components) in the domain of human language processing prediction, and in particular between behavioral and neural data. Given the small datasets associated with human language processing, using heterogeneous data is a potentially major advantage of a multitask approach. In future work, we will further explore what information is encoded into the model representations when neural and behavioral data are used to train neural networks, and how these representations differ from the representations in a model trained on language alone.
In future work, we will further explore what information is encoded into the model representations when neural and behavioral data are used to train neural networks, and how these representations differ from the representations in a model trained on language alone.
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What will they explore in the future?
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What information is encoded into the model representations when neural and behavioral data are used to train neural networks, and how these representations differ from the representations in a model trained on language alone.
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Star Wars (retroactively titled Star Wars: Episode IV – A New Hope) is a 1977 American epic space opera film written and directed by George Lucas, produced by Lucasfilm and distributed by 20th Century-Fox. It is the first film in the Star Wars film series and fourth chronological chapter of the "Skywalker Saga". Set "a long time ago" in a fictional universe where the galaxy is ruled by the tyrannical Galactic Empire, the story focuses on a group of freedom fighters known as the Rebel Alliance, who aim to destroy the Empire's newest weapon, the Death Star. Luke Skywalker becomes caught in the conflict while learning the ways of a metaphysical power known as "the Force" from Jedi Master Obi-Wan Kenobi. The cast includes Mark Hamill, Harrison Ford, Carrie Fisher, Peter Cushing, Alec Guinness, David Prowse, James Earl Jones, Anthony Daniels, Kenny Baker, and Peter Mayhew.
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From the passage provided, extract the name of the Director of the Star Wars movie
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Star wars was directed and written by George Lucas
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| 39
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Although we did not have access to a low-resource dataset, there is a corpus of noisy multi-speaker speech that simulates many of the conditions we expect to find in our motivating applications: the CALLHOME Spanish–English speech translation dataset (LDC2014T23; Post el al., 2013). We ran UTD over all 104 telephone calls, which pair 11 hours of audio with Spanish transcripts and their crowdsourced English translations. The transcripts contain 168,195 Spanish word tokens (10,674 types), and the translations contain 159,777 English word tokens (6,723 types). Though our system does not require Spanish transcripts, we use them to evaluate UTD and to simulate a perfect UTD system, called the oracle.
For MT training, we use the pseudotext and translations of 50 calls, and we filter out stopwords in the translations with NLTK BIBREF15 . Since UTD is better at matching patterns from the same speaker (§ SECREF8 ), we created two types of 90/10% train/test split: at the call level and at the utterance level. For the latter, 90% of the utterances are randomly chosen for the training set (independent of which call they occur in), and the rest go in the test set. Hence at the utterance level, but not the call level, some speakers are included in both training and test data. Although the utterance-level split is optimistic, it allows us to investigate how multiple speakers affect system performance. In either case, the oracle has about 38k Spanish tokens to train on.
Although we did not have access to a low-resource dataset, there is a corpus of noisy multi-speaker speech that simulates many of the conditions we expect to find in our motivating applications: the CALLHOME Spanish–English speech translation dataset (LDC2014T23; Post el al., 2013).
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What data sets are used in this article?
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The CALLHOME Spanish–English speech translation dataset.
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Classify each of the following as having 2 wheels, 4 wheels, or neither: Car, Tricycle, Bicycle, Motorcycle, Grocery Cart
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Car: 4 Wheels
Tricycle: Neither
Bicycle: 2 Wheels
Motorcycle: 2 Wheels
Grocery Cart: 4 Wheels
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| 29
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Over the years, a handful of QA systems have gained popularity around the world. One of the oldest QA system is BASEBALL (created on 1961) BIBREF4 which answers question related to baseball league in America for a particular season. LUNAR BIBREF5 system answers questions about soil samples taken from Apollo lunar exploration. Some of the most popular QA Systems are IBM Watson, Apple Siri and Wolfram Alpha. Examples of some QA systems based on different languages are: Zhang Yu Chinese question classification BIBREF6 based on Incremental Modified Bayes, Arabic QA system (AQAS) BIBREF7 by F. A. Mohammed, K. Nasser, & H. M. Harb and Syntactic open domain Arabic QA system for factoid questions BIBREF8 by Fareed et al. QA systems have been built on different analysis methods such as morphological analysis BIBREF9, syntactical analysis BIBREF10, semantic analysis BIBREF11 and expected answer Type analysis BIBREF12.
Researches on question classification, question taxonomies and QA system have been undertaken in recent years. There are two types of approaches for question classification according to Banerjee et al in BIBREF13 - by rules and by machine learning approach. Rule based approaches use some hard coded grammar rules to map the question to an appropriate answer type BIBREF14 BIBREF15. Machine Learning based approaches have been used by Zhang et al and Md. Aminul Islam et al in BIBREF16 and BIBREF0. Many classifiers have been used in machine learning for QC such as Support Vector Machine (SVM) BIBREF16 BIBREF17, Support Vector Machines and Maximum Entropy Model BIBREF18, Naive Bayes (NB), Kernel Naive Bayes (KNB), Decision Tree (DT) and Rule Induction (RI) BIBREF13. In BIBREF0, they claimed to achieve average precision of 0.95562 for coarse class and 0.87646 for finer class using Stochastic Gradient Descent (SGD).
A Bengali QC System was built by Somnath Banerjee and Sivaji Bandyopadhyay BIBREF13 BIBREF19 BIBREF20. They proposed a two-layer taxonomy classification with 9 coarse-grained classes and 69 fine-grained classes. There are other research works BIBREF0 BIBREF21 in Bengali Language. A survey was performed on text QA techniques BIBREF22 where there was an analysis conducted in Bengali Language. Syed Mehedi Hasan Nirob et al achieved 88.62% accuracy by using 380 top frequent words as the feature in their work BIBREF17.
There are two types of approaches for question classification according to Banerjee et al in [1] - by rules and by machine learning approach.
|
What are the two types of approaches for question classification？
|
By rules and by machine learning approach.
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null | false
| null |
Who was the first lead guitarist of Metallica?
|
Dave Mustaine
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null | false
| null |
What are some ways I can avoid financial failure?
|
Financial failure is the result of exceeding ones ability to service debts, and ones liabilities exceed their assets. In general, you should live beneath your means, and decrease debts to a serviceable level. To ensure financial success, it is recommended to save and invest to the point where you can comfortably live on 25x your yearly expenses at the typical yearly draw down of 4% to the point of the typical life expectancy of 30 years past retirement.
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Why do we feel lighter in weight in a swimming pool?
|
We feel lighter in a swimming pool because the water exerts an upward force or buoyant force on our body. This is because the weight of our body in water is equal to the apparent weight.
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|
1810.00663
| false
| null |
First, we can observe that the final model “Ours with Mask and Ordered Triplets” outperforms the Baseline and Ablation models on all metrics in previously seen environments. The difference in performance is particularly evident for the Exact Match and Goal Match metrics, with our model increasing accuracy by 35% and 25% in comparison to the Baseline and Ablation models, respectively. These results suggest that providing the behavioral navigation graph to the model and allowing it to process this information as a knowledge base in an end-to-end fashion is beneficial.
Lastly, it is worth noting that our proposed model (last row of Table TABREF28 ) outperforms all other models in previously seen environments. In particular, we obtain over INLINEFORM0 increase in EM and GM between our model and the next best two models.
First, we can observe that the final model “Ours with Mask and Ordered Triplets” outperforms the Baseline and Ablation models on all metrics in previously seen environments. The difference in performance is particularly evident for the Exact Match and Goal Match metrics, with our model increasing accuracy by 35% and 25% in comparison to the Baseline and Ablation models, respectively. These results suggest that providing the behavioral navigation graph to the model and allowing it to process this information as a knowledge base in an end-to-end fashion is beneficial.
Lastly, it is worth noting that our proposed model (last row of Table TABREF28 ) outperforms all other models in previously seen environments. In particular, we obtain over INLINEFORM0 increase in EM and GM between our model and the next best two models.
|
By how much did their model outperform the baseline?
|
The answers are shown as follows:
* increasing accuracy by 35% and 25% in comparison to the Baseline and Ablation models, respectively
* over INLINEFORM0 increase in EM and GM between our model and the next best two models
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null | false
| null |
Give me a list of 1980s computer games.
|
Here is a list of some computer games from the 1980s: Galaga, Donkey Kong, Pac-Man, Frogger, Tetris and SimCity.
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null | false
| null |
What is an atmospheric river?
|
Atmospheric rivers are relatively long, narrow regions in the atmosphere – like rivers in the sky – that transport most of the water vapor outside of the tropics. These columns of vapor move with the weather, carrying an amount of water vapor roughly equivalent to the average flow of water at the mouth of the Mississippi River. When the atmospheric rivers make landfall, they often release this water vapor in the form of rain or snow.
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null | false
| null |
Where do sloths live?
|
Sloths are found throughout Central America and northern South America, including parts of Brazil and Peru. They live high in the trees of tropical rainforests, where they spend most of their time curled up or hanging upside down from branches.
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|
2001.00137
| true
| null |
The incomplete dataset used for training is composed of lower-cased incomplete data obtained by manipulating the original corpora. The incomplete sentences with STT error are obtained in a 2-step process shown in Fig. FIGREF22. The first step is to apply a TTS module to the available complete sentence. Here, we apply gtts , a Google Text-to-Speech python library, and macsay , a terminal command available in Mac OS as say. The second step consists of applying an STT module to the obtained audio files in order to obtain text containing STT errors. The STT module used here was witai , freely available and maintained by Wit.ai. The mentioned TTS and STT modules were chosen according to code availability and whether it's freely available or has high daily usage limitations.
The incomplete dataset used for training is composed of lower-cased incomplete data obtained by manipulating the original corpora.
|
Do they test their approach on a dataset without incomplete data?
|
No.
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null | false
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write a scene between two actors discussing movie Inception
|
Actress 1: "Oh my god, have you seen Inception?"
Actor 2: "Yes! That movie blew my mind. What did you think of it?"
Actress 1: "Honestly, I was so confused for most of it. But it was so interesting, I couldn't look away. I had to know what was going on."
Actor 2: "That's exactly how I felt. It's one of those movies that you have to pay attention to every detail, or you'll get lost."
Actress 1: "Absolutely. And the way they played with time and reality was so cool. I don't think I've ever seen a movie like that before."
Actor 2: "Yeah, the concept of entering someone's dreams to implant an idea was mind-boggling. And the way they executed it was so well done."
Actress 1: "It was. And the cast was amazing too. Leonardo DiCaprio was incredible as usual, and I loved seeing Ellen Page in a different type of role."
Actor 2: "Definitely. And the action scenes were so intense. The zero-gravity hallway fight was insane."
Actress 1: "Oh my god, yes. I was on the edge of my seat for that one. And the ending...I still can't decide what it means."
Actor 2: "I know, right? It's one of those movies that leaves you with so many questions. But that's part of what makes it so great."
Actress 1: "Exactly. I love when movies challenge me to think and leave me wanting more. Inception definitely did that."
Actor 2: "Agreed. It's definitely one of my all-time favorites. I could watch it a hundred times and still discover something new."
Actress 1: "Same here. It's just one of those movies that sticks with you long after it's over."
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null | false
| null |
Imperial rule by Europeans would continue until after the conclusion of World War II, when almost all remaining colonial territories gradually obtained formal independence. Independence movements in Africa gained momentum following World War II, which left the major European powers weakened. In 1951, Libya, a former Italian colony, gained independence. In 1956, Tunisia and Morocco won their independence from France. Ghana followed suit the next year (March 1957), becoming the first of the sub-Saharan colonies to be granted independence. Most of the rest of the continent became independent over the next decade.
|
Which sub-Saharan colony was the first to gain independence?
|
Ghana was the first sub-Saharan colony to gain independence.
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null | false
| null |
Name some popular video games exclusive to Sony’s Playstation game consoles.
|
Some of the most popular games that are exclusive to Sony Playstation consoles include the Uncharted series, the Gran Turismo series, and the God of War series. Each series of games have sold tens of millions of copies.
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null | false
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The Basketball Association of America was founded in 1946 by owners of the major ice hockey arenas in the Northeastern and Midwestern United States and Canada. On November 1, 1946, in Toronto, Ontario, Canada, the Toronto Huskies hosted the New York Knickerbockers at Maple Leaf Gardens, in a game the NBA now refers to as the first game played in NBA history. The first basket was made by Ossie Schectman of the Knickerbockers. Although there had been earlier attempts at professional basketball leagues, including the American Basketball League (ABL) and the NBL, the BAA was the first league to attempt to play primarily in large arenas in major cities. During its early years, the quality of play in the BAA was not significantly better than in competing leagues or among leading independent clubs such as the Harlem Globetrotters. For instance, the 1948 ABL finalist Baltimore Bullets moved to the BAA and won that league's 1948 title, and the 1948 NBL champion Minneapolis Lakers won the 1949 BAA title. Prior to the 1948–49 season, however, NBL teams from Fort Wayne, Indianapolis, Minneapolis, and Rochester jumped to the BAA, which established the BAA as the league of choice for collegians looking to turn professional.
On August 3, 1949, the remaining NBL teams–Syracuse, Anderson, Tri-Cities, Sheboygan, Denver, and Waterloo–merged into the BAA. In deference to the merger and to avoid possible legal complications, the league name was changed to the present National Basketball Association, even though the merged league retained the BAA's governing body, including Maurice Podoloff as president. To this day, the NBA claims the BAA's history as its own. It now reckons the arrival of the NBL teams as an expansion, not a merger, and does not recognize NBL records and statistics.
|
Tell me about the history of how the NBA started?
|
The league was founded in New York City on June 6, 1946, as the Basketball Association of America (BAA). It changed its name to the National Basketball Association on August 3, 1949, after merging with the competing National Basketball League..
|
null | false
| null |
Is Daft Punk still together?
|
No. Daft Punk officially broke up in 2021.
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|
null | false
| null |
Classify these alcoholic beverages as bourbon, wine, or beer: Budweiser, Blanton's, Devil's Backbone, Chardonnay, Pinot Noir, Yellowstone, Elijah Craig, Pinot Grigio, Yeungling, Sauvignon Blanc, Cabernet Sauvignon, Samuel Adams, Sierra Nevada, Baker's, Basil Hayden, Eagle Rare, Merlot, Jim Beam, Coors Light, Jack Daniels, Heineken, Miller Lite
|
Bourbons: Blanton's, Yellowstone, Elijah Craig, Baker's, Basil Hayden, Eagle Rare, Jim Beam, Jack Daniels. Wine: Chardonnay, Pinor Noir, Pinot Grigio, Sauvignon Blanc, Merlot. Beer: Budweiser, Devil's Backbone, Yeungling, Samuel Adams, Sierra Nevada, Coors Light, Heineken, Miller Lite
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null | false
| null |
What is Occam's razor?
|
Occam’s razor is a principle of theory construction or evaluation according to which, other things equal, explanations that posit fewer entities, or fewer kinds of entities, are to be preferred to explanations that posit more. It is sometimes misleadingly characterized as a general recommendation of simpler explanations over more complex ones.
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null | false
| null |
How long can you store cooked food in refrigerators?
|
A common misconception is the assumption that food "loses nutrients" when it's refrigerated. That is not as true as you think it is. It is always good to ask 2 follow up questions
What nutrients exactly? And by how much?
It turns out that water soluble vitamins are the most unstable and easily lost nutrients, but fun fact: most of the loss happens during cooking, not refrigeration. It is heat that destroys vitamins, not cold. In fact, in an airtight container, most cooked food will last 2-3 days at the minimum and up to a week in many cases. In the freezer, food will last up to 6 months (assuming no power cuts). All biological activity slows down with temperature.
There are a few exceptions - plain cooked/steamed rice can sometimes be infected by a bacteria that doesn't mind low temperatures, so it's best to consume it within 1-2 days.
Bonus point: Indian food, is uniquely fridge friendly because it tends to be spicy, salty and sour - these are three conditions microbes absolutely hate.
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|
1710.09340
| false
| null |
Table TABREF12 compares our novel system with other state-of-the-art transition-based dependency parsers on the PT-SD. Greedy parsers are in the first block, beam-search and dynamic programming parsers in the second block. The third block shows the best result on this benchmark, obtained with constituent parsing with generative re-ranking and conversion to dependencies. Despite being the only non-projective parser tested on a practically projective dataset, our parser achieves the highest score among greedy transition-based models (even above those trained with a dynamic oracle).
We even slightly outperform the arc-swift system of Qi2017, with the same model architecture, implementation and training setup, but based on the projective arc-eager transition-based parser instead. This may be because our system takes into consideration any permissible attachment between the focus word INLINEFORM0 and any word in INLINEFORM1 at each configuration, while their approach is limited by the arc-eager logic: it allows all possible rightward arcs (possibly fewer than our approach as the arc-eager stack usually contains a small number of words), but only one leftward arc is permitted per parser state. It is also worth noting that the arc-swift and NL-Covington parsers have the same worst-case time complexity, ( INLINEFORM2 ), as adding non-local arc transitions to the arc-eager parser increases its complexity from linear to quadratic, but it does not affect the complexity of the Covington algorithm. Thus, it can be argued that this technique is better suited to Covington than to arc-eager parsing.
FLOAT SELECTED: Table 2: Accuracy comparison of state-of-theart transition-based dependency parsers on PT-SD. The “Type” column shows the type of parser: gs is a greedy parser trained with a static oracle, gd a greedy parser trained with a dynamic oracle, b(n) a beam search parser with beam size n, dp a parser that employs global training with dynamic programming, and c a constituent parser with conversion to dependencies.
Table TABREF12 compares our novel system with other state-of-the-art transition-based dependency parsers on the PT-SD. Greedy parsers are in the first block, beam-search and dynamic programming parsers in the second block. The third block shows the best result on this benchmark, obtained with constituent parsing with generative re-ranking and conversion to dependencies. Despite being the only non-projective parser tested on a practically projective dataset, our parser achieves the highest score among greedy transition-based models (even above those trained with a dynamic oracle).
We even slightly outperform the arc-swift system of Qi2017, with the same model architecture, implementation and training setup, but based on the projective arc-eager transition-based parser instead.
FLOAT SELECTED: Table 2: Accuracy comparison of state-of-theart transition-based dependency parsers on PT-SD. The “Type” column shows the type of parser: gs is a greedy parser trained with a static oracle, gd a greedy parser trained with a dynamic oracle, b(n) a beam search parser with beam size n, dp a parser that employs global training with dynamic programming, and c a constituent parser with conversion to dependencies.
|
By how much does the new parser outperform the current state-of-the-art?
|
Proposed method achieves 94.5 UAS and 92.4 LAS compared to 94.3 and 92.2 of best state-of-the -art greedy based parser. Best state-of-the art parser overall achieves 95.8 UAS and 94.6 LAS.
|
null | false
| null |
Denis-Benjamin Viger (French pronunciation: [dəni bɛ̃ʒamɛ̃ viʒe]; August 19, 1774 – February 13, 1861) was a 19th-century politician, lawyer, businessman in Lower Canada. He was a leader in the Patriote movement.
Viger was part of the militia in the early 19th century and then a captain in the War of 1812. He retired from the militia in 1824 with the rank of major.
|
Without quoting from the text, can you summarise from wikipedia who Denis-Benjamin Viger was?
|
Denis-Benjamin Viger was a Canadian 19th century politician, lawyer and businessman who lead the Patriote movement.
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null | false
| null |
5 ways on prem is better than cloud
|
Will have absolute control
Will have no external factors
It support safety requirements, and have the tools to ensure first-class safety
Full control over the data since it is stored locally
System can be customised according to your business
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null | false
| null |
Classify each as National Park in Utah or Arizona: Zion National Park, Bryce Canyon, Grand Canyon, Saguaro National Park
|
National Parks in Utah: Zion National Park, Bryce Canyon
National Parks in Arizona: Grand Canyon, Saguaro National Park
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|
null | false
| null |
What are toe beans?
|
Toe beans is a colloquial term originating on the Internet and is used to refer to the leathers of a cat (its toes and paw pad). It can also refer to a dog's paws but the term was popularized in the context of cats.
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|
1606.08495
| true
| null |
In this paper we focus on the skipgram approach with random negative examples proposed in BIBREF0 . This has been found to yield the best results among the proposed variants on a variety of semantic tests of the resulting vectors BIBREF7 , BIBREF0 . Given a corpus consisting of a sequence of sentences INLINEFORM0 each comprising a sequence of words INLINEFORM1 , the objective is to maximize the log likelihood: DISPLAYFORM0
In this paper we focus on the skipgram approach with random negative examples proposed in BIBREF0 .
|
Do they use skipgram version of word2vec?
|
Yes.
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null | false
| null |
Phrynobatrachus tokba is a species of frog in the family Phrynobatrachidae. It is found in West Africa from Ghana westward to Côte d'Ivoire, Liberia, Guinea, Sierra Leone, and Guinea-Bissau. Common names Tokba river frog, Tokba puddle frog, and—when referring to the formerly recognized Phrynobatrachus alticola, forest river frog—have been proposed for it.
|
Given a reference text about phrynobatrachus tokba, what are common names for it?
|
Common names for Phrynobatrachus tokba are Tokba river frog, Tokba puddle frog, and forest river frog.
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null | false
| null |
What are some well known movies with Leonardo DiCaprio?
|
Well known movies with Leonard DiCaprio are Inception, Titanic, The Wolf of Wall Street, and Shutter Island
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null | false
| null |
Given a polynomial x^2 + 2x + 1, what is x?
|
x is equal to -1
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null | false
| 133
|
We proposed to use visual renderings of documents to capture implicit document quality indicators, such as font choices, images, and visual layout, which are not captured in textual content. We applied neural network models to capture visual features given visual renderings of documents. Experimental results show that we achieve a 2.9% higher accuracy than state-of-the-art approaches based on textual features over Wikipedia, and performance competitive with or surpassing state-of-the-art approaches over arXiv. We further proposed a joint model, combining textual and visual representations, to predict the quality of a document. Experimental results show that our joint model outperforms the visual-only model in all cases, and the text-only model on Wikipedia and two subsets of arXiv. These results underline the feasibility of assessing document quality via visual features, and the complementarity of visual and textual document representations for quality assessment.
Experimental results show that our joint model outperforms the visual-only model in all cases, and the text-only model on Wikipedia and two subsets of arXiv.
|
Does the joint model proposed by authors outperform the visual-only model in all cases?
|
Yes, it does.
|
1809.04960
| false
| null |
In addition to the unsupervised training, we explore a semi-supervised training framework to combine the proposed unsupervised model and the supervised model. In this scenario we have a paired dataset that contains article-comment parallel contents INLINEFORM0 , and an unpaired dataset that contains the documents (articles or comments) INLINEFORM1 . The supervised model is trained on INLINEFORM2 so that we can learn the matching or mapping between articles and comments. By sharing the encoder of the supervised model and the unsupervised model, we can jointly train both the models with a joint objective function: DISPLAYFORM0
In this scenario we have a paired dataset that contains article-comment parallel contents INLINEFORM0 , and an unpaired dataset that contains the documents (articles or comments) INLINEFORM1 . The supervised model is trained on INLINEFORM2 so that we can learn the matching or mapping between articles and comments. By sharing the encoder of the supervised model and the unsupervised model, we can jointly train both the models with a joint objective function: DISPLAYFORM0
|
Which paired corpora did they use in the other experiment?
|
The answers are shown as follows:
* dataset that contains article-comment parallel contents INLINEFORM0 , and an unpaired dataset that contains the documents (articles or comments) INLINEFORM1
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null | false
| null |
What are some ways by which humanity could quickly work to cool down the planet to minimize the effects of global warming?
|
One idea humanity to implement to rapidly cool the planet to help minimize the effects of global warming would be to block some or all of the sunlight (UV radiation) hitting the planet from the sun. Sometimes referred to as GeoEngineering, these are projects on a truly planet-size scale. A project like this could, for example, consist of large reflective lightweight solar sails or other loft-able reflective material which could be seeded into the upper atmosphere to reflect some or all of the sunlight back into space. Another Idea would be to create massive and plentiful Co2 scrubbers to remove a noticeable quantity of the greenhouse gas, Co2, which works to reflect and prevent heat from the planet from leaving back out into space. Greatly reducing the quantity of Co2 in our atmosphere would allow more heat to escape the planet and consequently cool it down. Yet another thought might be to artificially and greatly increase the size of our ice caps which would lead to more sunlight being reflected back out into space. Yet another approach could be to mimic nature in prior heavily volcanic periods and inject massive quantities of sulfur dioxide into the atmosphere in the hopes of producing conditions that in the past led to mini ice-ages.
|
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null | false
| null |
Identify which animal is domesticated or wild: Cows (Cattle), Cheetah
|
Cheetah is wild, Cows (Cattle) is domesticated.
|
|
null | false
| null |
Give me a list of ten vegetables that are green.
|
1. Asparagus
2. Brussel sprout
3. Green bean
4. Broccoli
5. Kale
6. Peas
7. Cabbage
8. Celery
9. Artichoke
10. Arugula
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|
null | false
| null |
What is a covalent bond?
|
A covalent bond is a bond where electrons are shared between atoms. An example of a covalent bond is H2O, or water.
|
|
1912.00871
| true
| null |
Our attempt at language pre-training fell short of our expectations in all but one tested dataset. We had hoped that more stable language understanding would improve results in general. As previously mentioned, using more general and comprehensive corpora of language could help grow semantic ability.
Our pre-training was unsuccessful in improving accuracy, even when applied to networks larger than those reported. We may need to use more inclusive language, or pre-train on very math specific texts to be successful. Our results support our thesis of infix limitation.
Our attempt at language pre-training fell short of our expectations in all but one tested dataset.
Our pre-training was unsuccessful in improving accuracy, even when applied to networks larger than those reported.
|
Does pre-training on general text corpus improve performance?
|
No.
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null | false
| 483
|
In this work, we focus on multi-modal learning with a particular focus on learning video-text encoders for retrieval by proposing a novel, multi-modal adaptation module.
Video-text pretraining. Originating from the NLP domain, where the transformer architectures has been a key ingredient and subject to optimization in a multitude of ways, it has recently found applications in the vision-language domain. For example, recent works have leveraged transformers to learn generalizeable image or multi-modal image-text and video-multilingual text representations. A few works combine visual and text modalities as inputs to a BERT model to simultaneously learn semantic video and text representations. For representation learning, the availability of large-scale datasets such as HowTo100M has enabled more effective pretraining of video-text representations for multiple downstream tasks. More recently, show that adding a generative objective to contrastive pretraining can yield gains in video-text downstream tasks. Based on the CLIP model, which works well even without finetuning for some retrieval tasks, train video-text CLIP-initialized models by gradually scaling up video training from image training and a custom dataset. While we also start with a CLIP initialization as in, the focus of our paper lies in developing a novel method for leveraging user comments, a modality that has previously been overlooked in the text-video retrieval literature, as a valuable source of information. As is standard, the pretrained representations are subsequently evaluated on smaller datasets such as MSVD and MSR-VTT.
Multi-modal domain adaptation. While residual adapters for domain adaptation have been explored for uni-modal models such as CNNs, e.g. in, there are no works that translate this concept to the multi-modal domain, where cross-modal learning dominates.
There is little prior work using user comments as additional context in multimodal settings. The use of user comments and reactions to refine predictions has been discussed by for minimising harms on facebook.com. Overall, we are the first to demonstrate that user comments can be used as a complementary modality when learning video-text representations.
Overall, we are the first to demonstrate that user comments can be used as a complementary modality when learning video-text representations.
|
The conclusion we can learn from Table 1 is that training and testing with comments help visual-text retrieval. However, is this already known not a novel one?
|
To our knowledge our paper is the first to show that comments can improve video-text retrieval. If we have missed a reference, we are happy to include it in the discussion and update our claims.
|
1911.03310
| true
| null |
We thus try to remove the language-specific information from the representations by centering the representations of sentences in each language so that their average lies at the origin of the vector space. We do this by estimating the language centroid as the mean of the mBERT representations for a set of sentences in that language and subtracting the language centroid from the contextual embeddings.
We thus try to remove the language-specific information from the representations by centering the representations of sentences in each language so that their average lies at the origin of the vector space.
|
Are language-specific and language-neutral components disjunctive?
|
No.
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null | false
| 258
|
In the first experiment we perform an attribution of individual scenes of H8 using the Support Vector Machine as a classifier and the frequencies of 500 most frequent rhythmic types and the frequencies of 500 most frequent words as a feature set. As training samples, individual scenes of plays written by Shakespeare, Fletcher, and Massinger are used that come roughly from the period when H8 was supposedly written, namely:
Shakespeare: The Tragedy of Coriolanus (5 scenes), The Tragedy of Cymbeline (27 scenes), The Winter’s Tale (12 scenes), The Tempest (9 scenes)
Fletcher: Valentinian (21 scenes), Monsieur Thomas (28 scenes), The Woman’s Prize (23 scenes), Bonduca (18 scenes)
Massinger: The Duke of Milan (10 scenes), The Unnatural Combat (11 scenes), The Renegado (25 scenes)
Altogether there are thus 53 training samples for Shakespeare, 90 training samples for Fletcher and 46 training samples for Massinger. In order to estimate the accuracy of the model, cross-validation is performed in the following way:
To avoid the risk of overfitting which may be caused by testing the model on the scenes from the same play as it was trained on, we do not perform a standard k-fold cross validation. Instead, we classify scenes of each play by a model trained on the rest, i.e. 5 scenes of Shakespeare’s Coriolanus are classified by a model trained on the scenes from the remaining 3 plays by Shakespeare, 4 plays by Fletcher and 5 plays by Massinger, 27 scenes of Cymbeline are classified in the same way and so on.
Since the training data are imbalanced (which may bias the results), we level the number of training samples per author by random selection.
To obtain more representative results, the entire process is repeated 30 times (with a new random selection in each iteration) thus resulting in 30 classifications of each scene.
For the sake of comparison of the attribution power of both feature subsets, cross-validations are performed not only of the combined models (500 words $\cup $ 500 rhythmic types), but also of the words-based models (500 words) and versification-based models (500 rhythmic types) alone.
As shown in Table TABREF14, the versification-based models yield a very high accuracy with the recognition of Shakespeare and Fletcher (0.97 to 1 with the exception of Valentinian), yet slightly lower accuracy with the recognition of Massinger (0.81 to 0.88). The accuracy of words-based models remains very high across all three authors (0.95 to 1); in three cases it is nevertheless outperformed by the combined model. We thus may conclude that combined models provide a reliable discriminator between Shakespeare’s, Fletcher’s and Massinger’s styles.
Table TABREF19 gives the results of the classifiers when applied to the individual scenes of H8 on the basis of which we may conclude:
It is very unlikely that Massinger took part in the text of H8. Out of 17 scenes only 2 are attributed to Massinger by any of the models (2.1, 4.2), and in both cases by a mere minority of votes.
The probability that the text of H8 is a result of collaboration between Shakespeare and Fletcher is very high: with 7 scenes all the 30 models agree upon Shakespeare’s authorship, with 5 scenes all the 30 models agree upon Fletcher’s authorship.
Our results correspond to the Spedding’s attribution to a high extent. With the exception of two scenes, the majority of models always predict the same author to which it is attributed by Spedding. The two exceptions are the second scene of act 3, where Spedding supposed mixed authorship, and the first scene of act 4, which was originally attributed to Fletcher.
In the first experiment we perform an attribution of individual scenes of H8 using the Support Vector Machine as a classifier and the frequencies of 500 most frequent rhythmic types and the frequencies of 500 most frequent words as a feature set.
|
What is used as a classifier?
|
The Support Vector Machine.
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null | false
| null |
How does a paraglider work?
|
A paraglider works by leveraging airflow to create lift. Air flows over both the top and bottom of the glider and meets at the edge. Due to the specific shape of the paraglider it creates more pressure on the bottom of the glider than on the top, this creates lift upwards much like an airplane wing.
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How long does it take to make Kombucha?
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Many home brewers create kombucha using a two-step fermentation process. First, the sweet tea and SCOBY are combined in a container with a lid that is not airtight, but would keep out dust, debris, and any bugs. A dish cloth secured over the opening of a mason jar or crock is the simple set up of many home brewers. Leave this mixture at room temperature to ferment for 2-5 days, until the taste is to your liking. When ready, bottle the kombucha in airtight containers and add any flavor enhancing ingredients such as syrups, herbs, juices or fruit. Allow to ferment an additional 1-3 days to taste. Popular flavor enhancers include ginger, blueberry, strawberry, pineapple, mint.
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Skiing is the use of skis to glide on snow. Variations of purpose include basic transport, a recreational activity, or a competitive winter sport. Many types of competitive skiing events are recognized by the International Olympic Committee (IOC), and the International Ski Federation (FIS).
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what is snow skiing
|
skiing is a form of outdoor winter sport. Done in the mountains. You can ski on piste and off piste.
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Trump ordered a travel ban on citizens from several Muslim-majority countries, diverted military funding towards building a wall on the U.S.–Mexico border, and implemented a policy of family separations for apprehended migrants. He rolled back more than 100 environmental policies and regulations in an aggressive attempt to weaken environmental protections. Trump signed the Tax Cuts and Jobs Act of 2017, which cut taxes for individuals and businesses and rescinded the individual health insurance mandate penalty of the Affordable Care Act. He appointed 54 federal appellate judges and three U.S. Supreme Court justices. Trump initiated a trade war with China and withdrew the U.S. from the proposed Trans-Pacific Partnership trade agreement, the Paris Agreement on climate change, and the Iran nuclear deal. Trump met with North Korean leader Kim Jong-un three times, but made no progress on denuclearization. He reacted slowly to the COVID-19 pandemic, ignored or contradicted many recommendations from health officials in his messaging, and promoted misinformation about unproven treatments and the need for testing.
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How many judges did President Trump apoint?
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He appointed 57 judges, 54 federal appellate judges and three U.S. Supreme Court justices.
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null | false
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What are the risks of social isolation?
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Social isolation can lead to feeling of loneliness that can cause depression and other mental health issues. It could also lead to social anxiety, when the individual does go out and interact with people.
I read a research that show that the magnitude of risk presented by social isolation is very similar in magnitude to that of obesity, smoking, lack of access to care and physical activity.
My suggestion to those who are socially isolated will be to try to get yourself out of your comfort zone. Go to meetup.com to find people who like to do similar activities like you and join them. Once you are with them, reach out and introduce yourself. If all else fails, speak to a therapist who can provide activities to help you out.
Mental health is super important so take care of yourself and your loved one.
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null | false
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Is rule 606 good for the industry
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yes, overall create consistent accounting rules regardless of business or revenue model
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null | false
| 3
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In this section, we describe the results from our experiments on NMT task. We report the results on X-Hindi pair, where X is one of Bengali, Gujarati, Marathi, Tamil, and Malayalam. The results are presented in the Table TABREF6 . We report BLEU scores and LeBLEU scores BIBREF30 . We observe that both the pre-ordering configurations significantly improve the BLEU scores over the baseline scores. We observe larger gains when generic pre-ordering rules are used compared to the Hindi-tuned pre-ordering rules.
These results support our hypothesis that word-order divergence can limit the benefits of multilingual translation. Reducing the word order divergence can improve translation in extremely low-resource scenarios.
An analysis of the outputs revealed that pre-ordering significantly reducing the number of UNK tokens (placeholder for unknown words) in the test output (Table TABREF14 ). We hypothesize that due to word order divergence between English and Indian languages, the encoder representation generated is not consistent leading to decoder generating unknown words. However, the pre-ordered models generate better contextual representations leading to less number of unknown tokens and better translation which is also reflected in the BLEU scores.
We experiment with two scenarios: (a) an extremely resource scarce scenario with no parallel corpus for child tasks, (b) varying amounts of parallel corpora available for child task.
|
What are the two scenarios in the experiment?
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(a) an extremely resource scarce scenario with no parallel corpus for child tasks, (b) varying amounts of parallel corpora available for child task.
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null | false
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What is a bicameral legislature?
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A legislative body comprised of two separate chambers
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Beaver Creek is a tributary of the Des Moines River that rises at the northern border of Boone County in the U.S. state of Iowa, and then flows generally south and southeast through western Boone County, northeastern Dallas County, and finally northwestern Polk County before flowing into the Des Moines River approximately a mile south of the Saylorville Reservoir in Polk County. In total, the main channel is approximately 77 miles (124 km) in length, and the watershed drains approximately 380 square miles (980 km2).
|
Extract from the text the name of the state where Beaver Creek is located
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Iowa
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null | false
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What is FrieslandCampina?
|
FrieslandCampina is one of the biggest dairy companies in the world. Their headquaters is in the Netherlands in Amersfoort. Its main brands are Friesche Vlag (or Frisian Flag in Indonesian market), Chocomel, Fristi, Friso, Dutch Lady, Milner, Campina, Landliebe, Optimel, Mona and "Mix'it"
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null | false
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Endless Nights in Aurora (Chinese: 極光之愛) is a 2014 Taiwanese romantic drama film directed by Lee Szu-yuan. It stars Rainie Yang and Chris Wang. It was released on December 19, 2014.
Revolving around the romantic relationship of two generations, Alisha and her mother Xiao-feng, two parallel love stories are re-enacted across two and a half decades. With equally heated passion, the star-crossed lovers in different generations are faithfully attached to their experiences in love through promises, anticipation, losses, and forgiveness.
|
In what year did Endless Nights come out?
|
2014
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null | false
| null |
Assassin's Creed is an open-world, action-adventure, and stealth game franchise published by Ubisoft and developed mainly by its studio Ubisoft Montreal using the game engine Anvil and its more advanced derivatives. Created by Patrice Désilets, Jade Raymond, and Corey May, the Assassin's Creed video game series depicts a fictional millennia-old struggle between the Order of Assassins, who fight for peace and free will, and the Knights Templar, who desire peace through order and control. The series features historical fiction, science fiction, and fictional characters intertwined with real-world historical events and historical figures. In most games, players control a historical Assassin while also playing as an Assassin Initiate or someone caught in the Assassin–Templar conflict in the present-day framing story. Considered a spiritual successor to the Prince of Persia series, Assassin's Creed took inspiration from the novel Alamut by the Slovenian writer Vladimir Bartol, based on the historical Hashashin sect of the medieval Middle East.
|
What is Assassin's Creed?
|
Assassin's Creed is a game franchise about a mythical group of assassin's fighting against the antagonists, the Templars. While the Assassin's fight for Freedom, the Templars fight for control and World domination. The game is hugely popular amongst the people who play video games. The series has historical characters which makes it even more popular amongst people who play video games. It was created by Ubisoft and is considered built off of Prince of Persia.
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null | false
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Which of the following animals are marine mammals: Human, Dog, Bonobos, Cat, Bats, Whale shark, Bears, Orangutans, Great white shark, Lion, Ocean sunfish, Koala, Cheetah, Beluga sturgeon, Orca, Gorillas, Camel, Hamsters, Lemurs, Blue whale, Chimpanzee
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Of those animals you mentioned, some of them are mammals, some are marine animals and only a smaller number of them are marine mammals. The following can be classified as marine mammals: Orca and Blue whale.
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What is deafblindness
|
Deafblindness is the condition of little or no useful hearing and little or no useful sight. Different degrees of vision loss and auditory loss occur within each individual. Because of this inherent diversity, each deafblind individual's needs regarding lifestyle, communication, education, and work need to be addressed based on their degree of dual-modality deprivation, to improve their ability to live independently. In 1994, an estimated 35,000–40,000 United States residents were medically deafblind. Helen Keller was a well-known example of a deafblind individual. To further her lifelong mission to help the deafblind community to expand its horizons and gain opportunities, the Helen Keller National Center for Deaf-Blind Youths and Adults (also called the Helen Keller National Center or HKNC), with a residential training program in Sands Point, New York, was established in 1967 by an act of Congress.
The deafblind community has its own culture, comparable to those of the deaf community and the blind community. Members of the deafblind community have diverse backgrounds but are united by similar experiences and a shared, homogeneous understanding of what it means to be deafblind. Some deafblind individuals view their condition as a part of their identity.
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1909.07734
| false
| null |
FLOAT SELECTED: Table 6: F-scores for Friends (%)
FLOAT SELECTED: Table 7: F-scores for EmotionPush (%)
The submissions and the final results are summarized in Tables and . Two of the submissions did not follow up with technical papers and thus they do not appear in this summary. We note that the top-performing models used BERT, reflecting the recent state-of-the-art performance of this model in many NLP tasks. For Friends and EmotionPush the top micro-F1 scores were 81.5% and 88.5% respectively.
FLOAT SELECTED: Table 6: F-scores for Friends (%)
FLOAT SELECTED: Table 7: F-scores for EmotionPush (%)
For Friends and EmotionPush the top micro-F1 scores were 81.5% and 88.5% respectively.
|
Who was the top-scoring team?
|
IDEA
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null | false
| null |
What's the best way to cook a soft-boiled egg?
|
The best way to cook a soft-boiled egg:
1. Add 1/2 inch of water into a pot.
2. Bring water to a boil.
3. Add the egg directly from the fridge.
4. Simmer the egg for 6 minutes
5. Drain the hot water and immediately submerge the egg in cold water
It's ready to eat when you are. Enjoy!
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Agriculture is an important sector in California's economy. Farming-related sales more than quadrupled over the past three decades, from $7.3 billion in 1974 to nearly $31 billion in 2004. This increase has occurred despite a 15 percent decline in acreage devoted to farming during the period, and water supply suffering from chronic instability. Factors contributing to the growth in sales-per-acre include more intensive use of active farmlands and technological improvements in crop production. In 2008, California's 81,500 farms and ranches generated $36.2 billion products revenue. In 2011, that number grew to $43.5 billion products revenue. The Agriculture sector accounts for two percent of the state's GDP and employs around three percent of its total workforce. According to the USDA in 2011, the three largest California agricultural products by value were milk and cream, shelled almonds, and grapes.
|
From the passage provided, extract the more recent available annual revenue from agriculture in dollars.
|
In 2011, California's agricultural product revenue was $43.5 billion.
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null | false
| 352
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Recently, chit-chat dialogue models have achieved improved performance in modelling a variety of conversational domains, including movie subtitles, Twitter chats and help forums BIBREF0, BIBREF1, BIBREF2, BIBREF3. These neural systems were used to model conversational dialogue via training on large chit-chat datasets such as the OpenSubtitles corpus, which contains generic dialogue conversations from movies BIBREF4. The datasets used do not have an explicit dialogue state to be modelled BIBREF5, but rather require the agent to learn the nuances of natural language in the context of casual peer-to-peer interaction.
Many recent chit-chat systems BIBREF2, BIBREF3 attempt to introduce increased diversity into model responses. However, dialogue systems have also been known to suffer from a lack of coherence BIBREF0. Given an input message history, systems often have difficulty tracking important information such as professions and names BIBREF0. It would be of benefit to create a system which extracts relevant features from the input that indicate which responses would be most appropriate, and conditions on this stored information to select the appropriate response.
A major problem with existing recurrent neural network (RNN) architectures is that these systems aggregate all input tokens into a state vector, which is passed to a decoder for generation of the final response, or in the case of a neural probabilistic language model BIBREF6, the state at each time step is used to predict the next token in the sequence. Ideally the size of the state should expand with the number of input tokens and should not lose important information about the input. However, RNN states are typically fixed sized, and for any chosen state size, there exists an input sequence length for which the RNN would not be able to store all relevant details for a final response. In addition, the RNN state undergoes constant transformation at each computational step. This makes it difficult to maintain a persistent storage of information that remains constant over many time steps.
The introduction of attention mechanisms BIBREF7 has sparked a change in the current design of RNN architectures. Instead of relying fully on a fixed-sized state vector, an attention mechanism allows each decoder word prediction step to extract relevant information from past states through a key-value query mechanism. However, this mechanism connects every input token with all preceeding ones via a computational step, increasing the complexity of the calculation to $O(N^2)$ for an input sequence size N. In the ideal case, the mapping of input conversation history to output response would have a computational complexity of $O(N)$. For this reason, it is desirable to have an information retrieval system that is both scale-able, but not proportional to input length.
We study the impact of accessible memory on response coherence by constructing a memory-augmented dialogue system. The motivation is that it would be beneficial to store details of the conversational history in a more permanent memory structure, instead of being captured inside a fixed-sized RNN hidden state. Our proposed system is able to both read and write to a persistent memory module after reading each input utterance. As such, it has access to a stable representation of the input message history when formulating a final response. We explore two distinct memory architectures with different properties, and compare their differences and benefits. We evaluate our proposed memory systems using perplexity evaluation, and compare them to competitive baselines.
They show that using a context recurrent neural network (RNN) to read representations at the utterance-level allows for a more top-down perspective on the dialogue history.
|
Does using a context recurrent neural network (RNN) to read representations at the utterance-level allow for a more top-down perspective on the dialogue history?
|
Yes, it does.
|
null | false
| null |
Queen Elizabeth II closed coffin was adorned with several interesting objects and symbols including what?
|
Personal flag, the Royal Standard Flag, crown jewels Orb and Sceptre
|
|
null | false
| null |
What is the latest iOS version on iPhone and what issues it addressed?
|
The latest iOS for Apple iPhone is iOS 16.4.
This has bought a lot of updates to the iPhone like:
- It introduced a new set of emojis
- latest security patch
- It introduced a voice isolation feature for iPhone, now people can not listen to background noise when they are on call
- Now Cloud Shared Photo Library can also detect duplicate photos, this will save your storage
- Crash detection is been optimised for iPhone 14 series phones
- iCloud was unresponsive sometimes has been addressed
- Now you can add notifications for web apps on the home screen itself.
- Many more features are added
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null | false
| null |
Guacamole is traditionally made by mashing peeled, ripe avocados and salt with a molcajete y tejolote (mortar and pestle). Recipes often call for lime juice, cilantro, onions, and jalapeños. Some non-traditional recipes may call for sour cream, tomatoes, basil, or peas. Due to the presence of polyphenol oxidase in the cells of avocado, exposure to oxygen in the air causes an enzymatic reaction and develops melanoidin pigment, turning the sauce brown. This result is generally considered unappetizing, and there are several methods (some anecdotal) that are used to counter this effect, such as storing the guacamole in an air-tight container or wrapping tightly in plastic to limit the surface area exposed to the air.
|
Extract the ingredients required to prepare guacamole from the text. Separate them with a comma.
|
Here are the ingredients from the paragraph to prepare Guacamole: Ripe avocados, salt, lime juice, cilantro, onions, and jalapeños. While these are the most commonly used, some non-traditional recipes may use sour cream, tomatoes, basil, or peas.
|
1909.08859
| false
| null |
In the following, we explain our Procedural Reasoning Networks model. Its architecture is based on a bi-directional attention flow (BiDAF) model BIBREF6, but also equipped with an explicit reasoning module that acts on entity-specific relational memory units. Fig. FIGREF4 shows an overview of the network architecture. It consists of five main modules: An input module, an attention module, a reasoning module, a modeling module, and an output module. Note that the question answering tasks we consider here are multimodal in that while the context is a procedural text, the question and the multiple choice answers are composed of images.
Note that the question answering tasks we consider here are multimodal in that while the context is a procedural text, the question and the multiple choice answers are composed of images.
|
What multimodality is available in the dataset?
|
The answers are shown as follows:
* context is a procedural text, the question and the multiple choice answers are composed of images
|
null | false
| null |
Tell me whether these are Mandalorians or Jedi: Yoda, Luke Skywalker, Bobba Fett, Din Djarin
|
Yoda: Jedi, Luke Skywalker: Jedi, Bobba Fett: Mandalorian, Din Djarin: Mandalorian
|
|
null | false
| null |
The Green Bay Packers are a professional American football team based in Green Bay, Wisconsin. The Packers compete in the National Football League (NFL) as a member club of the National Football Conference (NFC) North division. It is the third-oldest franchise in the NFL, dating back to 1919, and is the only non-profit, community-owned major league professional sports team based in the United States. Home games have been played at Lambeau Field since 1957. They have the most wins of any NFL franchise.
|
Who are the Green Bay Packers and who owns them?
|
The Green Bay Packers are a professional American football team based in Green Bay, Wisconsin. The Packers compete in the National Football League (NFL) as a member club of the National Football Conference (NFC) North division. The 'Packers' are the third-oldest franchise in the NFL, dating back to 1919, and is the only non-profit, community-owned major league professional sports team based in the United States.
|
null | false
| null |
Who amongst these are tennis players: Virat Kohli, Roger Federer, Rafael Nadal, Novak Djokovic, Serena Williams, PV Sindhu, Virender Sehwag, Maria Sharapova, Steffi Graf, Venus Williams.
|
Roger Federer, Rafael Nadal, Novak Djokovic, Serena Williams, Maria Sharapova, Steffi Graf, Venus Williams are tennis players.
|
|
null | false
| null |
Zijldijk has three churches. The Mennomite church was built in 1772 in a non conspicuous barn-like building. It is still in use as a church. The Dutch Reformed church has been reconstructed as a village house. The Reformed Church was constructed in 1886, and nowadays serves as a care facility.
|
Given the passage about churches built in the village of Zijldijk in the Netherlands, when was the only running church built?
|
The Mennomite church was built in 1772 and is still in use as a church.
|
null | false
| 209
|
In this section, we describe the corpus and the alternative representations that we employ in this work.
We have created the HispaBlogs dataset by collecting posts from Spanish blogs from five different countries: Argentina, Chile, Mexico, Peru and Spain. For each country, there are 450 and 200 blogs respectively for training and test, ensuring that each author appears only in one set.
|
What content did the HispaBlogs corpus collect?
|
It collected posts from Spanish blogs from five different countries: Argentina, Chile, Mexico, Peru and Spain.
|
1809.04960
| false
| null |
We select a large-scale Chinese dataset BIBREF0 with millions of real comments and a human-annotated test set to evaluate our model. The dataset is collected from Tencent News, which is one of the most popular Chinese websites for news and opinion articles. The dataset consists of 198,112 news articles. Each piece of news contains a title, the content of the article, and a list of the users' comments. Following the previous work BIBREF0 , we tokenize all text with the popular python package Jieba, and filter out short articles with less than 30 words in content and those with less than 20 comments. The dataset is split into training/validation/test sets, and they contain 191,502/5,000/1,610 pieces of news, respectively. The whole dataset has a vocabulary size of 1,858,452. The average lengths of the article titles and content are 15 and 554 Chinese words. The average comment length is 17 words.
The dataset consists of 198,112 news articles.
|
How many articles did they have?
|
The answers are shown as follows:
* 198,112
|
null | false
| 469
|
Figure 9: The histogram of Pearson distance between Hn and 10000 benign users’ hardness degree histogram and Hn and 10000 adversaries’ hardness degree histogram for various attacks. STL10 users are benign users for CIFAR10 target classifier and are adversaries for CIFAR100 target classifier.
|
Table 3-4: Going by the table alone, are there a range of thresholds δ where HODA performs poorly?
|
To address the concern of the respected reviewer, Figure 9 in Appendix I shows the Pearson distance histogram of 10000 adversaries and 10000 benign users for all attacks. Figure 9 indicates the histogram of Pearson distance between Hn and benign users' hardness degree histogram (samples of negative class in confusion matrix) and also Hn and adversaries' hardness degree histogram (samples of positive class in confusion matrix) for nums=100. Since HODA can completely separate benign users from adversaries, the AUC score of HODA for all four attacks is 1.
|
null | false
| 388
|
In the context of investigative journalism, we address the problem of automatically identifying which claims in a given document are most worthy and should be prioritized for fact-checking. Despite its importance, this is a relatively understudied problem. Thus, we create a new dataset of political debates, containing statements that have been fact-checked by nine reputable sources, and we train machine learning models to predict which claims should be prioritized for fact-checking, i.e., we model the problem as a ranking task. Unlike previous work, which has looked primarily at sentences in isolation, in this paper we focus on a rich input representation modeling the context: relationship between the target statement and the larger context of the debate, interaction between the opponents, and reaction by the moderator and by the public. Our experiments show state-of-the-art results, outperforming a strong rivaling system by a margin, while also confirming the importance of the contextual information.
Thus, we create a new dataset of political debates, containing statements that have been fact-checked by nine reputable sources, and we train machine learning models to predict which claims should be prioritized for fact-checking, i.e., we model the problem as a ranking task.
|
What does the new dataset of political debates contain?
|
It contains statements that have been fact-checked by nine reputable sources.
|
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