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Language Model

Factory AI has unveiled ‘Code Droid’, a tool specially developed to improve and automate programming tasks through sophisticated self-reliant features: it has demonstrated its efficiency by scoring 19.27% on full SWE-bench and 31.67% on the lite version of SWE-bench.

Factory AI has unveiled Code Droid, a major innovation in artificial intelligence (AI) designed to streamline and expedite software development processes. As an autonomous AI tool, Code Droid is created to handle a multitude of coding duties based on natural language instructions, assimilating insights from multiple fields, including robotics, machine learning, and cognitive science. The key…

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Factory AI has launched Code Droid, an innovative tool meant to streamline and improve coding with sophisticated self-governing features. It boasts an impressive score of 19.27% on SWE-bench Full and 31.67% on SWE-bench Lite.

Factory AI has launched its state-of-the-art innovation, Code Droid. This artificial intelligence (AI) tool is designed to revolutionize software development by mechanizing and quickening the processes involved. Code Droid is essentially an autonomous system which carries out multiple coding tasks dependent on natural language directions. Its main objective is to automatize mundane programming operations, thus…

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BM25S: An English Programming Package Constituting the BM25 Procedure for Organizing Documents According to a Search Query

The rise of vast data systems has made information retrieval a vital process for numerous platforms, including search engines and recommender systems. This is achieved by finding documents based on their content, a task that presents challenges related to relevance assessment, document ranking, and efficiency. A new Python library named BM25S aims to overcome the…

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BM25S: A Python Toolkit for Executing the BM25 Algorithm to Prioritize Documents According to a Query

In the digital era where data is vast, the importance of information retrieval cannot be overstated, particularly for search engines, recommender systems, and applications that find documents based on their content. Information retrieval involves three fundamental challenges - relevance assessment, document ranking, and efficiency. BM25S is a recently introduced Python library that tackles these challenges…

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LOFT: An All-Inclusive AI Benchmark for Assessing Extensive-Context Language Models

Long-Context Language Models (LCLMs) have emerged as a new frontier in artificial intelligence with the potential to handle complex tasks and applications without needing intricate pipelines that were traditionally used due to the limitations of context length. Unfortunately, their evaluation and development have been fraught with challenges. Most evaluations rely on synthetic tasks with fixed-length…

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Emergence of Diffusion-Based Linguistic Models: Evaluating SEDD versus GPT-2

Large Language Models (LLMs) have revolutionized natural language processing, with considerable performance across various benchmarks and practical applications. However, these models also have their own sets of challenges, primarily due to the autoregressive training paradigm which they rely upon. The sequential nature of autoregressive token generation can drastically slow down processing speeds, limiting their practicality…

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Improving LLM Dependability: Identifying Made-up Stories using Semantic Chaos.

Researchers from the OATML group at the University of Oxford have developed a statistical method to improve the reliability of large language models (LLMs) such as ChatGPT and Gemini. This method looks to mitigate the issues of "hallucinations," wherein the model generates false or unsupported information, and "confabulations," where the model provides arbitrary or incorrect…

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Improving LLM Dependability: Identifying Misconceptions through Semantic Entropy

Language Learning Models (LLMs) such as ChatGPT and Gemini have shown the capability of answering complex queries, but they often produce false or unsupported information, a situation aptly titled "hallucinations". This gets in the way of their reliability, with potential repercussions in critical fields like law and medicine. A specific subset of these hallucinations, known…

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Revitalizing Mute Videos: The Potential of Google DeepMind’s Audio-from-Video (V2A) Technology

Google DeepMind is set to make significant strides in the field of artificial intelligence with its innovative Video-to-Audio (V2A) technology. This technology will revolutionize the synthesis of audiovisual content by addressing the common issue in current video generation models, which often produce silent films. V2A's potential to transform artificial intelligence-driven media creation is tremendous, providing…

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RABBITS: A Distinctive Database and Scoring System to Assist in Assessing Language Model Performance in Healthcare Sector

Biomedical Natural Language Processing (NLP) uses machine learning to interpret medical texts, aiding with diagnoses, treatment recommendations, and medical information extraction. However, ensuring the accuracy of these models is a challenge due to diverse and context-specific medical terminologies. To address this issue, researchers from MIT, Harvard, and Mass General Brigham, among other institutions, developed RABBITS (Robust…

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Explained with Simple Human Analogies: A Guide to Frequently Employed Advanced Techniques in Prompt Engineering

Artificial Intelligence (AI) models are becoming more sophisticated, and efficient communication with these models is crucial. Various prompt engineering strategies have been developed to facilitate this communication, utilizing concepts and structures similar to human problem-solving methods. These strategies can be categorized into different types: chaining methods, decomposition-based methods, path aggregation methods, reasoning-based methods, and external…

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Introducing BigCodeBench by BigCode: The New Benchmark for Assessing Sizeable Language Models in Practical Coding Assignments.

BigCode, a leading developer of large language models (LLMs), has launched BigCodeBench, a new benchmark for comprehensively assessing the programming capabilities of LLMs. This concurrent approach addresses the limitations of existing benchmarks like HumanEval, which has been criticized for its simplicity and scant real-world relevance. BigCodeBench comprises 1,140 function-level tasks which require the LLMs to…

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