AI News

JUNE 14, 2024

Researchers have introduced a novel approach called natural language embedded programs (NLEPs) to improve the numerical and symbolic reasoning capabilities of large language models (LLMs).

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Marktechpost

MARCH 22, 2024

The team has proposed a truly innovative approach to address these challenges: a data distillation procedure designed to distill essential information from large language models (LLMs) without compromising crucial details. Check out the Paper. All credit for this research goes to the researchers of this project.

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Topbots

JANUARY 30, 2023

In the last couple of years, Large Language Models (LLMs) such as ChatGPT, T5 and LaMDA have developed amazing skills to produce human language. We are quick to attribute intelligence to models and algorithms, but how much of this is emulation, and how much is really reminiscent of the rich language capability of humans?

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Marktechpost

JANUARY 15, 2024

One persistent challenge is the translation of low-resource languages, which often need more substantial data for training robust models. Traditional translation models, primarily based on large language models (LLMs), perform well with languages abundant in data but need help with underrepresented languages.

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Marktechpost

JANUARY 30, 2024

Language Agents represent a transformative advancement in computational linguistics. They leverage large language models (LLMs) to interact with and process information from the external world.

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Marktechpost

MARCH 2, 2024

The emergence of Large Language Models (LLMs) has notably enhanced the domain of computational linguistics, particularly in multi-agent systems. Despite the significant advancements, developing multi-agent applications remains a complex endeavor.

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Marktechpost

MAY 13, 2024

Tokenization is essential in computational linguistics, particularly in the training and functionality of large language models (LLMs). This process involves dissecting text into manageable pieces or tokens, which is foundational for model training and operations.

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Marktechpost

MAY 14, 2024

Research in computational linguistics continues to explore how large language models (LLMs) can be adapted to integrate new knowledge without compromising the integrity of existing information.

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Categorization Computational Linguistics Large Language Models Machine Learning 105

Marktechpost

MARCH 12, 2024

The advent of large language models (LLMs) has ushered in a new era in computational linguistics, significantly extending the frontier beyond traditional natural language processing to encompass a broad spectrum of general tasks.

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Marktechpost

APRIL 20, 2024

Exploring the synergy between reinforcement learning (RL) and large language models (LLMs) reveals a vibrant area of computational linguistics.

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Machine Learning Computational Linguistics Large Language Models LLM 137

Marktechpost

JANUARY 4, 2024

The development of Large Language Models (LLMs), such as GPT and BERT, represents a remarkable leap in computational linguistics. Training these models, however, is challenging.

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Marktechpost

AUGUST 15, 2024

Given the intricate nature of metaphors and their reliance on context and background knowledge, MCI presents a unique challenge in computational linguistics. This framework leverages the power of large language models (LLMs) like ChatGPT to improve the accuracy and efficiency of MCI.

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Marktechpost

DECEMBER 26, 2023

Computational linguistics focuses on developing advanced language models capable of understanding and generating human language. This dynamic field integrates the latest in machine learning and artificial intelligence, striving to create models that grasp the intricacies of language.

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Marktechpost

JANUARY 22, 2024

Its innovative techniques and optimizations make it a standout performer, capable of handling large-scale language understanding tasks with remarkable speed and reliability. As technology advances, solutions like Marlin play an important role in pushing the boundaries of what’s possible in computational linguistics.

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LLM Computational Linguistics Large Language Models Artificial Intelligence 129

Marktechpost

APRIL 29, 2024

In computational linguistics, much research focuses on how language models handle and interpret extensive textual data. These models are crucial for tasks that require identifying and extracting specific information from large volumes of text, presenting a considerable challenge in ensuring accuracy and efficiency.

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Marktechpost

AUGUST 12, 2023

This innovative tool was presented at the 2023 Association for Computational Linguistics (ACL) conference. Its primary purpose is quantifying and identifying biases within advanced generative models, like Stable Diffusion, which can magnify existing prejudices in the images generated.

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Google Research AI blog

JULY 10, 2023

Posted by Malaya Jules, Program Manager, Google This week, the 61st annual meeting of the Association for Computational Linguistics (ACL), a premier conference covering a broad spectrum of research areas that are concerned with computational approaches to natural language, is taking place online.

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ODSC - Open Data Science

APRIL 3, 2023

In particular, we fine-tune a re-ranker model using only the relevant feedback from each query and obtained large performance gains in multiple domains, including news and COVID. Lastly, we are currently working on integrating recent works on Large Language Models such as ChatGPT. Euro) in 2021.

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Marek Rei

NOVEMBER 4, 2024

It is probably good to also to mention that I wrote all of these summaries myself and they are not generated by any language models. Are Emergent Abilities of Large Language Models a Mirage? Do Large Language Models Latently Perform Multi-Hop Reasoning? Here we go. NeurIPS 2023. ArXiv 2024.

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The Stanford AI Lab Blog

MAY 25, 2022

The 60th Annual Meeting of the Association for Computational Linguistics (ACL) 2022 is taking place May 22nd - May 27th. We’re excited to share all the work from SAIL that’s being presented, and you’ll find links to papers, videos and blogs below.

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Bugra Akyildiz

JULY 16, 2023

In here, the distinction is that base models want to complete documents(with a given context) where assistant models can be used/tricked into performing tasks with prompt engineering. Large language models (LLMs) have shown promise in proving formal theorems using proof assistants such as Lean.

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Topbots

JUNE 15, 2023

Large language models such as ChatGPT process and generate text sequences by first splitting the text into smaller units called tokens. Language Disparity in Natural Language Processing This digital divide in natural language processing (NLP) is an active area of research. Shijie Wu and Mark Dredze.

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Mlearning.ai

FEBRUARY 19, 2023

Natural Language Processing (NLP) NLP is subset of Artificial Intelligence that is concerned with helping machines to understand the human language. It combines techniques from computational linguistics, probabilistic modeling, deep learning to make computers intelligent enough to grasp the context and the intent of the language.

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Flipboard

SEPTEMBER 7, 2023

One of the best-known critiques of AI large language models, or LLMs, for example, compares AI’s lack of language understanding to that of an animal: the concept of the “stochastic parrot,” which refers to how chatbots, not having minds, spit out language based on probabilistic models with no regard for meaning.

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John Snow Labs

DECEMBER 26, 2023

The 49th Annual Meeting of the Association for Computational Linguistics (ACL 2011). The post Testing the Robustness of LSTM-Based Sentiment Analysis Models appeared first on John Snow Labs. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng, and Christopher Potts. Learning Word Vectors for Sentiment Analysis.

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Sebastian Ruder

NOVEMBER 14, 2022

Cross-lingual performance prediction [42] could be used to estimate performance for a broader set of languages. Multilingual vs English-centric models   Let us now take a step back and look at recent large language models in NLP in general. Computational linguistics, 47(2), 255-308. Winata, G.

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Sebastian Ruder

JANUARY 24, 2022

  One of the most notable applications of large language models this year was code generation, which saw with Codex [79] its first integration into a major product as part of GitHub Copilot. Other advances in pre-training models ranged from better pre-training objectives [80] [81] to scaling experiments [82] [83].

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AWS Machine Learning Blog

MAY 22, 2023

Increasingly capable foundation models are being released continuously, with large language models (LLMs) being one of the most visible model classes. LLMs are models composed of billions of parameters trained on extensive corpora of text, up to hundreds of billions or even a trillion tokens.

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Snorkel AI

JUNE 14, 2023

That ranges all the way from analytical and computational linguists to applied research scientists, machine learning engineers, data scientists, product managers, designers, UX researchers, and so on. It’s clear how technology can help us in the advent of generative large language models.

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Snorkel AI

JUNE 14, 2023

That ranges all the way from analytical and computational linguists to applied research scientists, machine learning engineers, data scientists, product managers, designers, UX researchers, and so on. It’s clear how technology can help us in the advent of generative large language models.

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ML @ CMU

SEPTEMBER 22, 2023

Illustration depicting the process of a human and a large language model working together to find failure cases in a (not necessarily different) large language model. Trends Human Computer Interaction. [2] Adaptive Testing and Debugging of NLP Models. 2] Marco Tulio Ribeiro and Scott Lundberg.

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AWS Machine Learning Blog

AUGUST 8, 2024

In the past year, the team has increasingly focused on building artificial intelligence (AI) capabilities powered by large language models (LLMs) to improve productivity and experience for users. Karthik Raghunathan is the Senior Director for Speech, Language, and Video AI in the Webex Collaboration AI Group.

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Software Engineer Large Language Models Generative AI Computational Linguistics 111

ODSC - Open Data Science

MARCH 6, 2024

REGISTER NOW Building upon the exponential advancements in Deep Learning, Generative AI has attained mastery in Natural Language Processing. The driving force behind Generative AI and Large Language Models (LLMs) is Language Modeling, a Natural Language Processing technique that predicts the next word in a sequence of words.

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AWS Machine Learning Blog

AUGUST 8, 2024

Cisco’s Webex AI (WxAI) team plays a crucial role in enhancing these products with AI-driven features and functionalities, using large language models (LLMs) to improve user productivity and experiences. Karthik Raghunathan is the Senior Director for Speech, Language, and Video AI in the Webex Collaboration AI Group.

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