Tootfinder

Input Reduction Enhanced LLM-based Program Repair
Boyang Yang, Luyao Ren, Xin Yin, Jiadong Ren, Haoye Tian, Shunfu Jin
https://arxiv.org/abs/2507.15251 htt…

Input Reduction Enhanced LLM-based Program Repair
Large Language Models (LLMs) have shown great potential in Automated Program Repair (APR). Test inputs, being crucial for reasoning the root cause of failures, are always included in the prompt for LLM-based APR. Unfortunately, LLMs struggle to retain key information in long prompts. When the test inputs are extensive in the prompt, this may trigger the "lost-in-the-middle" issue, compromising repair performance. To address this, we propose ReduceFix, an LLM-based APR approach with a built-in c…

Seeing is Fixing: Cross-Modal Reasoning with Multimodal LLMs for Visual Software Issue Fixing
Kai Huang, Jian Zhang, Xiaofei Xie, Chunyang Chen
https://arxiv.org/abs/2506.16136

Seeing is Fixing: Cross-Modal Reasoning with Multimodal LLMs for Visual Software Issue Fixing
Large language model-(LLM) based automated program repair (APR) techniques have shown promising results in resolving real-world GitHub issue tasks. Existing APR systems are primarily evaluated in unimodal settings (e.g., SWE-bench). However, these autonomous systems struggle to resolve multimodal problem scenarios (e.g., SWE-bench M) due to limitations in interpreting and leveraging visual information. In multimodal scenarios, LLMs need to rely on visual information in the graphical user interf…

Shareholders in his companies feared that Musk was closing the golden money faucet for them in the White House.
https://www.pbs.org/newshour/politics/elon

Elon Musk backs off from feud with Trump, saying he regrets social media posts that 'went too far'
Musk earlier deleted a post in which he claimed without evidence that the government was concealing information about the president's association with infamous pedophile Jeffrey Epstein. Trump has said he has no desire to repair their relationship.

Series C, Episode 13 - Terminal
VILA: Then why the massive power drain?
ZEN: Auto-repair circuits are working at maximum capacity. Damage exceeds rectification capability.
DAYNA: Damage? What damage?
ZEN: That information is not available.
https://blake.torpidity.net/m/313/250

Identifying Helpful Context for LLM-based Vulnerability Repair: A Preliminary Study
G\'abor Antal, Bence Bogenf\"urst, Rudolf Ferenc, P\'eter Heged\H{u}s
https://arxiv.org/abs/2506.11561

Identifying Helpful Context for LLM-based Vulnerability Repair: A Preliminary Study
Recent advancements in large language models (LLMs) have shown promise for automated vulnerability detection and repair in software systems. This paper investigates the performance of GPT-4o in repairing Java vulnerabilities from a widely used dataset (Vul4J), exploring how different contextual information affects automated vulnerability repair (AVR) capabilities. We compare the latest GPT-4o's performance against previous results with GPT-4 using identical prompts. We evaluated nine additional…

How Students (Really) Use ChatGPT: Uncovering Experiences Among Undergraduate Students
Tawfiq Ammari, Meilun Chen, S M Mehedi Zaman, Kiran Garimella
https://arxiv.org/abs/2505.24126

How Students (Really) Use ChatGPT: Uncovering Experiences Among Undergraduate Students
This study investigates how undergraduate students engage with ChatGPT in self directed learning contexts. Analyzing naturalistic interaction logs, we identify five dominant use categories of ChatGPT information seeking, content generation, language refinement, meta cognitive engagement, and conversational repair. Behavioral modeling reveals that structured, goal driven tasks like coding, multiple choice solving, and job application writing are strong predictors of continued use. Drawing on Sel…