Marktechpost
MAY 11, 2024
With the significant advancement in the fields of Artificial Intelligence (AI) and Natural Language Processing (NLP), Large Language Models (LLMs) like GPT have gained attention for producing fluent text without explicitly built grammar or semantic modules. If you like our work, you will love our newsletter.
Marktechpost
MARCH 26, 2024
Large language models (LLMs) are at the forefront of technological advancements in natural language processing, marking a significant leap in the ability of machines to understand, interpret, and generate human-like text. Similarly, on the CaseHOLD dataset, there was a 32.6% enhancement, and on SNIPS, a 32.0%
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Marktechpost
AUGUST 3, 2023
Also, the limited number of available music-language datasets poses a challenge. With the scarcity of datasets, training a music captioning model successfully doesn’t remain easy. Large language models (LLMs) could be a potential solution for music caption generation. The training process of GPT-3.5
Marktechpost
JANUARY 15, 2024
Machine translation, an integral branch of Natural Language Processing, is continually evolving to bridge language gaps across the globe. One persistent challenge is the translation of low-resource languages, which often need more substantial data for training robust models.
Unite.AI
JANUARY 22, 2024
Synthetic data , artificially generated to mimic real data, plays a crucial role in various applications, including machine learning , data analysis , testing, and privacy protection. However, generating synthetic data for NLP is non-trivial, demanding high linguistic knowledge, creativity, and diversity.
Marktechpost
SEPTEMBER 2, 2023
On various Natural Language Processing (NLP) tasks, Large Language Models (LLMs) such as GPT-3.5 They optimize the LVLM using synthesized anomalous visual-textual data and incorporating IAD expertise. Direct training using IAD data, however, needs to be improved. Data scarcity is the first.
Allen AI
DECEMBER 4, 2023
Highlighted work from our institute appearing at this year’s EMNLP conference Empirical Methods in Natural Language Processing ( EMNLP ) is a leading conference in natural language processing and artificial intelligence. Yet controlling these models through prompting alone is limited.
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