Large Language Models (LLMs) have drawn widespread attention and research due to their astounding performance in text generation and reasoning tasks. Derivative products, like ChatGPT, have been extensively deployed and highly sought after. Meanwhile, the evaluation and optimization of LLMs in software...
Towards Trustworthy and Responsible Large Language Models摘要 ABSTRACT Large language models (LLMs) have demonstrated remarkable performance on knowledge reasoning tasks, owing to their implicit knowledge derived from extensive pretraining...
prediction, reasoning, and decision-making through direct interactions with the model. By integrating GTL with language models, the system not only generates predictive results but also provides explanations, enhancing the interpretability of tabular data le...
[CL] Towards Systematic Evaluation of Logical Reasoning Ability of Large Language Models O网页链接 LogicBench通过设计包含25种推理模式的问答数据集,系统地评估了大型语言模型在命题逻辑、一阶逻辑和非单调逻辑方面的逻辑推理能力,发现现有模型在处理复杂推理和否定时存在明显缺陷,为未来的研究提供了有价值的洞见。
2023. Pythia: A suite for analyzing large language models across training and scaling. In ICML, pages 2397– 2430. Yonatan Bisk, Rowan Zellers, Jianfeng Gao, Yejin Choi, et al. 2020. PIQA: Reasoning about physical commonsense in natural language. In Proceedings of the AAAI, volume 34, ...
Towards AGI in Computer Vision: Lessons Learned from GPT and Large Language Modelsarxiv.org/abs/2306.08641 这篇文章是今年6月份挂到Arxiv上面的,算是比较新的文章,相当于一篇Techical Report,或者说一篇Review,展望了接下来AGI在CV领域的研究方向,我简单地对论文做了一个翻译(感谢ChatGPT 学术优化中的论文...
Code for "Towards Learning to Reason: Comparing LLMs with Neuro-Symbolic on Arithmetic Relations in Abstract Reasoning" - IBM/raven-large-language-models
这种设置在语言模型训练中比较常见,尤其是Causal Language Model类型。 总结: 代码从examples中提取到每个样本的文本数据,使用tokenizer将其转化为 token ID,同时生成attention_mask和labels,最终构造出output作为模型的输入。这个过程实现了从原始文本到模型可以理解的数值表示的转化。
togethercomputer/stripedhyena 349 lindermanlab/S5 284 ↳ Quickstart in Colab 32 See all 6implementations Tasks Edit AddRemove Datasets Results from the Paper Edit AddRemove Ranked #37 onLanguage Modelling on WikiText-103 Get a GitHub badge ...
“Chain of thought prompting elicits reasoning in large language models.” arXiv preprint arXiv:2201.11903 (2022). [4] Zhou, Yongchao, et al. “Large language models are human-level prompt engineers.” arXiv preprint arXiv:2211.01910 (2022). [5] Shin, Taylor, et al. “Autoprompt: ...