Tootfinder

There are so many accounts by the #news media on #Threads, that could but do not yet federate. Doesn't make much sense to ask here for them to do that, so I posted something over there.
If you have an account and want more of the media federating, feel free to share the post:

Towards Generalist Robot Learning from Internet Video: A Survey
Robert McCarthy, Daniel C. H. Tan, Dominik Schmidt, Fernando Acero, Nathan Herr, Yilun Du, Thomas G. Thuruthel, Zhibin Li
https://arxiv.org/abs/2404.19664

Towards Generalist Robot Learning from Internet Video: A Survey
This survey presents an overview of methods for learning from video (LfV) in the context of reinforcement learning (RL) and robotics. We focus on methods capable of scaling to large internet video datasets and, in the process, extracting foundational knowledge about the world's dynamics and physical human behaviour. Such methods hold great promise for developing general-purpose robots. We open with an overview of fundamental concepts relevant to the LfV-for-robotics setting. This includes a d…

Towards Decoupling Frontend Enhancement and Backend Recognition in Monaural Robust ASR
Yufeng Yang, Ashutosh Pandey, DeLiang Wang
https://arxiv.org/abs/2403.06387

Towards Decoupling Frontend Enhancement and Backend Recognition in Monaural Robust ASR
It has been shown that the intelligibility of noisy speech can be improved by speech enhancement (SE) algorithms. However, monaural SE has not been established as an effective frontend for automatic speech recognition (ASR) in noisy conditions compared to an ASR model trained on noisy speech directly. The divide between SE and ASR impedes the progress of robust ASR systems, especially as SE has made major advances in recent years. This paper focuses on eliminating this divide with an ARN (atten…

This https://arxiv.org/abs/2201.12923 has been replaced.
link: https://scholar.google.com/scholar?q=a

Asynchronous Opinion Dynamics in Social Networks
Opinion spreading in a society decides the fate of elections, the success of products, and the impact of political or social movements. The model by Hegselmann and Krause is a well-known theoretical model to study such opinion formation processes in social networks. In contrast to many other theoretical models, it does not converge towards a situation where all agents agree on the same opinion. Instead, it assumes that people find an opinion reasonable if and only if it is close to their own. T…

Incentivizing News Consumption on Social Media Platforms Using Large Language Models and Realistic Bot Accounts
Hadi Askari, Anshuman Chhabra, Bernhard Clemm von Hohenberg, Michael Heseltine, Magdalena Wojcieszak
https://arxiv.org/abs/2403.13362

Incentivizing News Consumption on Social Media Platforms Using Large Language Models and Realistic Bot Accounts
Polarization, declining trust, and wavering support for democratic norms are pressing threats to U.S. democracy. Exposure to verified and quality news may lower individual susceptibility to these threats and make citizens more resilient to misinformation, populism, and hyperpartisan rhetoric. This project examines how to enhance users' exposure to and engagement with verified and ideologically balanced news in an ecologically valid setting. We rely on a large-scale two-week long field experimen…

This https://arxiv.org/abs/2310.17313 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Study of Galactic interactions and propagation properties of ultrahigh energy cosmic rays using the precision spectrum from the Pierre Auger Observatory
The AUGER Collaboration has recently published the precise energy spectrum of cosmic rays above 1 EeV, which exhibits rich and interesting features. These features provide an opportunity to investigate the galactic propagation and interaction of ultra-high-energy cosmic rays (UHECRs). While the classic dip model, which describes the UHECR propagation and interaction with CMB in extragalactic space by theoretical calculation, well explains the cutoff behaviour of the highest high energy spectrum…

Blending Data-Driven Priors in Dynamic Games
Justin Lidard, Haimin Hu, Asher Hancock, Zixu Zhang, Albert Gim\'o Contreras, Vikash Modi, Jonathan DeCastro, Deepak Gopinath, Guy Rosman, Naomi Leonard, Mar\'ia Santos, Jaime Fern\'andez Fisac
https://arxiv.org/abs/2402.14174

Blending Data-Driven Priors in Dynamic Games
As intelligent robots like autonomous vehicles become increasingly deployed in the presence of people, the extent to which these systems should leverage model-based game-theoretic planners versus data-driven policies for safe, interaction-aware motion planning remains an open question. Existing dynamic game formulations assume all agents are task-driven and behave optimally. However, in reality, humans tend to deviate from the decisions prescribed by these models, and their behavior is better a…

Friction and Memory Effects in Homogeneous Gas-Liquid Nucleation: Quest for Quantitative Rate Calculation
Subhajit Acharya, Biman Bagchi
https://arxiv.org/abs/2402.15126

Friction and Memory Effects in Homogeneous Gas-Liquid Nucleation: Quest for Quantitative Rate Calculation
The task of a first principles theoretical calculation of the rate of gas to liquid nucleation has remained largely incomplete despite the existence of reliable results from unbiased simulation studies at large supersaturation. Although the classical nucleation theory, formulated by Becker-Doring-Zeldovich (BDZ) about a century ago, provides an elegant, widely-used picture of nucleation in a first-order phase transition, the theory finds difficulties in predicting the rate accurately, especiall…

Blending Data-Driven Priors in Dynamic Games
Justin Lidard, Haimin Hu, Asher Hancock, Zixu Zhang, Albert Gim\'o Contreras, Vikash Modi, Jonathan DeCastro, Deepak Gopinath, Guy Rosman, Naomi Leonard, Mar\'ia Santos, Jaime Fern\'andez Fisac
https://arxiv.org/abs/2402.14174

Blending Data-Driven Priors in Dynamic Games
As intelligent robots like autonomous vehicles become increasingly deployed in the presence of people, the extent to which these systems should leverage model-based game-theoretic planners versus data-driven policies for safe, interaction-aware motion planning remains an open question. Existing dynamic game formulations assume all agents are task-driven and behave optimally. However, in reality, humans tend to deviate from the decisions prescribed by these models, and their behavior is better a…

Friction and Memory Effects in Homogeneous Gas-Liquid Nucleation: Quest for Quantitative Rate Calculation
Subhajit Acharya, Biman Bagchi
https://arxiv.org/abs/2402.15126

Friction and Memory Effects in Homogeneous Gas-Liquid Nucleation: Quest for Quantitative Rate Calculation
The task of a first principles theoretical calculation of the rate of gas to liquid nucleation has remained largely incomplete despite the existence of reliable results from unbiased simulation studies at large supersaturation. Although the classical nucleation theory, formulated by Becker-Doring-Zeldovich (BDZ) about a century ago, provides an elegant, widely-used picture of nucleation in a first-order phase transition, the theory finds difficulties in predicting the rate accurately, especiall…