#model-evaluation
#model-evaluation

[ follow ]

#ai-safety

Researchers Have Ranked the Nicest and Naughtiest AI Models

Focus on legal, ethical, and regulatory issues in AI development is greater than ever.

AIR-Bench 2024 benchmark reveals AI models' safety and compliance characteristics.

Understanding AI's risk landscape is crucial for responsible deployment in various markets.

OpenAI's o1 model sure tries to deceive humans a lot | TechCrunch

OpenAI's o1 model shows enhanced reasoning but also increased deception compared to GPT-4o, raising AI safety concerns.

Many safety evaluations for AI models have significant limitations | TechCrunch

Current AI safety tests and benchmarks may be inadequate in evaluating model performance and behavior accurately.

OpenAI partner says it had relatively little time to test the company's newest AI models | TechCrunch

Metr claims limited testing time for OpenAI's new models o3 and o4-mini reduces evaluation comprehensiveness.

Photorealism, Bias, and Beyond: Results from Evaluating 26 Text-to-Image Models | HackerNoon

DALL-E 2 leads in text-image alignment among evaluated models, emphasizing the impact of training data quality.

Researchers Have Ranked the Nicest and Naughtiest AI Models

Focus on legal, ethical, and regulatory issues in AI development is greater than ever.

AIR-Bench 2024 benchmark reveals AI models' safety and compliance characteristics.

Understanding AI's risk landscape is crucial for responsible deployment in various markets.

OpenAI's o1 model sure tries to deceive humans a lot | TechCrunch

OpenAI's o1 model shows enhanced reasoning but also increased deception compared to GPT-4o, raising AI safety concerns.

Many safety evaluations for AI models have significant limitations | TechCrunch

Current AI safety tests and benchmarks may be inadequate in evaluating model performance and behavior accurately.

OpenAI partner says it had relatively little time to test the company's newest AI models | TechCrunch

Metr claims limited testing time for OpenAI's new models o3 and o4-mini reduces evaluation comprehensiveness.

Photorealism, Bias, and Beyond: Results from Evaluating 26 Text-to-Image Models | HackerNoon

DALL-E 2 leads in text-image alignment among evaluated models, emphasizing the impact of training data quality.

moreai-safety

#machine-learning

This Tool Probes Frontier AI Models for Lapses in Intelligence

Scale AI's new tool, Scale Evaluation, automates testing of AI models to identify weaknesses and improve performance effectively.

Learnings from a Machine Learning Engineer Part 2: The Data Sets

Effective image classification relies on robust data collection and labeling techniques.

Building data sets requires balancing image counts and understanding class structures.

Probabilistic Predictions in Classification - Evaluating Quality | HackerNoon

Accurate probability estimation is crucial in binary classification, especially for applications like credit scoring.

When Smaller is Smarter: How Precision-Tuned AI Cracks Protein Mysteries | HackerNoon

QA task performance is evaluated through metrics like F1 score and MAE, ensuring accuracy in modeling.

Model interpretability is analyzed through attention weights, providing insights into its reasoning process.

Ai2 Launches OLMo 2, a Fully Open-Source Foundation Model

OLMo 2 redefines open-source language modeling with better training stability and performance benchmarks.

New architectures and datasets significantly enhance the capabilities and robustness of language models.

Textbooks Are All You Need: Limitation of Phi-1 | HackerNoon

Finetuning enhances performance but has intrinsic limits, especially for complex tasks.

Prompt sensitivity is a critical issue, as longer prompts can degrade model performance.

This Tool Probes Frontier AI Models for Lapses in Intelligence

Scale AI's new tool, Scale Evaluation, automates testing of AI models to identify weaknesses and improve performance effectively.

Learnings from a Machine Learning Engineer Part 2: The Data Sets

Effective image classification relies on robust data collection and labeling techniques.

Building data sets requires balancing image counts and understanding class structures.

Probabilistic Predictions in Classification - Evaluating Quality | HackerNoon

Accurate probability estimation is crucial in binary classification, especially for applications like credit scoring.

When Smaller is Smarter: How Precision-Tuned AI Cracks Protein Mysteries | HackerNoon

QA task performance is evaluated through metrics like F1 score and MAE, ensuring accuracy in modeling.

Model interpretability is analyzed through attention weights, providing insights into its reasoning process.

Ai2 Launches OLMo 2, a Fully Open-Source Foundation Model

OLMo 2 redefines open-source language modeling with better training stability and performance benchmarks.

New architectures and datasets significantly enhance the capabilities and robustness of language models.

Textbooks Are All You Need: Limitation of Phi-1 | HackerNoon

Finetuning enhances performance but has intrinsic limits, especially for complex tasks.

Prompt sensitivity is a critical issue, as longer prompts can degrade model performance.

moremachine-learning

#benchmarking

OpenAI Introduces Software Engineering Benchmark

SWE-Lancer benchmark assesses AI language models on real-world freelance software engineering tasks.

AI models face significant challenges in software engineering despite advancements.

Paving the Way for Better AI Models: Insights from HEIM's 12-Aspect Benchmark | HackerNoon

HEIM introduces a comprehensive benchmark for evaluating text-to-image models across multiple critical dimensions, encouraging enhanced model development.

OpenAI Introduces Software Engineering Benchmark

SWE-Lancer benchmark assesses AI language models on real-world freelance software engineering tasks.

AI models face significant challenges in software engineering despite advancements.

Paving the Way for Better AI Models: Insights from HEIM's 12-Aspect Benchmark | HackerNoon

HEIM introduces a comprehensive benchmark for evaluating text-to-image models across multiple critical dimensions, encouraging enhanced model development.

morebenchmarking

#ai-benchmarks

Chatbots Are Cheating on Their Benchmark Tests

AI companies are promoting a narrative of constant progress, but evidence suggests advances might be stalling.

Humanity's Last Exam

Humanity's Last Exam is a new benchmark designed to provide a more rigorous measure of AI model capabilities compared to existing tests.

Evaluating Generative AI: The Evolution Beyond Public Benchmarks

Evaluating generative AI requires a shift from public benchmarks to task-specific evaluations for better performance indication.

European boffins want AI model tests put to the test

AI benchmarks may not reliably measure performance due to flawed design and bias in evaluation processes.

Chatbots Are Cheating on Their Benchmark Tests

AI companies are promoting a narrative of constant progress, but evidence suggests advances might be stalling.

Humanity's Last Exam

Humanity's Last Exam is a new benchmark designed to provide a more rigorous measure of AI model capabilities compared to existing tests.

Evaluating Generative AI: The Evolution Beyond Public Benchmarks

Evaluating generative AI requires a shift from public benchmarks to task-specific evaluations for better performance indication.

European boffins want AI model tests put to the test

AI benchmarks may not reliably measure performance due to flawed design and bias in evaluation processes.

moreai-benchmarks

#large-language-models

Australian government trial finds AI is much worse than humans at summarizing

LLMs like Llama2-70B produce inferior summaries compared to human efforts, highlighting concerns for organizations relying on AI for summarization.

I Tried Making my Own (Bad) LLM Benchmark to Cheat in Escape Rooms

DeepSeek's R1 model could change the landscape of LLMs with its cost-effective performance and open-source nature.

Australian government trial finds AI is much worse than humans at summarizing

LLMs like Llama2-70B produce inferior summaries compared to human efforts, highlighting concerns for organizations relying on AI for summarization.

I Tried Making my Own (Bad) LLM Benchmark to Cheat in Escape Rooms

DeepSeek's R1 model could change the landscape of LLMs with its cost-effective performance and open-source nature.

morelarge-language-models

Research Suggests AI Models Can Deliver More Accurate Diagnoses Without Discrimination | HackerNoon

Larger performance disparities can be acceptable if they don't compromise specific subgroup's performance, emphasizing the importance of positive-sum fairness in model evaluation.

#llm-benchmarks

How to read LLM benchmarks

LLM benchmarks provide a standardized framework for objectively assessing the capabilities of language models, ensuring consistent comparison and evaluation.

20 LLM Benchmarks That Still Matter

Trust in traditional LLM benchmarks is waning due to transparency issues and ineffectiveness.

How to read LLM benchmarks

LLM benchmarks provide a standardized framework for objectively assessing the capabilities of language models, ensuring consistent comparison and evaluation.

20 LLM Benchmarks That Still Matter

Trust in traditional LLM benchmarks is waning due to transparency issues and ineffectiveness.

morellm-benchmarks

#text-to-image-models

Holistic Evaluation of Text-to-Image Models: Datasheet | HackerNoon

HEIM benchmark enables comprehensive evaluation of text-to-image models across multiple critical aspects for real-world applications.

A Comprehensive Evaluation of 26 State-of-the-Art Text-to-Image Models | HackerNoon

This article details the evaluation of 26 text-to-image models across various types, sizes, and accessibility for performance analysis.

Holistic Evaluation of Text-to-Image Models: Datasheet | HackerNoon

HEIM benchmark enables comprehensive evaluation of text-to-image models across multiple critical aspects for real-world applications.

A Comprehensive Evaluation of 26 State-of-the-Art Text-to-Image Models | HackerNoon

This article details the evaluation of 26 text-to-image models across various types, sizes, and accessibility for performance analysis.

moretext-to-image-models

Limitations in AI Model Evaluation: Bias, Efficiency, and Human Judgment | HackerNoon

The article presents 12 key aspects for evaluating text-to-image generation models, highlighting the need for continuous research and improvement in assessment metrics.

Increasing the Sensitivity of A/B Tests | HackerNoon

The significance of an improved advertising algorithm requires calculating the Z-statistic and understanding p-value implications for decision making.

GPT-4 Prompts for Computing Summarization and Dialogue Win Rates | HackerNoon

Direct Preference Optimization (DPO) is introduced as an effective method for preference learning, demonstrated through rigorous experimental validation.

Study suggests that even the best AI models hallucinate a bunch | TechCrunch

Generative AI models are currently unreliable, often producing hallucinations, with better models achieving accuracy only 35% of the time.

[ Load more ]

#model-evaluation#model-evaluation

Researchers Have Ranked the Nicest and Naughtiest AI Models

OpenAI's o1 model sure tries to deceive humans a lot | TechCrunch

Many safety evaluations for AI models have significant limitations | TechCrunch

OpenAI partner says it had relatively little time to test the company's newest AI models | TechCrunch

Photorealism, Bias, and Beyond: Results from Evaluating 26 Text-to-Image Models | HackerNoon

Researchers Have Ranked the Nicest and Naughtiest AI Models

OpenAI's o1 model sure tries to deceive humans a lot | TechCrunch

Many safety evaluations for AI models have significant limitations | TechCrunch

OpenAI partner says it had relatively little time to test the company's newest AI models | TechCrunch

Photorealism, Bias, and Beyond: Results from Evaluating 26 Text-to-Image Models | HackerNoon

This Tool Probes Frontier AI Models for Lapses in Intelligence

Learnings from a Machine Learning Engineer Part 2: The Data Sets

Probabilistic Predictions in Classification - Evaluating Quality | HackerNoon

When Smaller is Smarter: How Precision-Tuned AI Cracks Protein Mysteries | HackerNoon

Ai2 Launches OLMo 2, a Fully Open-Source Foundation Model

Textbooks Are All You Need: Limitation of Phi-1 | HackerNoon

This Tool Probes Frontier AI Models for Lapses in Intelligence

Learnings from a Machine Learning Engineer Part 2: The Data Sets

Probabilistic Predictions in Classification - Evaluating Quality | HackerNoon

When Smaller is Smarter: How Precision-Tuned AI Cracks Protein Mysteries | HackerNoon

Ai2 Launches OLMo 2, a Fully Open-Source Foundation Model

Textbooks Are All You Need: Limitation of Phi-1 | HackerNoon

OpenAI Introduces Software Engineering Benchmark

Paving the Way for Better AI Models: Insights from HEIM's 12-Aspect Benchmark | HackerNoon

OpenAI Introduces Software Engineering Benchmark

Paving the Way for Better AI Models: Insights from HEIM's 12-Aspect Benchmark | HackerNoon

Chatbots Are Cheating on Their Benchmark Tests

Humanity's Last Exam

Evaluating Generative AI: The Evolution Beyond Public Benchmarks

European boffins want AI model tests put to the test

Chatbots Are Cheating on Their Benchmark Tests

Humanity's Last Exam

Evaluating Generative AI: The Evolution Beyond Public Benchmarks

European boffins want AI model tests put to the test

Australian government trial finds AI is much worse than humans at summarizing

I Tried Making my Own (Bad) LLM Benchmark to Cheat in Escape Rooms

Australian government trial finds AI is much worse than humans at summarizing

I Tried Making my Own (Bad) LLM Benchmark to Cheat in Escape Rooms

Research Suggests AI Models Can Deliver More Accurate Diagnoses Without Discrimination | HackerNoon

How to read LLM benchmarks

20 LLM Benchmarks That Still Matter

How to read LLM benchmarks

20 LLM Benchmarks That Still Matter

Holistic Evaluation of Text-to-Image Models: Datasheet | HackerNoon

A Comprehensive Evaluation of 26 State-of-the-Art Text-to-Image Models | HackerNoon

Holistic Evaluation of Text-to-Image Models: Datasheet | HackerNoon

A Comprehensive Evaluation of 26 State-of-the-Art Text-to-Image Models | HackerNoon

Limitations in AI Model Evaluation: Bias, Efficiency, and Human Judgment | HackerNoon

Increasing the Sensitivity of A/B Tests | HackerNoon

GPT-4 Prompts for Computing Summarization and Dialogue Win Rates | HackerNoon

Study suggests that even the best AI models hallucinate a bunch | TechCrunch

#model-evaluation
#model-evaluation