GAOKAO-Bench is an evaluation framework that utilizes GAOKAO questions as a dataset to evaluate large language models.
Las características principales de openlmlab/gaokao-bench son: Model Evaluation, Model Evaluation and Benchmarking, Natural Language Processing, Natural Language Corpora.
Las alternativas de código abierto para openlmlab/gaokao-bench incluyen: open-compass/opencompass — OpenCompass is an open-source framework for standardized benchmarking of large language models. It provides a… ntmc-community/matchzoo — MatchZoo is a deep learning framework designed for building, training, and evaluating neural networks that determine… didi/chinesenlp — Datasets, SOTA results of every fields of Chinese NLP. comet-ml/opik — Opik is an observability and evaluation platform designed for generative AI applications and agentic workflows. It… confident-ai/deepeval — Deepeval is a framework for testing and evaluating large language model applications. It provides a suite of tools for… complementizer/wcep-mds-dataset — The WCEP dataset for multi-document summarization (MDS) consists of short, human-written summaries about news events,…
OpenCompass is an open-source framework for standardized benchmarking of large language models. It provides a configurable evaluation pipeline that supports both objective and subjective assessment, using a dual-engine architecture to handle closed-form answer comparison and open-ended response rating. The framework is designed as a modular platform where datasets, models, and metrics are composed through declarative YAML configuration files. The framework distinguishes itself through its extensible model integration layer, which supports custom models, HuggingFace models, and third-party API
MatchZoo is a deep learning framework designed for building, training, and evaluating neural networks that determine the relevance and similarity between pairs of textual inputs. It serves as a research platform for neural information retrieval, specifically supporting the development of models for document retrieval, question answering, and ranking tasks. The framework utilizes declarative architecture composition to define complex neural network structures. It includes automated hyper-parameter resolution to populate missing configuration parameters before model compilation and uses callbac
The WCEP dataset for multi-document summarization (MDS) consists of short, human-written summaries about news events, obtained from the Wikipedia Current Events Portal (WCEP), each paired with a cluster of news articles associated with an event. These articles consist of sources cited by editors…
Opik is an observability and evaluation platform designed for generative AI applications and agentic workflows. It provides a centralized environment for tracing execution flows, managing prompt templates, and monitoring production performance, allowing teams to gain visibility into complex model interactions and tool usage without requiring manual application code changes. The platform distinguishes itself through its integrated approach to the AI development lifecycle, combining distributed trace instrumentation with automated evaluation frameworks. It supports model-as-a-judge scoring, syn