Tootfinder

This https://arxiv.org/abs/2502.13681 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

Repo2Run: Automated Building Executable Environment for Code Repository at Scale
Scaling up executable code data is significant for improving language models' software engineering capability. The intricate nature of the process makes it labor-intensive, time-consuming and expert-knowledge-dependent to build a large number of executable code repositories, limiting the scalability of existing work based on running tests. The primary bottleneck lies in the automated building of test environments for different repositories, which is an essential yet underexplored task. To mitig…

GPU Implementation of Zippel Method for Feynman Integral Reconstruction
Alexander V. Smirnov, Boris I. Rozhnov, Vadim V. Voevodin
https://arxiv.org/abs/2505.24256

GPU Implementation of Zippel Method for Feynman Integral Reconstruction
The Zippel algorithm performs a rational reconstruction of multivariate polynomials and aims specifically at the sparse case. It is applied in different fields of science, lately becoming an important step in Feynman integral reduction in elementary particle physics. In some cases with multiple variables it might become a bottleneck for the whole evaluation so that different optimizations are required. In this paper we describe how we ported the classical Zippel algorithm together with its bala…

This https://arxiv.org/abs/2504.00587 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csMA_…

AgentNet: Decentralized Evolutionary Coordination for LLM-based Multi-Agent Systems
The rapid advancement of large language models (LLMs) has enabled the development of multi-agent systems where multiple LLM-based agents collaborate on complex tasks. However, existing systems often rely on centralized coordination, leading to scalability bottlenecks, reduced adaptability, and single points of failure. Privacy and proprietary knowledge concerns further hinder cross-organizational collaboration, resulting in siloed expertise. We propose AgentNet, a decentralized, Retrieval-Augme…

"The big problem is 'bottlenecks' that make it harder to produce housing, expand energy production, or build new roads and bridges."
vs.
"The big problem is that big corporations have way too much power over our economy and our government."
By 12pts all voters and by 42pts Dem voters prefer the second statement. They're right!

Poll: Democratic voters prefer "populism" over "abundance"
Democrats are asking themselves some hard questions as they ponder how they lost the 2024 election.

Oh, de ironie.
#NOS

Er is steeds meer geluid en dat is ongezond
Vandaag was de tweede Nationale Geluidmeetdag. Met een app kan iedereen doorgeven hoe stil of luidruchtig de buitenomgeving is. De bedoeling is dat dat adviezen oplevert over hoe de omgeving beter kan worden ingericht.

This https://arxiv.org/abs/2407.02722 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Pulse Design of Baseband Flux Control for Adiabatic Controlled-Phase Gates in Superconducting Circuits
Despite progress towards achieving low error rates with superconducting qubits, error-prone two-qubit gates remain a bottleneck for realizing large-scale quantum computers. Therefore, a systematic framework to design high-fidelity gates becomes imperative. One type of two-qubit gate in superconducting qubits is the controlled-phase (CPHASE) gate, which utilizes a conditional interaction between higher energy levels of the qubits controlled by a baseband flux pulse on one of the qubits or a tuna…

Weekend #Plankton Factoid 🦠🦐
Plankton is fundamental to the functioning of aquatic #ecosystems. An example was seen in the 2013 deaths of #Florida bottlenose dolphins. Dense harmful phytoplankton

DX100: A Programmable Data Access Accelerator for Indirection
Alireza Khadem, Kamalavasan Kamalakkannan, Zhenyan Zhu, Akash Poptani, Yufeng Gu, Jered Benjamin Dominguez-Trujillo, Nishil Talati, Daichi Fujiki, Scott Mahlke, Galen Shipman, Reetuparna Das
https://arxiv.org/abs/2505.23073

DX100: A Programmable Data Access Accelerator for Indirection
Indirect memory accesses frequently appear in applications where memory bandwidth is a critical bottleneck. Prior indirect memory access proposals, such as indirect prefetchers, runahead execution, fetchers, and decoupled access/execute architectures, primarily focus on improving memory access latency by loading data ahead of computation but still rely on the DRAM controllers to reorder memory requests and enhance memory bandwidth utilization. DRAM controllers have limited visibility to future …

Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization
Mingzhe Du, Luu Tuan Tuan, Yue Liu, Yuhao Qing, Dong Huang, Xinyi He, Qian Liu, Zejun Ma, See-kiong Ng
https://arxiv.org/abs/2505.23387

Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization
Large Language Models (LLMs) generate functionally correct solutions but often fall short in code efficiency, a critical bottleneck for real-world deployment. In this paper, we introduce a novel test-time iterative optimization framework to address this, employing a closed-loop system where LLMs iteratively refine code based on empirical performance feedback from an execution sandbox. We explore three training strategies: Supervised Fine-Tuning (SFT), Direct Preference Optimization (DPO), and G…

Synthesizing Performance Constraints for Evaluating and Improving Code Efficiency
Jun Yang, Cheng-Chi Wang, Bogdan Alexandru Stoica, Kexin Pei
https://arxiv.org/abs/2505.23471

Synthesizing Performance Constraints for Evaluating and Improving Code Efficiency
Large Language Models (LLMs) have been increasingly used to optimize code efficiency. Evaluating their effectiveness and further suggesting optimization opportunities often rely on high-quality tests to demonstrate the performance bottlenecks presented in the program. However, existing approaches rely on a limited set of hand-curated inputs or LLM-generated uninteresting length-stressing tests, failing to reveal more nuanced optimization opportunities. We present WEDGE, a framework for generati…