Tootfinder

Psychological safety in software workplaces: A systematic literature review
Beatriz Santana, Lidiv\^anio Monte, Bianca Santana de Ara\'ujo Silva, Glauco Carneiro, S\'avio Freire, Jos\'e Amancio Macedo Santos, Manoel Mendon\c{c}a
https://arxiv.org/abs/2508.03369

Psychological safety in software workplaces: A systematic literature review
Context: Psychological safety (PS) is an important factor influencing team well-being and performance, particularly in collaborative and dynamic domains such as software development. Despite its acknowledged significance, research on PS within the field of software engineering remains limited. The socio-technical complexities and fast-paced nature of software development present challenges to cultivating PS. To the best of our knowledge, no systematic secondary study has synthesized existing kn…

NEURODNAAI: Neural pipeline approaches for the advancing dna-based information storage as a sustainable digital medium using deep learning framework
Rakesh Thakur, Lavanya Singh, Yashika, Manomay Bundawala, Aruna Kumar
https://arxiv.org/abs/2510.02417

NEURODNAAI: Neural pipeline approaches for the advancing dna-based information storage as a sustainable digital medium using deep learning framework
DNA is a promising medium for digital information storage for its exceptional density and durability. While prior studies advanced coding theory, workflow design, and simulation tools, challenges such as synthesis costs, sequencing errors, and biological constraints (GC-content imbalance, homopolymers) limit practical deployment. To address this, our framework draws from quantum parallelism concepts to enhance encoding diversity and resilience, integrating biologically informed constraints with…

Automated Multi-Agent Workflows for RTL Design
Amulya Bhattaram, Janani Ramamoorthy, Ranit Gupta, Diana Marculescu, Dimitrios Stamoulis
https://arxiv.org/abs/2509.20182 https://…

Automated Multi-Agent Workflows for RTL Design
The rise of agentic AI workflows unlocks novel opportunities for computer systems design and optimization. However, for specialized domains such as program synthesis, the relative scarcity of HDL and proprietary EDA resources online compared to more common programming tasks introduces challenges, often necessitating task-specific fine-tuning, high inference costs, and manually-crafted agent orchestration. In this work, we present VeriMaAS, a multi-agent framework designed to automatically compo…

Accelerated Interactive Auralization of Highly Reverberant Spaces using Graphics Hardware
Hannes Rosseel, Toon van Waterschoot
https://arxiv.org/abs/2509.04390 https://

Accelerated Interactive Auralization of Highly Reverberant Spaces using Graphics Hardware
Interactive acoustic auralization allows users to explore virtual acoustic environments in real-time, enabling the acoustic recreation of concert hall or Historical Worship Spaces (HWS) that are either no longer accessible, acoustically altered, or impractical to visit. Interactive acoustic synthesis requires real-time convolution of input signals with a set of synthesis filters that model the space-time acoustic response of the space. The acoustics in concert halls and HWS are both characteriz…

Atom-Searcher: Enhancing Agentic Deep Research via Fine-Grained Atomic Thought Reward
Yong Deng, Guoqing Wang, Zhenzhe Ying, Xiaofeng Wu, Jinzhen Lin, Wenwen Xiong, Yuqin Dai, Shuo Yang, Zhanwei Zhang, Qiwen Wang, Yang Qin, Changhua Meng
https://arxiv.org/abs/2508.12800

Atom-Searcher: Enhancing Agentic Deep Research via Fine-Grained Atomic Thought Reward
Large language models (LLMs) exhibit remarkable problem-solving abilities, but struggle with complex tasks due to static internal knowledge. Retrieval-Augmented Generation (RAG) enhances access to external information, yet remains limited in multi-hop reasoning and strategic search due to rigid workflows. Recent advancements in agentic deep research empower LLMs to autonomously reason, search, and synthesize information. However, current approaches relying on outcome-based reinforcement learnin…

Sonnet 065 - LXV
Since brass, nor stone, nor earth, nor boundless sea,
But sad mortality o'ersways their power,
How with this rage shall beauty hold a plea,
Whose action is no stronger than a flower?
O! how shall summer's honey breath hold out,
Against the wrackful siege of battering days,
When rocks impregnable are not so stout,
Nor gates of steel so strong but Time decays?
O fearful meditation! where, alack,
Shall Time'…

The Evolving Role of Large Language Models in Scientific Innovation: Evaluator, Collaborator, and Scientist
Haoxuan Zhang, Ruochi Li, Yang Zhang, Ting Xiao, Jiangping Chen, Junhua Ding, Haihua Chen
https://arxiv.org/abs/2507.11810

The Evolving Role of Large Language Models in Scientific Innovation: Evaluator, Collaborator, and Scientist
Scientific innovation is undergoing a paradigm shift driven by the rapid advancement of Large Language Models (LLMs). As science faces mounting challenges including information overload, disciplinary silos, and diminishing returns on conventional research methods, LLMs are emerging as powerful agents capable not only of enhancing scientific workflows but also of participating in and potentially leading the innovation process. Existing surveys mainly focus on different perspectives, phrases, and…

Sonnet 065 - LXV
Since brass, nor stone, nor earth, nor boundless sea,
But sad mortality o'ersways their power,
How with this rage shall beauty hold a plea,
Whose action is no stronger than a flower?
O! how shall summer's honey breath hold out,
Against the wrackful siege of battering days,
When rocks impregnable are not so stout,
Nor gates of steel so strong but Time decays?
O fearful meditation! where, alack,
Shall Time'…