Tootfinder

Steelers OC Arthur Smith on offseason changes: 'I've had to adapt' https://www.nfl.com/news/steelers-oc-arthur-smith-on-offseason-changes-i-ve-had-to-adapt

Predictive Control Strategies for Sustaining Innovation Adoption on Multilayer Social Networks
Martina Alutto, Qiulin Xu, Fabrizio Dabbene, Hideaki Ishii, Chiara Ravazzi
https://arxiv.org/abs/2509.01457

Predictive Control Strategies for Sustaining Innovation Adoption on Multilayer Social Networks
This paper studies an optimal control problem for an adoption-opinion model that couples innovation adoption with opinion formation on a multilayer network. Adoption spreads through social contagion and perceived benefits, while opinions evolve via social interactions and feedback from adoption levels. Individuals may abandon adoption due to dissatisfaction or external constraints, potentially hindering diffusion. We analyze system equilibria and their stability, identifying conditions under wh…

TeRA: Vector-based Random Tensor Network for High-Rank Adaptation of Large Language Models
Yuxuan Gu, Wuyang Zhou, Giorgos Iacovides, Danilo Mandic
https://arxiv.org/abs/2509.03234

TeRA: Vector-based Random Tensor Network for High-Rank Adaptation of Large Language Models
Parameter-Efficient Fine-Tuning (PEFT) methods, such as Low-Rank Adaptation (LoRA), have significantly reduced the number of trainable parameters needed in fine-tuning large language models (LLMs). Subsequent developments of LoRA-style adapters have diverged into two main directions: (1) enhancing model expressivity with high-rank adapters, and (2) pushing for further parameter reduction, as exemplified by vector-based methods. However, these approaches present a trade-off, as achieving the exp…

Adaptive Iterative Soft-Thresholding Algorithm with the Median Absolute Deviation
Yining Feng, Ivan Selesnick
https://arxiv.org/abs/2507.02084 https://

Adaptive Iterative Soft-Thresholding Algorithm with the Median Absolute Deviation
The adaptive Iterative Soft-Thresholding Algorithm (ISTA) has been a popular algorithm for finding a desirable solution to the LASSO problem without explicitly tuning the regularization parameter $λ$. Despite that the adaptive ISTA is a successful practical algorithm, few theoretical results exist. In this paper, we present the theoretical analysis on the adaptive ISTA with the thresholding strategy of estimating noise level by median absolute deviation. We show properties of the fixed points …

O'Reilly: GenAI has adopted a colonialist business model.
https://www.linkedin.com/posts/timo3_proud-of-the-cloudflare-team-working-to-build-activity-7345899260506271745-mlHS

If you want to understand why O'Reilly is a supporter of this announcement, and want to ask both me and Matthew Prince about it, join our July 14 conversation on Live with Tim O'Reilly. | Tim O'Reilly
If you want to understand why O'Reilly is a supporter of this announcement, and want to ask both me and Matthew Prince about it, join our July 14 conversation on Live with Tim O'Reilly. AI has adopted colonialism as its business model: Extract resources from others and use it to enrich yourself and your customers at the expense of those whose resources you have taken, without giving much back. It's high time we started developing new mechanisms to enable content monetization for creators, not …

Adapting Language Models to Indonesian Local Languages: An Empirical Study of Language Transferability on Zero-Shot Settings
Rifki Afina Putri
https://arxiv.org/abs/2507.01645

Adapting Language Models to Indonesian Local Languages: An Empirical Study of Language Transferability on Zero-Shot Settings
In this paper, we investigate the transferability of pre-trained language models to low-resource Indonesian local languages through the task of sentiment analysis. We evaluate both zero-shot performance and adapter-based transfer on ten local languages using models of different types: a monolingual Indonesian BERT, multilingual models such as mBERT and XLM-R, and a modular adapter-based approach called MAD-X. To better understand model behavior, we group the target languages into three categori…

LobRA: Multi-tenant Fine-tuning over Heterogeneous Data
Sheng Lin, Fangcheng Fu, Haoyang Li, Hao Ge, Xuanyu Wang, Jiawen Niu, Yaofeng Tu, Bin Cui
https://arxiv.org/abs/2509.01193

LobRA: Multi-tenant Fine-tuning over Heterogeneous Data
With the breakthrough of Transformer-based pre-trained models, the demand for fine-tuning (FT) to adapt the base pre-trained models to downstream applications continues to grow, so it is essential for service providers to reduce the cost of processing FT requests. Low-rank adaption (LoRA) is a widely used FT technique that only trains small-scale adapters and keeps the base model unaltered, conveying the possibility of processing multiple FT tasks by jointly training different LoRA adapters wit…

Uncertainty-aware Test-Time Training (UT$^3$) for Efficient On-the-fly Domain Adaptive Dense Regression
Uddeshya Upadhyay
https://arxiv.org/abs/2509.03012 https://

Uncertainty-aware Test-Time Training (UT$^3$) for Efficient On-the-fly Domain Adaptive Dense Regression
Deep neural networks (DNNs) are increasingly being used in autonomous systems. However, DNNs do not generalize well to domain shift. Adapting to a continuously evolving environment is a safety-critical challenge inevitably faced by all autonomous systems deployed to the real world. Recent work on test-time training proposes methods that adapt to a new test distribution on the fly by optimizing the DNN model for each test input using self-supervision. However, these techniques result in a sharp …

SPENCER: Self-Adaptive Model Distillation for Efficient Code Retrieval
Wenchao Gu, Zongyi Lyu, Yanlin Wang, Hongyu Zhang, Cuiyun Gao, Michael R. Lyu
https://arxiv.org/abs/2508.00546

SPENCER: Self-Adaptive Model Distillation for Efficient Code Retrieval
Code retrieval aims to provide users with desired code snippets based on users' natural language queries. With the development of deep learning technologies, adopting pre-trained models for this task has become mainstream. Considering the retrieval efficiency, most of the previous approaches adopt a dual-encoder for this task, which encodes the description and code snippet into representation vectors, respectively. However, the model structure of the dual-encoder tends to limit the model's perf…

Speech Adaptation Relies More on Time Than Practice
https://scienmag.com/speech-adaptation-relies-more-on-time-than-practice/