All numerical rankings should be taken with a grain of salt. We rank by numbers here strictly for the sake of interest. In general, the numerical ranking is substantially less relevant than the language’s tier or grouping. In many cases, one spot on the list is not distinguishable from th...
We use the aggregated history to determine ranking (though based on the table structure changes this can no longer be accomplished via a single query.) For Stack Overflow, we simply collect the required metrics using their useful data explorer tool. With that description out of the way, please...
While the company's ranking of programming languages is influential among developers, O'Grady notes that numerical rankings should be "taken with a grain of salt". The company produces the ranking twice a year. Python has been rising across several programming language popularity indexes, including ...
The results, in the form of labelled projects, showed overlap between the considered categories. Thus, in line with the methodology, a counter of tagged subcategories within matched bigrams was introduced as an element in the ranking of subcategories. The categorisation of the projects was distinguis...
-XL, the state-of-the-art autoregressive model, into pretraining. Empirically, XLNet outperforms BERT on 20 tasks, often by a large margin, and achieves state-of-the-art results on 18 tasks including question answering, natural language inference, sentiment analysis, and document ranking...
🚀 Feb. 17, 2025: We introduced two papers:SPOandAOT, check thecode! 🚀 Jan. 22, 2025: Our paperAFlow: Automating Agentic Workflow Generationaccepted fororal presentation (top 1.8%)at ICLR 2025,ranking #2in the LLM-based Agent category. ...
Modification includes reranking, deleting or proposing new word candidates. Collocations are word patterns that occur frequently in language; intuitively, if word A is present, there is a high probability that word B also is present. Methods to apply syntactic knowledge include N-gram word models,...
The aiXcoder core dataset is mainly used to enhance the performance of the large code model in the aforementioned programming languages, undergoing a rigorous filtering and selection process. Specifically, this process includes the following steps: 1) Selection of raw data; 2) Comprehensive ranking an...
The field of “BERTology” aims to locate linguistic representations in large language models (LLMs). These have commonly been interpreted as rep
Human Annotation Outcome ouyang2022training 2022 Preference Alignment Preference ranking Human Annotation Process lightman2023let 2023 Mathematical reasoning Stepwise annotation Human-LLM Collaboration Outcome goel2023llms 2023 Semantic analysis Human correction Human-LLM Collaboration Outcome wang2024human 2024 Text...