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A curated list of Awesome LLM Inference Paper with codes.

A curated list of Multi-modal Large Language Model in 3D world, including 3D understanding, reasoning, generation, and embodied agents.

a curated collection of datasets specifically designed for chatbot training, including links, size, language, usage, and a brief description of each dataset

整理开源的中文大语言模型，以规模较小、可私有化部署、训练成本较低的模型为主，包括底座模型，垂直领域微调及应用，数据集与教程等。

Applying Large language models (LLMs) for diverse optimization tasks (Opt) is an emerging research area. This is a collection of references and papers of LLM4Opt.

This paper list focuses on the theoretical or empirical analysis of language models, e.g., the learning dynamics, expressive capacity, interpretability, generalization, and other interesting topics.

a benchmark platform for large language models (LLMs) that features anonymous, randomized battles in a crowdsourced manner.

aims to track, rank, and evaluate LLMs and chatbots as they are released.

An Automatic Evaluator for Instruction-following Language Models using Nous benchmark suite.

an evaluation benchmark focused on ancient Chinese language comprehension.

A pioneering benchmark specifically designed to assess honesty in LLMs comprehensively.

evaluates LLM's ability to call external functions/tools.

CompassRank is dedicated to exploring the most advanced language and visual models, offering a comprehensive, objective, and neutral evaluation reference for the industry and research.

a benchmark evaluating QA methods that operate over a mixture of heterogeneous input sources (KB, text, tables, infoboxes).

a benchmark for evaluating the performance of large language models (LLMs) in various tasks related to both textual and visual imagination.

a meta-benchmark that evaluates how well factuality evaluators assess the outputs of large language models (LLMs).

a benchmark designed to evaluate large language models (LLMs) specifically in their ability to answer real-world coding-related questions.

a benchmark designed to evaluate large language models in the legal domain.

focuses on understanding how these models perform in various scenarios and analyzing results from an interpretability perspective.

a benchmark that evaluates large language models on a variety of multimodal reasoning tasks, including language, natural and social sciences, physical and social commonsense, temporal reasoning, algebra, and geometry.