Automatic Detection of LLM-generated Code: A Case Study of Claude 3 Haiku
The results indicate that Claude 3 tends to generate longer functions, but shorter classes than humans, and this characteristic can be used to detect Claude 3-generated code with ML models with 82% and 66% accuracies for function-level and class-level snippets, respectively.
The results indicate that Claude 3 tends to generate longer functions, but shorter classes than humans, and this characteristic can be used to detect Claude 3-generated code with ML models with 82% and 66% accuracies for function-level and class-level snippets, respectively.
Fixing Code Generation Errors for Large Language Models
The authors conducted ten rounds of tests on 14 LLMs using the HumanEval dataset. Through manual analysis of the test results, they found that these LLMs achieved an average of 84.07% of their reported performance.
They also investigated the relationship between Pass@1 results, model inference time, and model parameter size. The analysis revealed a positive correlation between Pass@1 results and model parameter size, while no significant correlation was observed between inference time and parameter size.
Subsequently, the authors performed an in-depth analysis of errors in the test results, extracting and categorizing 12,837 errors into 14 types. Through the analysis, they identified 19 specific causes leading to these errors.
The proposed a fixing method can fix three types of errors, improving the performance of 14 LLMs on HumanEval and MBPP datasets with average increases of 9.5% and 5.4%, respectively.
The authors conducted ten rounds of tests on 14 LLMs using the HumanEval dataset. Through manual analysis of the test results, they found that these LLMs achieved an average of 84.07% of their reported performance.
They also investigated the relationship between Pass@1 results, model inference time, and model parameter size. The analysis revealed a positive correlation between Pass@1 results and model parameter size, while no significant correlation was observed between inference time and parameter size.
Subsequently, the authors performed an in-depth analysis of errors in the test results, extracting and categorizing 12,837 errors into 14 types. Through the analysis, they identified 19 specific causes leading to these errors.
The proposed a fixing method can fix three types of errors, improving the performance of 14 LLMs on HumanEval and MBPP datasets with average increases of 9.5% and 5.4%, respectively.
Chat template viewer
Different LLMs expect very different input formats. HuggingFace added chat templates, they are part of the tokenizer. Chat templates pecify how to convert conversations, represented as lists of messages, into a single string in the format that the model expects. To learn more about chat_template in the different models, visit this.
Different LLMs expect very different input formats. HuggingFace added chat templates, they are part of the tokenizer. Chat templates pecify how to convert conversations, represented as lists of messages, into a single string in the format that the model expects. To learn more about chat_template in the different models, visit this.
The 2024 Nobel Prize in Physics has been awarded to John J. Hopfield and Geoffrey E. Hinton
“for foundational discoveries and inventions that enable machine learning with artificial neural networks.”
“for foundational discoveries and inventions that enable machine learning with artificial neural networks.”
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LLMs Know More Than They Show: On the Intrinsic Representation of LLM Hallucinations
The authors analyzed the errors of LLMs by examining their internal representations. They discover that information related to truthfulness is localized within the exact answer tokens. From a practical perspective, this finding enhances error detection methods applicable to production-level LLMs.
The code is coming soon
The authors analyzed the errors of LLMs by examining their internal representations. They discover that information related to truthfulness is localized within the exact answer tokens. From a practical perspective, this finding enhances error detection methods applicable to production-level LLMs.
The code is coming soon
ml4se
The 2024 Nobel Prize in Physics has been awarded to John J. Hopfield and Geoffrey E. Hinton “for foundational discoveries and inventions that enable machine learning with artificial neural networks.”
NobelPrize.org
Nobel Prize in Chemistry 2024
The Nobel Prize in Chemistry 2024 was divided, one half awarded to David Baker "for computational protein design", the other half jointly to Demis Hassabis and John Jumper "for protein structure prediction"
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State of AI Report 2024
Key takeways from the 2024 Report include:
- Frontier lab performance begins to converge and proprietary models lose their edge
- Planning and reasoning take priority in LLM research
- Foundation models demonstrate their ability to break out of language
- US sanctions have limited effects on Chinese labs’ ability to produce capable models
- The enterprise value of AI companies has hit $9T
- A handful of AI companies begin to generate serious revenue
- The pseudo-acquisition emerges as an off-ramp for AI companies
- The existential risk discourse has cooled off
PDF
Key takeways from the 2024 Report include:
- Frontier lab performance begins to converge and proprietary models lose their edge
- Planning and reasoning take priority in LLM research
- Foundation models demonstrate their ability to break out of language
- US sanctions have limited effects on Chinese labs’ ability to produce capable models
- The enterprise value of AI companies has hit $9T
- A handful of AI companies begin to generate serious revenue
- The pseudo-acquisition emerges as an off-ramp for AI companies
- The existential risk discourse has cooled off
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2^136279841-1 is the New Largest Known Prime Number
The Great Internet Mersenne Prime Search has discovered a new Mersenne prime number, $2^136279841-1$. At 41,024,320 digits, it eclipses by more than 16 million digits the previous largest known prime number found by GIMPS nearly 6 years ago.
The Great Internet Mersenne Prime Search has discovered a new Mersenne prime number, $2^136279841-1$. At 41,024,320 digits, it eclipses by more than 16 million digits the previous largest known prime number found by GIMPS nearly 6 years ago.
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