Analogy-Based Estimation (ABE) is a popular method for non-algorithmic estimation due to its simplicity and effectiveness. The Analogy-Based Estimation (ABE) model was proposed by researchers, however, no optimal approach for reliable estimation was developed. Achieving high accuracy in the ABE might be challenging for new software projects that differ from previous initiatives. This study (conducted in June 2024) proposes a Firefly Algorithm-guided Analogy-Based Estimation (FAABE) model that combines FA with ABE to improve estimation accuracy. The FAABE model was tested on five publicly accessible datasets: Cocomo81, Desharnais, China, Albrecht, Kemerer and Maxwell. To improve prediction efficiency, feature selection was used. The results were measured using a variety of evaluation metrics; various error measures include MMRE, MAE, MSE, and RMSE. Compared to conventional models, the experimental results show notable increases in prediction precision, demonstrating the efficacy of the Firefly-Analogy ensemble.

Model ensembling is a technique to combine the predicted distributions of two or more models, often leading to improved robustness and performance. For ensembling in text generation, the next token's probability distribution is derived from a weighted sum of the distributions of each individual model. This requires the underlying models to share the same subword vocabulary, limiting the applicability of ensembling, since many open-sourced models have distinct vocabularies. In research settings, experimentation or upgrades to vocabularies may introduce multiple vocabulary sizes. This paper proposes an inference-time only algorithm that allows for ensembling models with different vocabularies, without the need to learn additional parameters or alter the underlying models. Instead, the algorithm ensures that tokens generated by the ensembled models \textit{agree} in their surface form. We apply this technique to combinations of traditional encoder-decoder models and decoder-only LLMs and evaluate on machine translation. In addition to expanding to model pairs that were previously incapable of token-level ensembling, our algorithm frequently improves translation performance over either model individually.

When I was a kid, the gadgets in any given movie or TV show were the real stars. John Connor's handheld Atari, Marty McFly's self-lacing Nikes, and about a million different variations on the radio watch were what I dreamed of owning one day. So I feel a certain kinship with YouTuber Abe's Projects, who took his love for fictional gadgets one step further and made a real version of the Pokedex from the Pokemon cartoon. If you weren't the right age in the late 90s, the Pokedex is a handheld computer riffing on the Palm Pilots of the day. Its sole purpose is to identify and catalog Pokemon creatures in the wild.

In developed nations assassinations are rare and thus the impact of such acts on the electoral and political landscape is understudied. In this paper, we focus on Twitter data to examine the effects of Japan's former Primer Minister Abe's assassination on the Japanese House of Councillors elections in 2022. We utilize sentiment analysis and emotion detection together with topic modeling on over 2 million tweets and compare them against tweets during previous election cycles. Our findings indicate that Twitter sentiments were negatively impacted by the event in the short term and that social media attention span has shortened. We also discuss how "necropolitics" affected the outcome of the elections in favor of the deceased's party meaning that there seems to have been an effect of Abe's death on the election outcome though the findings warrant further investigation for conclusive results.. Keywords Japanese House of Councillors Elections; Abe assassination; sentiment analysis ...

Multilingual semantic parsing aims to leverage the knowledge from the high-resource languages to improve low-resource semantic parsing, yet commonly suffers from the data imbalance problem. Prior works propose to utilize the translations by either humans or machines to alleviate such issues. However, human translations are expensive, while machine translations are cheap but prone to error and bias. In this work, we propose an active learning approach that exploits the strengths of both human and machine translations by iteratively adding small batches of human translations into the machine-translated training set. Besides, we propose novel aggregated acquisition criteria that help our active learning method select utterances to be manually translated. Our experiments demonstrate that an ideal utterance selection can significantly reduce the error and bias in the translated data, resulting in higher parser accuracies than the parsers merely trained on the machine-translated data.

Prominent approaches to belief revision prescribe the adoption of a new belief that is as close as possible to the prior belief, in a process that, even in the standard case, can be described as attempting to minimize surprise. Here we extend the existing model by proposing a measure of surprise, dubbed relative surprise, in which surprise is computed with respect not just to the prior belief, but also to the broader context provided by the new information, using a measure derived from familiar distance notions between truth-value assignments. We characterize the surprise minimization revision operator thus defined using a set of intuitive rationality postulates in the AGM mould, along the way obtaining representation results for other existing revision operators in the literature, such as the Dalal operator and a recently introduced distance-based min-max operator.

When Japan won the competition to host the 2020 Olympics in the wake of a devastating earthquake and tsunami, then-Prime Minister Shinzo Abe said it would be a "tremendous opportunity for Tokyo and for Japan to shine at the very center of the world stage." Lauding his country as among the safest in the world, Abe vowed in 2013 that problems surrounding the crippled Fukushima nuclear plant would be resolved and hordes of overseas visitors would see that Japan is "marvelous." Plans raced ahead for new casinos, driverless taxis and a futuristic stadium to dazzle tourists. Yet many of those projects fell into disarray long before the pandemic forced Abe to postpone the games last year. And now just weeks before the rescheduled opening ceremony on July 23, a resurgent outbreak coupled with one of the slowest vaccine rollouts in Asia has prompted even top business leaders to call for them to be delayed again or scrapped altogether -- shining a spotlight on how Japan's Olympic ambitions have deteriorated.

Prime Minister Shinzo Abe will cancel plans to visit Saudi Arabia, the United Arab Emirates, and Oman this weekend, TV Asahi reported on Wednesday, after Iran struck back at the United States for the killing of a top Iranian general. Kyodo News reported separately that Abe convened a National Security Council (NSC) meeting, likely to discuss Iran's attack on U.S. forces based in Iraq. Iranian state TV said it was in revenge for the U.S. killing of Revolutionary Guard Gen. Qassem Soleimani, whose death last week in an American drone strike near Baghdad prompted angry calls to avenge his slaying.

Finding new medicines is like finding a needle in a haystack. By linking a powerful computational ... [ ] approach to advances in chemical manufacturing, this company is making piles of needles. Finding new drugs is hard. Sometimes we don't even know how a disease works, and drug tests in animals don't always go the same as in humans. Drugs can even behave very differently from person to person.

Japan has told the United States it is ready to provide its robot technology for use in dismantling nuclear and uranium enrichment facilities in North Korea as Washington and Pyongyang pursue further denuclearization talks, government sources said Friday. As Japan turns to the remotely controlled robots it has developed to decommission reactors crippled by the triple core meltdown in 2011 at the Fukushima No. 1 power plant, it believes the same technology can be used in North Korea, according to the sources. The offer is part of Japan's efforts to make its own contribution to the denuclearization talks amid concern that Tokyo could be left out of the loop as the United States and North Korea step up diplomacy. Tokyo has already told Washington it would shoulder part of the costs of any International Atomic Energy Agency inspections of North Korean facilities and dispatch its own nuclear experts to help. The scrapping of nuclear facilities, such as the Yongbyon complex, which has a graphite-moderated reactor, will come into focus in forthcoming working-level talks between Washington and Pyongyang.