The article discusses the significant progress in Natural Language Processing (NLP), focusing on Large Language Models (LLM) and prompt engineering techniques. The authors discuss the use of reasoning topologies like…
Continue readingThe paper presents TURNA, a language model designed for the low-resource language Turkish. The model is capable of both understanding and generating natural language tasks. TURNA is pre-trained using an…
Continue readingThe article presents a new method called crowdsourced adaptive survey (CSAS), which combines natural language processing and adaptive algorithms. The method transforms open-ended text from participants into potential survey questions,…
Continue readingThis paper investigates the biases present in Bengali sentiment analysis tools, particularly those influenced by the impacts of colonialism. The authors conducted an audit of all such tools available on…
Continue readingThe article introduces MuTox, a multilingual audio-based toxicity detection system. It’s the first of its kind, with a dataset that includes 20,000 audio utterances for English and Spanish, and 4,000…
Continue readingThe article ‘Understanding Large-Language Model (LLM)-powered Human-Robot Interaction’ by Callie Y. Kim, Christine P Lee, and Bilge Mutlu explores the potential of large-language models (LLMs) in improving human-robot interaction. The…
Continue readingThis article presents L3Cube-IndicNews, a multilingual text classification corpus aimed at creating a high-quality dataset for Indian regional languages. The focus is on news headlines and articles in 10 prominent…
Continue readingTinyLlama, a compact 1.1B language model pretrained on around 1 trillion tokens for roughly 3 epochs, shows remarkable performance in various downstream tasks. Despite its small size, it outperforms other…
Continue readingThis academic paper delves into the advancements made by Large Language Models (LLMs) in natural language processing and their extension to other modalities such as speech and vision. It carries…
Continue readingThis research paper discusses a type of output error called hallucinations, produced by deep neural networks in Automatic Speech Recognition (ASR). Hallucinations in ASR are transcriptions generated by a model…
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