Best AI tools for< Improve Test Scores >

PrepGenius.ai is an AI-driven test preparation platform designed to revolutionize the way students prepare for AP courses, college admission tests, and more. The platform offers personalized study plans, real-time feedback, interactive learning tools, and comprehensive resources to help students understand their strengths and weaknesses. With PrepGenius.ai, students can study smarter, receive tailored feedback, and track their progress to improve their test scores effectively.

Face Symmetry Test is an AI-powered tool that analyzes the symmetry of facial features by detecting key landmarks such as eyes, nose, mouth, and chin. Users can upload a photo to receive a personalized symmetry score, providing insights into the balance and proportion of their facial features. The tool uses advanced AI algorithms to ensure accurate results and offers guidelines for improving the accuracy of the analysis. Face Symmetry Test is free to use and prioritizes user privacy and security by securely processing uploaded photos without storing or sharing data with third parties.

VisualEyes is a user experience (UX) optimization tool that uses attention heatmaps and clarity scores to help businesses improve the effectiveness of their digital products. It provides insights into how users interact with websites and applications, allowing businesses to identify areas for improvement and make data-driven decisions about their designs. VisualEyes is part of Neurons, a leading neuroscience company that specializes in providing AI-powered solutions for businesses.

VisualHUB is an AI-powered design analysis tool that provides instant insights on UI, UX, readability, and more. It offers features like A/B Testing, UI Analysis, UX Analysis, Readability Analysis, Margin and Hierarchy Analysis, and Competition Analysis. Users can upload product images to receive detailed reports with actionable insights and scores. Trusted by founders and designers, VisualHUB helps optimize design variations and identify areas for improvement in products.

CogniCircuit AI is an AI-powered TOEFL preparation application designed to help students improve their English skills and achieve high scores in the TOEFL exam. The app offers comprehensive practice tests, personalized feedback, and realistic exam simulations to enhance students' reading, speaking, writing, and listening abilities. With over 90,000 students on the platform and a success rate of 98%, CogniCircuit AI is a trusted tool for TOEFL test preparation.

The SAT Reading & Writing Question Generator is an AI-powered tool designed to help students practice for the SAT exam. It generates a wide variety of reading and writing questions to improve students' skills and boost their confidence. With its smart algorithms, the tool provides personalized practice questions tailored to each student's needs, making exam preparation more effective and efficient. The tool is user-friendly and accessible, offering a seamless experience for students to enhance their test-taking abilities.

Unspam is an email spam checker and deliverability test tool that helps businesses ensure their emails land in the inbox, not spam. It offers a range of features including email spam checking, deliverability testing, email preview, AI eye-tracking heatmap, SPF, DKIM, DMARC, and more. Unspam's mission is to help businesses improve their email deliverability and engagement, and its tools and insights are designed to help users optimize their email campaigns for maximum impact.

LingoLeap is an AI-powered tool and platform designed for TOEFL and IELTS preparation. It leverages artificial intelligence to provide personalized feedback and guidance tailored to individual learning needs. With features such as instant feedback, practice tests, high-score answer generation, and vocabulary boost, LingoLeap aims to help users improve their English skills efficiently. The tool offers subscription plans with varying credits for speaking and writing evaluations, along with a free trial option. LingoLeap's innovative approach enhances language learning by analyzing users' language expression, grammar accuracy, and vocabulary application, similar to the official TOEFL test standards.

APEUni is an AI-powered platform designed to help users practice for the Pearson Test of English (PTE) exam. It offers various AI scoring features for different sections of the PTE exam, such as Speaking, Writing, Reading, and Listening. Users can access practice materials, study guides, and receive detailed score reports to improve their performance. APEUni aims to provide a comprehensive and efficient way for PTE test takers to prepare for the exam.

testRigor is an AI-based test automation tool that allows users to create and execute test cases using plain English instructions. It leverages generative AI in software testing to automate test creation and maintenance, offering features such as no code/codeless testing, web, mobile, and desktop testing, Salesforce automation, and accessibility testing. With testRigor, users can achieve test coverage faster and with minimal maintenance, enabling organizations to reallocate QA engineers to build API tests and increase test coverage significantly. The tool is designed to simplify test automation, reduce QA headaches, and improve productivity by streamlining the testing process.

Testmint.ai is an online mock test platform designed to help users prepare for competitive exams. It offers a wide range of practice tests and study materials to enhance exam readiness. The platform is user-friendly and provides a simulated exam environment to improve test-taking skills. Testmint.ai aims to assist students and professionals in achieving their academic and career goals by offering a comprehensive and effective exam preparation solution.

MAIHEM is an AI-powered quality assurance platform that helps businesses test and improve the performance and safety of their AI applications. It automates the testing process, generates realistic test cases, and provides comprehensive analytics to help businesses identify and fix potential issues. MAIHEM is used by a variety of businesses, including those in the customer support, healthcare, education, and sales industries.

SmartLifeSkills.AI is an AI-powered platform that offers a wide range of tools and resources to help users test and improve their skills in various topics. It provides a transformative learning experience by leveraging Artificial Intelligence to personalize learning paths and enhance user engagement. With features like interactive AI chat, custom quiz maker, complex text explainer, and more, SmartLifeSkills.AI aims to unlock users' potential and empower them to achieve their goals through continuous learning and skill development.

The AI-powered Cambridge English Test platform offers exercises for English levels B1, B2, C1, and C2. Users can select exercise types such as Reading and Use of English, including activities like Open Cloze, Multiple Choice, Word Formation, and more. The AI, developed by Shining Apps in partnership with Use of English PRO, provides a unique learning experience by generating exercises from a database of over 5000 official exams. It uses advanced Natural Language Processing (NLP) to understand context, tweak exercises, and offer detailed feedback for effective learning.

AI Generated Test Cases is an innovative tool that leverages artificial intelligence to automatically generate test cases for software applications. By utilizing advanced algorithms and machine learning techniques, this tool can efficiently create a comprehensive set of test scenarios to ensure the quality and reliability of software products. With AI Generated Test Cases, software development teams can save time and effort in the testing phase, leading to faster release cycles and improved overall productivity.

SmallTalk2Me is an AI-powered simulator designed to help users improve their spoken English. It offers a range of features, including mock job interviews, IELTS speaking test simulations, and daily stories and courses. The platform uses AI to provide users with instant feedback on their performance, helping them to identify areas for improvement and track their progress over time.

ELSA Speech Analyzer is an AI-powered conversational English fluency coach that provides instant, personalized feedback on speech. It helps users improve pronunciation, intonation, grammar, and fluency through real-time analysis. The tool is designed for individuals, professionals, students, and organizations to enhance English speaking skills and communication abilities.

Symflower is an AI-powered unit test generator for Java applications. It helps developers write and maintain test code with ease, saving time and improving code quality. Symflower works with JUnit 4 and JUnit 5 for Java, Spring, and Spring Boot applications.

ILoveMyQA is an AI-powered QA testing service that provides comprehensive, well-documented bug reports. The service is affordable, easy to get started with, and requires no time-zapping chats. ILoveMyQA's team of Rockstar QAs is dedicated to helping businesses find and fix bugs before their customers do, so they can enjoy the results and benefits of having a QA team without the cost, management, and headaches.

Reprompt is a prompt testing tool designed to help developers save time and make data-driven decisions about their prompts. It enables users to analyze more data in less time, easily identify anomalies, and speed up debugging by testing multiple scenarios at once. With Reprompt, users can have confidence in their changes by comparing with previous versions. The tool also offers real-time trading, < 1 sec operations, no commissions, built-in enterprise encryption and security, 256-bit AES encryption, and advanced security standards.

Langfuse is a powerful tool that helps you develop, monitor, and test your LLM applications. With Langfuse, you can: * **Develop:** Instrument your app and start ingesting traces to Langfuse, inspect and debug complex logs, and manage, version, and deploy prompts from within Langfuse. * **Monitor:** Track metrics (cost, latency, quality) and gain insights from dashboards & data exports, collect and calculate scores for your LLM completions, run model-based evaluations, collect user feedback, and manually score observations in Langfuse. * **Test:** Track and test app behaviour before deploying a new version, test expected in and output pairs and benchmark performance before deploying, and track versions and releases in your application. Langfuse is easy to get started with and offers a generous free tier. You can sign up for Langfuse Cloud or deploy Langfuse locally or on your own infrastructure. Langfuse also offers a variety of integrations to make it easy to connect to your LLM applications.

llm_benchmarks is a collection of benchmarks and datasets for evaluating Large Language Models (LLMs). It includes various tasks and datasets to assess LLMs' knowledge, reasoning, language understanding, and conversational abilities. The repository aims to provide comprehensive evaluation resources for LLMs across different domains and applications, such as education, healthcare, content moderation, coding, and conversational AI. Researchers and developers can leverage these benchmarks to test and improve the performance of LLMs in various real-world scenarios.

The Lakera PINT Benchmark provides a neutral evaluation method for prompt injection detection systems, offering a dataset of English inputs with prompt injections, jailbreaks, benign inputs, user-agent chats, and public document excerpts. The dataset is designed to be challenging and representative, with plans for future enhancements. The benchmark aims to be unbiased and accurate, welcoming contributions to improve prompt injection detection. Users can evaluate prompt injection detection systems using the provided Jupyter Notebook. The dataset structure is specified in YAML format, allowing users to prepare their datasets for benchmarking. Evaluation examples and resources are provided to assist users in evaluating prompt injection detection models and tools.

FeedGen is an open-source tool that uses Google Cloud's state-of-the-art Large Language Models (LLMs) to improve product titles, generate more comprehensive descriptions, and fill missing attributes in product feeds. It helps merchants and advertisers surface and fix quality issues in their feeds using Generative AI in a simple and configurable way. The tool relies on GCP's Vertex AI API to provide both zero-shot and few-shot inference capabilities on GCP's foundational LLMs. With few-shot prompting, users can customize the model's responses towards their own data, achieving higher quality and more consistent output. FeedGen is an Apps Script based application that runs as an HTML sidebar in Google Sheets, allowing users to optimize their feeds with ease.

Parea AI provides a SDK to evaluate & monitor AI applications. It allows users to test, evaluate, and monitor their AI models by defining and running experiments. The SDK also enables logging and observability for AI applications, as well as deploying prompts to facilitate collaboration between engineers and subject-matter experts. Users can automatically log calls to OpenAI and Anthropic, create hierarchical traces of their applications, and deploy prompts for integration into their applications.

Examor is a website application that allows you to take exams based on your knowledge notes. It helps you to remember what you have learned and written. The application generates a set of questions from the documents you upload, and you can answer them to test your knowledge. Examor also uses GPT to score and validate your answers, and provides you with feedback. The application is still in its early stages of development, but it has the potential to be a valuable tool for learners.

Reinforcement Learning from AI Feedback (RLAIF) is a concept that describes a type of machine learning approach where **an AI agent learns by receiving feedback or guidance from another AI system**. This concept is closely related to the field of Reinforcement Learning (RL), which is a type of machine learning where an agent learns to make a sequence of decisions in an environment to maximize a cumulative reward. In traditional RL, an agent interacts with an environment and receives feedback in the form of rewards or penalties based on the actions it takes. It learns to improve its decision-making over time to achieve its goals. In the context of Reinforcement Learning from AI Feedback, the AI agent still aims to learn optimal behavior through interactions, but **the feedback comes from another AI system rather than from the environment or human evaluators**. This can be **particularly useful in situations where it may be challenging to define clear reward functions or when it is more efficient to use another AI system to provide guidance**. The feedback from the AI system can take various forms, such as: - **Demonstrations** : The AI system provides demonstrations of desired behavior, and the learning agent tries to imitate these demonstrations. - **Comparison Data** : The AI system ranks or compares different actions taken by the learning agent, helping it to understand which actions are better or worse. - **Reward Shaping** : The AI system provides additional reward signals to guide the learning agent's behavior, supplementing the rewards from the environment. This approach is often used in scenarios where the RL agent needs to learn from **limited human or expert feedback or when the reward signal from the environment is sparse or unclear**. It can also be used to **accelerate the learning process and make RL more sample-efficient**. Reinforcement Learning from AI Feedback is an area of ongoing research and has applications in various domains, including robotics, autonomous vehicles, and game playing, among others.

Prometheus-Eval is a repository dedicated to evaluating large language models (LLMs) in generation tasks. It provides state-of-the-art language models like Prometheus 2 (7B & 8x7B) for assessing in pairwise ranking formats and achieving high correlation scores with benchmarks. The repository includes tools for training, evaluating, and using these models, along with scripts for fine-tuning on custom datasets. Prometheus aims to address issues like fairness, controllability, and affordability in evaluations by simulating human judgments and proprietary LM-based assessments.

R-Judge is a benchmarking tool designed to evaluate the proficiency of Large Language Models (LLMs) in judging and identifying safety risks within diverse environments. It comprises 569 records of multi-turn agent interactions, covering 27 key risk scenarios across 5 application categories and 10 risk types. The tool provides high-quality curation with annotated safety labels and risk descriptions. Evaluation of 11 LLMs on R-Judge reveals the need for enhancing risk awareness in LLMs, especially in open agent scenarios. Fine-tuning on safety judgment is found to significantly improve model performance.

LLaMa2lang is a repository containing convenience scripts to finetune LLaMa3-8B (or any other foundation model) for chat towards any language that isn't English. The repository aims to improve the performance of LLaMa3 for non-English languages by combining fine-tuning with RAG. Users can translate datasets, extract threads, turn threads into prompts, and finetune models using QLoRA and PEFT. Additionally, the repository supports translation models like OPUS, M2M, MADLAD, and base datasets like OASST1 and OASST2. The process involves loading datasets, translating them, combining checkpoints, and running inference using the newly trained model. The repository also provides benchmarking scripts to choose the right translation model for a target language.

TigerGraph CoPilot is an AI assistant that combines graph databases and generative AI to enhance productivity across various business functions. It includes three core component services: InquiryAI for natural language assistance, SupportAI for knowledge Q&A, and QueryAI for GSQL code generation. Users can interact with CoPilot through a chat interface on TigerGraph Cloud and APIs. CoPilot requires LLM services for beta but will support TigerGraph's LLM in future releases. It aims to improve contextual relevance and accuracy of answers to natural-language questions by building knowledge graphs and using RAG. CoPilot is extensible and can be configured with different LLM providers, graph schemas, and LangChain tools.

Cherry Data Selection project introduces a self-guided methodology for LLMs to autonomously discern and select cherry samples from open-source datasets, minimizing manual curation and cost for instruction tuning. The project focuses on selecting impactful training samples ('cherry data') to enhance LLM instruction tuning by estimating instruction-following difficulty. The method involves phases like 'Learning from Brief Experience', 'Evaluating Based on Experience', and 'Retraining from Self-Guided Experience' to improve LLM performance.

The RAG Experiment Accelerator is a versatile tool that helps you conduct experiments and evaluations using Azure AI Search and RAG pattern. It offers a rich set of features, including experiment setup, integration with Azure AI Search, Azure Machine Learning, MLFlow, and Azure OpenAI, multiple document chunking strategies, query generation, multiple search types, sub-querying, re-ranking, metrics and evaluation, report generation, and multi-lingual support. The tool is designed to make it easier and faster to run experiments and evaluations of search queries and quality of response from OpenAI, and is useful for researchers, data scientists, and developers who want to test the performance of different search and OpenAI related hyperparameters, compare the effectiveness of various search strategies, fine-tune and optimize parameters, find the best combination of hyperparameters, and generate detailed reports and visualizations from experiment results.

Reflection-Tuning is a project focused on improving the quality of instruction-tuning data through a reflection-based method. It introduces Selective Reflection-Tuning, where the student model can decide whether to accept the improvements made by the teacher model. The project aims to generate high-quality instruction-response pairs by defining specific criteria for the oracle model to follow and respond to. It also evaluates the efficacy and relevance of instruction-response pairs using the r-IFD metric. The project provides code for reflection and selection processes, along with data and model weights for both V1 and V2 methods.

Torch-Pruning (TP) is a library for structural pruning that enables pruning for a wide range of deep neural networks. It uses an algorithm called DepGraph to physically remove parameters. The library supports pruning off-the-shelf models from various frameworks and provides benchmarks for reproducing results. It offers high-level pruners, dependency graph for automatic pruning, low-level pruning functions, and supports various importance criteria and modules. Torch-Pruning is compatible with both PyTorch 1.x and 2.x versions.

STRIDE GPT is an AI-powered threat modelling tool that leverages Large Language Models (LLMs) to generate threat models and attack trees for a given application based on the STRIDE methodology. Users provide application details, such as the application type, authentication methods, and whether the application is internet-facing or processes sensitive data. The model then generates its output based on the provided information. It features a simple and user-friendly interface, supports multi-modal threat modelling, generates attack trees, suggests possible mitigations for identified threats, and does not store application details. STRIDE GPT can be accessed via OpenAI API, Azure OpenAI Service, Google AI API, or Mistral API. It is available as a Docker container image for easy deployment.

This repository hosts the official code and data artifact for the paper 'Monitor-Guided Decoding of Code LMs with Static Analysis of Repository Context'. It introduces Monitor-Guided Decoding (MGD) for code generation using Language Models, where a monitor uses static analysis to guide the decoding. The repository contains datasets, evaluation scripts, inference results, a language server client 'multilspy' for static analyses, and implementation of various monitors monitoring for different properties in 3 programming languages. The monitors guide Language Models to adhere to properties like valid identifier dereferences, correct number of arguments to method calls, typestate validity of method call sequences, and more.

Comet Opik is a repository containing two main services: a frontend and a backend. It provides a Python SDK for easy installation. Users can run the full application locally with minikube, following specific installation prerequisites. The repository structure includes directories for applications like Opik backend, with detailed instructions available in the README files. Users can manage the installation using simple k8s commands and interact with the application via URLs for checking the running application and API documentation. The repository aims to facilitate local development and testing of Opik using Kubernetes technology.

Simulates the IELTS Writing Test, evaluates responses, and estimates band scores.

Provides IELTS speaking and writing feedback and scores.

SAT test preparation assistant, offering strategies and tips.

Get 1-on-1 tutoring. Trained from official questions only (verbal, quant, data insights). Score in the 90th percentile! 🚀

TOEIC Part 5の日本語説明付きの問題を無限に提供

Expert in GRE/GMAT with up-to-date strategies, tricks, answers and explanations to questions. Identifies strengths and weaknesses to curate a tailored study plan. Upload materials or questions for immediate answers and explanations.

解きたい分野を伝えると、問題をつくってくれます。解説で分からないところを聞くと、あなたが納得するまで教えてくれます。

快速提分+vx：alllllllen3

Bilingual TOEIC reading coach, explains all answer choices

Comprehensive, adaptive, multi-featured ASVAB study assistant

The official GPT for the MegaMock library

Crafting full, accurate Apex test classes, with 100% user service.

Test Shaman: Guiding software testing with Grug wisdom and humor, balancing fun with practical advice.

I'm like a test taker, answering questions across various subjects.

Makes every Sofware Tester an Expert Prompt Engineer

Primary School Question-Making Assistant（小学出题助手）

A moot competition companion. & Trial Prep companion . Test and improve arguments- predict your opponent's reaction.

Helps user learn essential vocabulary for GRE test with multiple choice questions

I write unit tests for uploaded Dynamics 365 C# code files.

How smart are you? Solve it with your friends, find out who is smarter!