LLMs successfully translate quantum programs between SDKs with zero-shot Pass@1 reaching 72.33%. Study reveals missing source artifacts and SDK compilation errors as primary barriers, while one-shot prompting significantly improves translation effectiveness.
#QuantumSoftware #LLMCode #Research
#QuantumSoftware #LLMCode #Research
Large Language Models for Quantum Code Translation: An Exploratory Study
iq.fp2.dev
October 27, 2026 at 8:22 AM
LLMs successfully translate quantum programs between SDKs with zero-shot Pass@1 reaching 72.33%. Study reveals missing source artifacts and SDK compilation errors as primary barriers, while one-shot prompting significantly improves translation effectiveness.
#QuantumSoftware #LLMCode #Research
#QuantumSoftware #LLMCode #Research
LLMs übersetzen erfolgreich Quantenprogramme zwischen SDKs mit Zero-Shot Pass@1 von 72,33%. Die Studie zeigt fehlende Quellartefakte und SDK-Compilerfehler als primäre Hindernisse auf, während One-Shot-Prompting die Übersetzungseffektivität erheblich verbessert.
#Quantensoftware #LLMCode #Forschung
#Quantensoftware #LLMCode #Forschung
Große Sprachmodelle für die Quantencode-Übersetzung: Eine explorative Studie
arxiv.org
October 27, 2026 at 8:22 AM
LLMs übersetzen erfolgreich Quantenprogramme zwischen SDKs mit Zero-Shot Pass@1 von 72,33%. Die Studie zeigt fehlende Quellartefakte und SDK-Compilerfehler als primäre Hindernisse auf, während One-Shot-Prompting die Übersetzungseffektivität erheblich verbessert.
#Quantensoftware #LLMCode #Forschung
#Quantensoftware #LLMCode #Forschung
Introducing LLMCode Lab
AI is changing how we work every day. I want to take this opportunity to share some of what I am working on. LLMCode Lab is a free testing lab for large language models. You bring your own API key, pick up to five models from HuggingFace, OpenAI, Anthropic, and Google, send…
AI is changing how we work every day. I want to take this opportunity to share some of what I am working on. LLMCode Lab is a free testing lab for large language models. You bring your own API key, pick up to five models from HuggingFace, OpenAI, Anthropic, and Google, send…
Introducing LLMCode Lab
AI is changing how we work every day. I want to take this opportunity to share some of what I am working on. LLMCode Lab is a free testing lab for large language models. You bring your own API key, pick up to five models from HuggingFace, OpenAI, Anthropic, and Google, send them all the same prompt, and read the answers side by side, with what each one costs.
mstechdiva.com
October 21, 2026 at 5:52 AM
Introducing LLMCode Lab
AI is changing how we work every day. I want to take this opportunity to share some of what I am working on. LLMCode Lab is a free testing lab for large language models. You bring your own API key, pick up to five models from HuggingFace, OpenAI, Anthropic, and Google, send…
AI is changing how we work every day. I want to take this opportunity to share some of what I am working on. LLMCode Lab is a free testing lab for large language models. You bring your own API key, pick up to five models from HuggingFace, OpenAI, Anthropic, and Google, send…
Built LLMCode.ai - a smarter way to work with AI models.
Compare up to 5 models side-by-side (OpenAI, Anthropic, Google, Hugging Face) or use Fusion Lab to synthesize responses from multiple models - comparable to Perplexity MAX, but you use your own API keys.
Free tool.
Compare up to 5 models side-by-side (OpenAI, Anthropic, Google, Hugging Face) or use Fusion Lab to synthesize responses from multiple models - comparable to Perplexity MAX, but you use your own API keys.
Free tool.
LLMCode Lab - Open Source LLM Comparison Tool
Compare LLM responses side-by-side. Test Llama, Mistral, GPT-4, Claude and more. Free, open source, no registration required. Built by XYZagents.ai
LLMCode.ai
February 11, 2026 at 12:45 AM
Built LLMCode.ai - a smarter way to work with AI models.
Compare up to 5 models side-by-side (OpenAI, Anthropic, Google, Hugging Face) or use Fusion Lab to synthesize responses from multiple models - comparable to Perplexity MAX, but you use your own API keys.
Free tool.
Compare up to 5 models side-by-side (OpenAI, Anthropic, Google, Hugging Face) or use Fusion Lab to synthesize responses from multiple models - comparable to Perplexity MAX, but you use your own API keys.
Free tool.
Testing multiple models at the same time paid and free. No session data saved.
1 prompt
5 responses
Try it with hugging face
llmcode.ai
1 prompt
5 responses
Try it with hugging face
llmcode.ai
LLMCode Lab - Open Source LLM Comparison Tool
Compare LLM responses side-by-side. Test Llama, Mistral, GPT-4, Claude and more. Free, open source, no registration required. Built by XYZagents.ai
llmcode.ai
December 20, 2025 at 6:32 AM
Testing multiple models at the same time paid and free. No session data saved.
1 prompt
5 responses
Try it with hugging face
llmcode.ai
1 prompt
5 responses
Try it with hugging face
llmcode.ai
AP2O, a new training method for LLM code generation, improves pass@k scores by up to 3% across models from 0.5 B to 34 B parameters. The research was posted on 1 Oct 2025. https://getnews.me/ap2o-improves-llm-code-generation-by-correcting-errors-type-by-type/ #ap2o #llmcode #passatk
October 6, 2025 at 5:05 AM
AP2O, a new training method for LLM code generation, improves pass@k scores by up to 3% across models from 0.5 B to 34 B parameters. The research was posted on 1 Oct 2025. https://getnews.me/ap2o-improves-llm-code-generation-by-correcting-errors-type-by-type/ #ap2o #llmcode #passatk
I would like to see the C file because I'm interested in this kind of bizarre OS-level fuckery.
LLMcode though so I doubt it'll have comprehensible docs
LLMcode though so I doubt it'll have comprehensible docs
May 1, 2026 at 3:42 AM
I would like to see the C file because I'm interested in this kind of bizarre OS-level fuckery.
LLMcode though so I doubt it'll have comprehensible docs
LLMcode though so I doubt it'll have comprehensible docs
research examines the trustworthiness of LLM-driven design insights, using qualitative coding as a case study to explore the interpretive processes central to RfD. We introduce LLMCode, an open-source tool integrating two metrics, namely Intersection [2/5 of https://arxiv.org/abs/2504.16671v1]
April 24, 2025 at 5:59 AM
research examines the trustworthiness of LLM-driven design insights, using qualitative coding as a case study to explore the interpretive processes central to RfD. We introduce LLMCode, an open-source tool integrating two metrics, namely Intersection [2/5 of https://arxiv.org/abs/2504.16671v1]
Joel Oksanen, Andr\'es Lucero, Perttu H\"am\"al\"ainen: LLMCode: Evaluating and Enhancing Researcher-AI Alignment in Qualitative Analysis https://arxiv.org/abs/2504.16671 https://arxiv.org/pdf/2504.16671 https://arxiv.org/html/2504.16671
April 24, 2025 at 5:59 AM
Joel Oksanen, Andr\'es Lucero, Perttu H\"am\"al\"ainen: LLMCode: Evaluating and Enhancing Researcher-AI Alignment in Qualitative Analysis https://arxiv.org/abs/2504.16671 https://arxiv.org/pdf/2504.16671 https://arxiv.org/html/2504.16671
Despite utility, skepticism remains regarding LLM-generated code. Concerns about long-term maintainability and whether LLMs can fully replace human developers persist. It's not just about generating code, but sustaining it. #LLMCode 3/6
December 22, 2025 at 2:00 AM
Despite utility, skepticism remains regarding LLM-generated code. Concerns about long-term maintainability and whether LLMs can fully replace human developers persist. It's not just about generating code, but sustaining it. #LLMCode 3/6
HN discussion explores LLMs for codebases: review, refactoring, quality improvement. Key insights: careful prompting, human oversight, and a clear definition of "high-quality" code are essential for practical AI application in software development. #LLMCode 1/5
December 12, 2025 at 8:00 AM
HN discussion explores LLMs for codebases: review, refactoring, quality improvement. Key insights: careful prompting, human oversight, and a clear definition of "high-quality" code are essential for practical AI application in software development. #LLMCode 1/5
HN discussed "comprehension debt" in LLM-generated code. While LLMs speed up production, they risk declining understanding and maintainability. The core issue: a lack of a coherent mental model for AI-produced code. This impacts software quality. #LLMCode 1/5
October 1, 2025 at 10:00 AM
HN discussed "comprehension debt" in LLM-generated code. While LLMs speed up production, they risk declining understanding and maintainability. The core issue: a lack of a coherent mental model for AI-produced code. This impacts software quality. #LLMCode 1/5
A key insight: LLMs often produce subtly buggy code that's hard to spot. This emphasizes the need for rigorous testing methods like fuzzing or property testing to validate LLM outputs, especially for critical applications. #LLMCode 3/6
June 19, 2025 at 9:00 PM
A key insight: LLMs often produce subtly buggy code that's hard to spot. This emphasizes the need for rigorous testing methods like fuzzing or property testing to validate LLM outputs, especially for critical applications. #LLMCode 3/6
OK I asked the gemini 1206 for a pattern I'm more familiar with and I definitely see the slop but at the same time it was instant. First time using one of these for code so I'm taking that into account too.
#geminiAI #promptEngineer
#LLMcode #developers #aiStudio #generativeCode #LLM
#geminiAI #promptEngineer
#LLMcode #developers #aiStudio #generativeCode #LLM
December 21, 2024 at 7:25 PM
OK I asked the gemini 1206 for a pattern I'm more familiar with and I definitely see the slop but at the same time it was instant. First time using one of these for code so I'm taking that into account too.
#geminiAI #promptEngineer
#LLMcode #developers #aiStudio #generativeCode #LLM
#geminiAI #promptEngineer
#LLMcode #developers #aiStudio #generativeCode #LLM