Tootfinder

CORE-BEHRT: A Carefully Optimized and Rigorously Evaluated BEHRT
Mikkel Odgaard, Kiril Vadimovic Klein, Sanne M{\o}ller Thysen, Espen Jimenez-Solem, Martin Sillesen, Mads Nielsen
https://arxiv.org/abs/2404.15201

CORE-BEHRT: A Carefully Optimized and Rigorously Evaluated BEHRT
BERT-based models for Electronic Health Records (EHR) have surged in popularity following the release of BEHRT and Med-BERT. Subsequent models have largely built on these foundations despite the fundamental design choices of these pioneering models remaining underexplored. To address this issue, we introduce CORE-BEHRT, a Carefully Optimized and Rigorously Evaluated BEHRT. Through incremental optimization, we isolate the sources of improvement for key design choices, giving us insights into the…

Well, this explains quite a bit.
(Taken from an article discussing the newly released Apple AI program, in which we discover the source of corporate interest in AI.)

The Conservative Partnership Institute,
a nonprofit whose funding skyrocketed after it became a nerve center for President Donald J. Trump’s allies in Washington,
has paid at least $3.2 million since the start of 2021 to corporations led by its own leaders or their relatives, records show.
In its most recent tax filings, the nonprofit’s three highest-paid contractors were all connected to insiders.
One was led by the institute’s president,

Trump-Allied Nonprofit Paid Millions to Companies Run by Insiders
The Conservative Partnership Institute’s three highest-paid contractors had connections to the group’s leaders or their relatives, raising concerns about self-dealing.

InstructNav: Zero-shot System for Generic Instruction Navigation in Unexplored Environment
Yuxing Long, Wenzhe Cai, Hongcheng Wang, Guanqi Zhan, Hao Dong
https://arxiv.org/abs/2406.04882

InstructNav: Zero-shot System for Generic Instruction Navigation in Unexplored Environment
Enabling robots to navigate following diverse language instructions in unexplored environments is an attractive goal for human-robot interaction. However, this goal is challenging because different navigation tasks require different strategies. The scarcity of instruction navigation data hinders training an instruction navigation model with varied strategies. Therefore, previous methods are all constrained to one specific type of navigation instruction. In this work, we propose InstructNav, a g…

Do Large Language Models Understand Conversational Implicature -- A case study with a chinese sitcom
Shisen Yue, Siyuan Song, Xinyuan Cheng, Hai Hu
https://arxiv.org/abs/2404.19509 https://arxiv.org/pdf/2404.19509
arXiv:2404.19509v1 Announce Type: new
Abstract: Understanding the non-literal meaning of an utterance is critical for large language models (LLMs) to become human-like social communicators. In this work, we introduce SwordsmanImp, the first Chinese multi-turn-dialogue-based dataset aimed at conversational implicature, sourced from dialogues in the Chinese sitcom $\textit{My Own Swordsman}$. It includes 200 carefully handcrafted questions, all annotated on which Gricean maxims have been violated. We test eight close-source and open-source LLMs under two tasks: a multiple-choice question task and an implicature explanation task. Our results show that GPT-4 attains human-level accuracy (94%) on multiple-choice questions. CausalLM demonstrates a 78.5% accuracy following GPT-4. Other models, including GPT-3.5 and several open-source models, demonstrate a lower accuracy ranging from 20% to 60% on multiple-choice questions. Human raters were asked to rate the explanation of the implicatures generated by LLMs on their reasonability, logic and fluency. While all models generate largely fluent and self-consistent text, their explanations score low on reasonability except for GPT-4, suggesting that most LLMs cannot produce satisfactory explanations of the implicatures in the conversation. Moreover, we find LLMs' performance does not vary significantly by Gricean maxims, suggesting that LLMs do not seem to process implicatures derived from different maxims differently. Our data and code are available at https://github.com/sjtu-compling/llm-pragmatics.

Satellite Drag Analysis During the May 2024 Geomagnetic Storm
William E. Parker, Richard Linares
https://arxiv.org/abs/2406.08617 https://

Satellite Drag Analysis During the May 2024 Geomagnetic Storm
Between May 10-12, 2024, Earth saw its largest geomagnetic storm in over 20 years. Since the last major storm in 2003, the population of satellites in low Earth orbit has surged following the commercialization of space services and the ongoing establishment of proliferated LEO constellations. In this note, we investigate the various impacts of the geomagnetic storm on satellite operations. A forecast performance assessment of the geomagnetic index ap shows that the magnitude and duration of the…

Optimally Improving Cooperative Learning in a Social Setting
Shahrzad Haddadan, Cheng Xin, Jie Gao
https://arxiv.org/abs/2405.20808 https://

Optimally Improving Cooperative Learning in a Social Setting
We consider a cooperative learning scenario where a collection of networked agents with individually owned classifiers dynamically update their predictions, for the same classification task, through communication or observations of each other's predictions. Clearly if highly influential vertices use erroneous classifiers, there will be a negative effect on the accuracy of all the agents in the network. We ask the following question: how can we optimally fix the prediction of a few classifiers s…

This https://arxiv.org/abs/2406.05763 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

WenetSpeech4TTS: A 12,800-hour Mandarin TTS Corpus for Large Speech Generation Model Benchmark
With the development of large text-to-speech (TTS) models and scale-up of the training data, state-of-the-art TTS systems have achieved impressive performance. In this paper, we present WenetSpeech4TTS, a multi-domain Mandarin corpus derived from the open-sourced WenetSpeech dataset. Tailored for the text-to-speech tasks, we refined WenetSpeech by adjusting segment boundaries, enhancing the audio quality, and eliminating speaker mixing within each segment. Following a more accurate transcriptio…

Thermodynamics of the most generalized form of Holographic Dark Energy and some particular cases with Corrected Entropies
Sanghati Saha, Ertan G\"udekli, Surajit Chattopadhyay
https://arxiv.org/abs/2405.20783

Thermodynamics of the most generalized form of Holographic Dark Energy and some particular cases with Corrected Entropies
The holographic cut-off in generalized dark energy (HDE) formalism depends on its cut-off. Following this, a four-parameter generalized entropy has recently been developed. It reduces to various known entropies for appropriate parameter limits in the study of Odintsov, S. D., S. DOnofrio, and T. Paul. (2023) Physics of the Dark Universe, 42 pp: 101277. In the current work, we investigate the evolution of the universe in its early phase and late phase within the framework of entropic cosmology, …