State-of-the-art cross-encoders can be fine-tuned to be highly effective in passage re-ranking. The typical fine-tuning process of cross-encoders as re-rankers requires large amounts of manually labelled data, a contrastive learning objective, and a set of heuristically sampled negatives. An alternative recent approach for fine-tuning instead involves teaching the model to mimic the rankings of a highly effective large language model using a distillation objective. These fine-tuning strategies can be applied either individually, or in sequence. In this work, we systematically investigate the effectiveness of point-wise cross-encoders when fine-tuned independently in a single stage, or sequentially in two stages. Our experiments show that the effectiveness of point-wise cross-encoders fine-tuned using contrastive learning is indeed on par with that of models fine-tuned with multi-stage approaches. Code is available for reproduction at https://github.com/fpezzuti/multistage-finetuning.

Dolphins seem to make open-mouthed facial expressions most often while they are visible to a playmate, suggesting such displays may be similar to human smiles. While we often perceive these as a smile, there has been little research on facial communication in dolphins. We're finally realising that many species are To find out more, Elisabetta Palagi at the University of Pisa, Italy, and her colleagues analysed the behaviour of 22 captive bottlenose dolphins (Tursiops truncatus) at two wildlife parks: Zoomarine Rome in Italy and Planète Sauvage in Port-Saint-Père, France. In 80 hours of footage, the team observed a total of 1288 open-mouth expressions during social play sessions. More than 90 per cent of these events occurred during play between dolphins, with the rest happening during interactions between the dolphins and people.

Robotic microsurgery company Medical Microinstruments announced today that it raised $75 million in a Series B financing round. Pisa, Italy–based Medical Microinstruments plans to use proceeds from the financing round, along with its planned U.S. presence, to move into its next stage of growth through expanded indications and ongoing commercialization efforts for its Symani microsurgery system. The company designed Symani to address the challenges of microsurgery with the NanoWrist instruments for accessing and suturing small, delicate anatomy, such as veins, arteries, nerves and lymphatic vessels as small as 0.3mm in diameter. It provides motion scaling and tremor reduction to allow precise micro-movements. Symani received CE mark in 2019, and the company intends to accelerate commercialization in the U.S. and Asia-Pacific, as well as advance clinical research through an FDA investigational device exemption (IDE) pivotal study.

Bio: Angelica Lo Duca (Medium) works as post-doc at the Institute of Informatics and Telematics of the National Research Council (IIT-CNR) in Pisa, Italy. She is Professor of "Data Journalism" for the Master degree course in Digital Humanities at the University of Pisa. Her research interests include Data Science, Data Analysis, Text Analysis, Open Data, Web Applications and Data Journalism, applied to the fields of society, tourism and cultural heritage. She used to work on Data Security, Semantic Web and Linked Data. Angelica is also an enthusiastic tech writer.

A football player wears a vest holding a GPS sensor. The data captured feed into an algorithm.Credit: Matthew Ashton/AMA/Corbis via Getty In 2005, 17-year-old aspiring footballer Alessio Rossi tore two ligaments in his right ankle during training for lower league Italian football club USD Olginatese. The injury ended his dream of playing at the highest level. Today, Rossi is a postdoctoral researcher at the University of Pisa, Italy, where he collects and analyses reams of data to help prevent players at top teams getting injuries of their own. When Rossi was playing, his coaches' instincts and experiences were all they had to predict whether he might receive an injury.

A robot conducts the Orchestra Filarmonica di Lucca at Teatro Verdi in Pisa, Italy, this September.

In recent years, robots have been taking on a number of tasks previously considered impossible, and along the way proving us wrong about the extent of their capabilities. Well, last night the humanoid robot known as YuMi--a clever combination of the words'you and me'--did just that when he conducted the Lucca Philharmonic Orchestra at the Verdi Theatre in Pisa, Italy. Also present was Italian tenor Andrea Bocelli. Rehearsals were allowed for the robot to memorize and incorporate the precise hand movements and gestures used by resident conductor Andrea Colombini. This was assuming, no doubt, that the musicians were able to maintain a consistent tempo.

You might have heard someone say that "one day robots will replace humans, they'll even be able to conduct an orchestra!". Well, that day has arrived. Enter YuMi, a dual-arm robot created by ABB, who made a stunning conducting debut in the historical Teatro Verdi, in Pisa, Italy. He directed Andrea Bocelli, the popular Italian tenor, as he sang "La Donna è Mobile", the aria from Verdi's Rigoletto. Even if you're a classical music expert, I challenge you to close your eyes and listen carefully to YuMi's direction.

On Tuesday evening a robot took the stage of the Verdi Theater in Pisa, Italy. The robot was there to conduct the Lucca Philharmonic orchestra for three of the 18 arrangements that night. The event was part of the International Robotics Festival there. The robot was created by the Swiss company ABB and its name, YuMi, stands for "You and Me." The description of the bot says it's "working together to create endless possibilities."

Italian tenor Andrea Bocelli, left, performs Giuseppe Verdi's opera "La Donna e' Mobile", on stage next to the robot YuMi conducting the Lucca Philharmonic Orchestra, at the Verdi Theater, in Pisa, Italy, Tuesday, Sept. 12, 2017. A world famous tenor, a celebrated orchestra and a robot conductor were the highlight of Pisa's inaugural International Robotics Festival which runs from Sept. 7 to Sept. 13.