Category

Model Evaluation

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Showing 61-120 of 121 articles

Langfuse

Langfuse is an open-source LLM engineering platform that provides observability, tracing, prompt management, evaluation, and dataset tooling for applications...

AI CompaniesDeveloper Tools

LongBench v2

LongBench v2 is a benchmark for evaluating how well large language models understand and reason over long contexts. It consists of 503 challenging...

AI BenchmarksLarge Language Models

Loss Curve

See also: Machine learning terms, Loss function A loss curve is a plot that shows the value of a loss function over the course of training a machine learning...

Deep LearningMachine Learning

MATH

MATH is a benchmark of 12,500 competition mathematics problems used to evaluate the mathematical problem-solving ability of machine learning systems,...

AI BenchmarksReasoning Models

METEOR (metric)

METEOR (Metric for Evaluation of Translation with Explicit ORdering) is an automatic evaluation metric for machine translation and other text-generation tasks...

Machine LearningNatural Language Processing

MMLU-Redux

MMLU-Redux is a manually re-annotated, error-corrected subset of the Massive Multitask Language Understanding (MMLU) benchmark, intended to serve as a cleaner...

AI Benchmarks

MRCR

MRCR (Multi-Round Co-reference Resolution) is a synthetic long-context evaluation that tests whether a large language model can locate and disambiguate among...

AI BenchmarksLarge Language Models

Mean Absolute Error (MAE)

Mean Absolute Error (MAE) is a regression accuracy metric and loss function that measures the average absolute difference between predicted values and actual...

Machine LearningStatistics

Mean Squared Error (MSE)

See also: Machine learning terms Mean Squared Error (MSE), also called mean squared deviation (MSD), is the average of the squared differences between...

Machine LearningStatistics

Model Capacity

Model capacity is the size and richness of the family of functions a machine learning model can represent and learn, which determines how complex a pattern the...

Machine Learning

MuSR

MuSR (Multistep Soft Reasoning) is a benchmark for evaluating multistep reasoning in large language models, built around long free-text narratives such as...

AI BenchmarksReasoning Models

Multi-SWE-bench

Multi-SWE-bench is a multilingual benchmark for evaluating the ability of large language model based coding systems to resolve real-world software issues...

AI BenchmarksAI Code Generation

NIST ARIA

NIST ARIA (Assessing Risks and Impacts of AI) is a testing, evaluation, validation, and verification (TEVV) program operated by the United States National...

AI Policy & RegulationAI Safety

NoLiMa

NoLiMa, short for "No Literal Matching," is a long-context benchmark for large language models that measures how well a model can find and use a single...

AI BenchmarksLarge Language Models

OlympiadBench

OlympiadBench is an AI benchmark of 8,476 Olympiad-level mathematics and physics problems, designed to test the advanced scientific reasoning of large language...

AI Benchmarks

Omni-MATH

Omni-MATH is an AI benchmark of Olympiad-level competition mathematics, introduced in October 2024 to measure the mathematical reasoning ability of large...

AI Benchmarks

Out-of-bag evaluation (OOB evaluation)

See also: Machine learning terms, Bagging, Random forest, Cross-validation Out-of-bag (OOB) evaluation, sometimes called out-of-bag estimation or OOB error, is...

Machine Learning

Overfitting

Overfitting is when a machine learning model fits its training set so closely that it learns the noise and quirks of those specific examples instead of the...

Deep LearningMachine Learning

PR AUC

See also: precision, recall, ROC curve, AUC, F1 score, confusion matrix, precision-recall curve PR AUC (Precision-Recall Area Under the Curve), also referred...

Machine Learning

Pass@k

Pass@k is the standard metric for evaluating code generation models: it measures the probability that at least one of k generated candidate solutions passes...

AI BenchmarksAI Code Generation

Patronus AI

Patronus AI is an automated LLM evaluation, observability, and guardrails platform founded in 2023[1] and headquartered in San Francisco. The company builds...

AI CompaniesAI Safety

Precision

Precision is a classification metric defined as the fraction of positive predictions that are correct: Precision = TP / (TP + FP), where TP is the number of...

Machine Learning

Precision-Recall Curve

A precision-recall curve (PR curve) is a graph that plots precision on the y-axis against recall on the x-axis at every possible classification threshold for a...

Machine Learning

Prediction Bias

Prediction bias is the difference between the average of a machine learning model's predictions and the average of the ground-truth labels in a dataset. Stated...

Machine Learning

Process reward model (PRM)

A process reward model (PRM), also called a process-supervised reward model or step-level verifier, is a learned scoring model that evaluates the correctness...

AI SafetyMachine Learning

ProcessBench

ProcessBench is a benchmark for step-level verification of mathematical reasoning, built by the Qwen Team at Alibaba and released in December 2024. [1] It...

AI BenchmarksReasoning Models

PutnamBench

PutnamBench is a benchmark for evaluating automated theorem proving systems, especially neural and large-language-model-based provers, on competition...

AI Benchmarks

RE-Bench

RE-Bench (short for Research Engineering Benchmark) is a benchmark for evaluating the frontier AI research-and-development capabilities of large language model...

AI Benchmarks

ROC (Receiver Operating Characteristic) Curve

A Receiver Operating Characteristic (ROC) curve is a graph that measures how well a binary classification system separates two classes by plotting its true...

Machine Learning

ROUGE

ROUGE (Recall-Oriented Understudy for Gisting Evaluation) is a set of automatic metrics that score the quality of a machine-generated text summary by counting...

Machine LearningNatural Language Processing

Recall (metric)

Recall is a classification and retrieval metric that measures the proportion of actual positive instances a model correctly identifies, defined as TP / (TP +...

Machine Learning

RewardBench

RewardBench is a benchmark and public leaderboard for evaluating reward models, the scoring functions that sit at the center of reinforcement learning from...

AI BenchmarksReinforcement Learning

Root Mean Squared Error (RMSE)

Root Mean Squared Error (RMSE), also known as root mean square deviation (RMSD), is a regression evaluation metric equal to the square root of the average of...

Machine LearningStatistics

SWE-bench Verified

Software Engineering Benchmark, Verified subset Abbreviation A 500-task, human-validated subset of SWE-bench for evaluating AI agents on real-world GitHub...

AI BenchmarksAI Code Generation

Sabotage evaluations

Sabotage evaluations are a set of tests, introduced by Anthropic in October 2024, that try to measure whether a frontier language model is capable of covertly...

AI SafetyAnthropic

Sandbagging (artificial intelligence)

Sandbagging, in the context of AI safety, refers to the strategic and intentional underperformance of an AI system on a capability evaluation or specific task,...

AI Safety

Scale SEAL Leaderboards

The SEAL Leaderboards are a set of expert-curated, contamination-resistant evaluation leaderboards for frontier large language models, produced by the Safety,...

AI Companies

ScienceAgentBench

ScienceAgentBench is an AI benchmark for evaluating whether language model agents can perform real, data-driven scientific analysis by writing and executing...

AI Benchmarks

Self-Taught Evaluator

Self-Taught Evaluator is a method for training a strong LLM-as-a-judge without any human preference annotations, using synthetic training data and an iterative...

Meta AITraining & Optimization

SimpleQA Verified

SimpleQA Verified is a short-form factuality benchmark released by Google DeepMind and Google Research in September 2025 that measures the parametric knowledge...

AI BenchmarksGoogle DeepMind

Spider 2.0

Spider 2.0 is a benchmark for evaluating large language models on real-world enterprise text-to-SQL workflows. Introduced by Fangyu Lei and colleagues in the...

AI BenchmarksAI Code Generation

Splitter

A splitter is a term used in two distinct senses in machine learning. The first and most common sense is a utility that partitions a dataset into subsets such...

Machine Learning

Stanford HAI AI Index Report

The AI Index Report is an annual, independent, data-driven publication that tracks, distills, and visualizes trends in artificial intelligence across research...

AI Companies

State of AI Report

The State of AI Report is a free, annual review of progress in artificial intelligence, published every year since 2018. It is compiled by the investor Nathan...

AI Companies

StrongREJECT

StrongREJECT is a benchmark and automated evaluator for measuring how well jailbreaking attacks actually work against large language models. It was introduced...

AI BenchmarksAI Safety

SuperGPQA

SuperGPQA is a large graduate-level knowledge and reasoning benchmark for evaluating large language models across 285 academic disciplines. It contains 26,529...

AI Benchmarks

Task-completion time horizon (METR)

The task-completion time horizon is a metric for AI capability proposed by METR that expresses a model's ability in units of human time: it is the length of...

AI BenchmarksAI Safety

Terminal-Bench

Terminal-Bench is an open benchmark for evaluating AI agents on complex, real-world tasks performed through command-line terminal interfaces. Developed as a...

AI AgentsAI Benchmarks

Test Set

A test set is a portion of data held back from model development and used only once, after all training and tuning is complete, to give an unbiased estimate of...

Machine Learning

The Leaderboard Illusion

The Leaderboard Illusion is a 2025 research paper, led by Cohere and Cohere Labs with academic collaborators, that argues the most influential public ranking...

AI Companies

True negative

A true negative (TN) is a case that a binary classification model correctly predicts as belonging to the negative class: the true label is negative and the...

Machine LearningStatistics

True positive

A true positive (TP) is a prediction that is correctly positive: the model predicts the positive class and the true label is also positive.[^1][^3][^17] It is...

Machine LearningStatistics

True positive rate (TPR)

The true positive rate (TPR) is the proportion of actual positive cases that a classifier correctly identifies as positive, computed as TPR = TP / (TP + FN),...

Machine Learning

UK AI Security Institute

The UK AI Security Institute (AISI) is a research organization within the United Kingdom's Department for Science, Innovation and Technology (DSIT) that...

AI Policy & RegulationAI Safety

Validation Set

A validation set (also called a development set or dev set) is a subset of labeled data that is held out from the training set and used to evaluate a model's...

Machine Learning

Vals AI

Vals AI is an independent, third-party AI model evaluation company based in San Francisco that builds and publishes domain-specific benchmarks measuring how...

AI Companies

WebArena

WebArena is a realistic, self-hosted web environment and benchmark designed for developing and evaluating autonomous AI agents that perform tasks on the web....

AI AgentsAI Benchmarks

WebVoyager

WebVoyager is an end-to-end web agent and its companion benchmark, introduced by Hongliang He and seven coauthors in a paper accepted to ACL 2024 [1][2]. It is...

AI AgentsAI Benchmarks

WildBench

WildBench is an automated evaluation framework for large language models (LLMs) introduced by the Allen Institute for AI (AI2) in 2024. It evaluates models on...

AI Benchmarks

Word error rate

Word error rate (WER) is the standard metric for measuring the accuracy of an automatic speech recognition (ASR) system, expressed as the fraction of words the...

Machine LearningNatural Language Processing