This dataset contains 3.3K expert-level pairwise human preferences for model responses generated by 6 models in response to 80 MT-bench questions. The 6 models are GPT-4, GPT-3.5, Claud-v1, Vicuna-13B, Alpaca-13B, and LLaMA-13B. The annotators are mostly graduate students with expertise ...
1 introduction We create MT-bench, a benchmark consisting of80 high-quality multi-turn questions. MT-bench is designed to test multi-turn conversation and instruction-following ability, covering common use cases and focusing on challenging questions to differentiate models. We identify8 common categor...
The OPUS-MT benchmark is a systematic collection of results from these models, focusing on verifiable translation performance and large coverage in terms of languages and domains. The OPUS-MT Dashboard is a web-based platform that provides a comprehensiv
Pixtral Large 展示了 MM-MT-Bench 的竞争能力,超过了所有 Claude-3.5 Sonnet (新款)、 Gemini-1.5 Pro 和 GPT-4o (最新款)。MM-MT-Bench 是一个开源的、基于法官的评估,旨在反映多模式 LLM 的真实用例(详见 Pixtral 12B 技术报告)。 Mistral刚在在7月份发布了3个模型:明星 AI 独角兽 Mistral AI...,...
to boost the feature representation capability of point tokens, we refine the classification head, enabling point tokens to directly participate in prediction. Experimental results on multiple evaluation benchmarks demonstrate that PointMT achieves performance comparable to state-of-the-art methods while ...
Please cite our paper if you find the repo helpful in your work: @article{fan2024fairmt, title={FairMT-Bench: Benchmarking Fairness for Multi-turn Dialogue in Conversational LLMs}, author={Fan, Zhiting and Chen, Ruizhe and Hu, Tianxiang and Liu, Zuozhu}, journal={arXiv preprint arXiv:...
我们正在开源我们的Nemotron-Mini-4B-Instruct模型!这个模型是通过对Nemotron-4-15B进行修剪和蒸馏得到的。在MT-Bench和指令跟踪方面展示了出色的基准结果,适用于小于4B大小的模型。欢迎尝试并提供反馈
The code (training, serving, and evaluation) in this repository is mostly developed for or derived from the paper below. Please cite it if you find the repository helpful. @misc{zheng2023judging, title={Judging LLM-as-a-judge with MT-Bench and Chatbot Arena}, author={Lianmin Zheng and We...
We tested it on several benchmark data sets, namely KITTI 2015, Driving, FlyingThings3D, Middlebury 2014, Monkaa and the TrimBot2020 garden data sets, and achieved competitive accuracy. The code is available at https://github.com/rbrandt1/MaxTreeS ....
In this paper, we propose a conversational SimulMT framework to enhance the inference efficiency of LLM-based SimulMT through multi-turn-dialogue-based decoding. Our experiments with Llama2-7b-chat on two SimulMT benchmarks demonstrate the superiority of LLM in translation quality while achieving ...