Tootfinder

From Empirical Evaluation to Context-Aware Enhancement: Repairing Regression Errors with LLMs
Anh Ho, Thanh Le-Cong, Bach Le, Christine Rizkallah
https://arxiv.org/abs/2506.13182 …

From Empirical Evaluation to Context-Aware Enhancement: Repairing Regression Errors with LLMs
[...] Since then, various APR approaches, especially those leveraging the power of large language models (LLMs), have been rapidly developed to fix general software bugs. Unfortunately, the effectiveness of these advanced techniques in the context of regression bugs remains largely unexplored. This gap motivates the need for an empirical study evaluating the effectiveness of modern APR techniques in fixing real-world regression bugs. In this work, we conduct an empirical study of APR techniqu…

Instruction Tuning and CoT Prompting for Contextual Medical QA with LLMs
Chenqian Le, Ziheng Gong, Chihang Wang, Haowei Ni, Panfeng Li, Xupeng Chen
https://arxiv.org/abs/2506.12182

Instruction Tuning and CoT Prompting for Contextual Medical QA with LLMs
Large language models (LLMs) have shown great potential in medical question answering (MedQA), yet adapting them to biomedical reasoning remains challenging due to domain-specific complexity and limited supervision. In this work, we study how prompt design and lightweight fine-tuning affect the performance of open-source LLMs on PubMedQA, a benchmark for multiple-choice biomedical questions. We focus on two widely used prompting strategies - standard instruction prompts and Chain-of-Thought (Co…

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection
Han Zhang, Akram Bin Sediq, Ali Afana, Melike Erol-Kantarci
https://arxiv.org/abs/2506.12074

Mobile Traffic Prediction using LLMs with Efficient In-context Demonstration Selection
Mobile traffic prediction is an important enabler for optimizing resource allocation and improving energy efficiency in mobile wireless networks. Building on the advanced contextual understanding and generative capabilities of large language models (LLMs), this work introduces a context-aware wireless traffic prediction framework powered by LLMs. To further enhance prediction accuracy, we leverage in-context learning (ICL) and develop a novel two-step demonstration selection strategy, optimizin…

Well, I'm heading to Resident Evil Outbreak stage 5
#residentevil #residenteviloutbreak #capcom

Trump Media and Technology Group files an S-1 with the US SEC to launch a spot Bitcoin and Ethereum ETF, allocating 75% to bitcoin and 25% to ether (Oliver Knight/CoinDesk)
https://www.coindesk.com/business/2025/06/16/d…

Donald Trump's Truth Social Files for Dual BTC and ETH ETF
The move follows registration for a standalone Truth Social bitcoin ETF earlier this month.

Artificial Intelligence and Civil Discourse: How LLMs Moderate Climate Change Conversations
Wenlu Fan, Wentao Xu
https://arxiv.org/abs/2506.12077 https://

Artificial Intelligence and Civil Discourse: How LLMs Moderate Climate Change Conversations
As large language models (LLMs) become increasingly integrated into online platforms and digital communication spaces, their potential to influence public discourse - particularly in contentious areas like climate change - requires systematic investigation. This study examines how LLMs naturally moderate climate change conversations through their distinct communicative behaviors. We conduct a comparative analysis of conversations between LLMs and human users on social media platforms, using fiv…

Well, Resident Evil Outbreak stage 3 there I go!!
#residentevil #residenteviloutbreak #capcom

Get on the Train or be Left on the Station: Using LLMs for Software Engineering Research
Bianca Trinkenreich, Fabio Calefato, Geir Hanssen, Kelly Blincoe, Marcos Kalinowski, Mauro Pezz\`e, Paolo Tell, Margaret-Anne Storey
https://arxiv.org/abs/2506.12691

Get on the Train or be Left on the Station: Using LLMs for Software Engineering Research
The adoption of Large Language Models (LLMs) is not only transforming software engineering (SE) practice but is also poised to fundamentally disrupt how research is conducted in the field. While perspectives on this transformation range from viewing LLMs as mere productivity tools to considering them revolutionary forces, we argue that the SE research community must proactively engage with and shape the integration of LLMs into research practices, emphasizing human agency in this transformation…

Ala misma mierda de siempre en #eurovision
Hasta el año que viene señores!.

Tired from #Gmail sigh...I need to have a change, a fresh air.
My #mailbox are fulled of junk, messed mails, etc.
I'm wondering what #mail provider I can choose.
Or as always I…