Popular GitHub Repositories for Errors

AI-powered Jupyter Notebook — use local AI to generate and edit code cells, automatically fix errors, and chat with your data

The toolkit to test, validate, and evaluate your models and surface, curate, and prioritize the most valuable data for labeling.

DeepConsensus uses gap-aware sequence transformers to correct errors in Pacific Biosciences (PacBio) Circular Consensus Sequencing (CCS) data.

API 200 is an open source API gateway to simplify 3rd-party integrations. Import endpoints, set up caching, retries, and mocks. Access all services via one URL. Monitor logs, track errors, and get alerts on API incidents.

? Keeps ChatGPT sessions fresh to avoid network errors + Cloudflare checks

AI powered cli coding agent that monitors your dev/test server and fixes errors and adds features

[ICRA2023] CoAlign: Robust Collaborative 3D Object Detection in Presence of Pose Errors

The definitive Vibe Coder's sanity check MCP server: Prevent cascading errors in AI workflows by implementing strategic pattern interrupts. Uses tool call "Vibe Check" with LearnLM 1.5 Pro (Gemini API), fine-tuned for pedagogy and metacognition to enhance complex workflow strategy, and prevents tunnel vision errors.

Certified defense to adversarial examples using CROWN and IBP. Also includes GPU implementation of CROWN verification algorithm (in PyTorch).

An intelligent CLI tool that intercepts terminal errors and provides instant, context-aware solutions using LLM's. Transform natural language into terminal commands and never get stuck on cryptic error messages again! Currently in early development.

Comprehensive guidelines for AI assistants working with Nuxt UI v3. Prevents common v2→v3 migration errors and provides best practices for modern Nuxt UI development.

CLAIRify: Errors are Useful Prompts: Instruction Guided Task Programming with Verifier-Assisted Iterative Prompting

Developed a sophisticated machine learning model capable of generating diverse interview questions aligned with specific topics, ensuring depth of conversation. Integrated advanced Natural Language Processing (NLP) algorithms to analyse spoken responses, identifying grammatical errors & offering accurate corrections after the interview.

A markerless, low monetary cost, accessible approach to human gait analysis using an OpenPose-based 2D estimation system for knee flexion landmarks. Clinical gait angles, points of contact, and errors in estimation plotted.

Code for Findings of ACL 2022 Paper "Sentiment Word Aware Multimodal Refinement for Multimodal Sentiment Analysis with ASR Errors"

NoMIRACL: A multilingual hallucination evaluation dataset to evaluate LLM robustness in RAG against first-stage retrieval errors on 18 languages.

Learning to Avoid Errors in GANs by Input Space Manipulation (Code for paper)

DDC-Outlier: Preventing medication errors using unsupervised learning

Neural Lexicon Reader: Reduce Pronunciation Errors in End-to-end TTS by Leveraging External Textual Knowledge

Statistics, signal processing, finance, econometrics, manufacturing, networking[disambiguation needed] and data mining, anomaly detection (also outlier detection) is the identification of rare items, events or observations which raise suspicions by differing significantly from the majority of the data. Typically the anomalous items will translate to some kind of problem such as bank fraud, a structural defect, medical problems or errors in a text. Anomalies are also referred to as outliers, novelties, noise, deviations and exceptions.