Marktechpost

JANUARY 22, 2024

For example, it organizes computations in a way that minimizes the need to load data repeatedly from memory, ensuring that the process doesn’t become a bottleneck. Additionally, Marlin uses asynchronous loading of data, meaning it can fetch the necessary information while continuing other computations, optimizing the use of the GPU.

LLM 129

LLM Computational Linguistics Large Language Models Artificial Intelligence 129

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. This structured approach provides a clear view of the impact of fine-tuning with both familiar and novel data on model accuracy.

Categorization 103

Categorization Computational Linguistics Large Language Models Machine Learning 103

Allen AI

JULY 7, 2023

In Advances in Neural Information Processing Systems, volume 33, pages 1877–1901. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 1115–1127, Seattle, United States. Association for Computational Linguistics.

Computational Linguistics 98

Computational Linguistics Artificial Intelligence Artificial Intelligence AI 98

Marktechpost

JANUARY 4, 2024

The development of Large Language Models (LLMs), such as GPT and BERT, represents a remarkable leap in computational linguistics. The computational intensity required and the potential for various failures during extensive training periods necessitate innovative solutions for efficient management and recovery.

Computational Linguistics 117

Computational Linguistics Large Language Models LLM BERT 117

NYU Center for Data Science

JULY 24, 2024

Ravfogel’s research focuses on understanding how neural networks learn distributed representations that encode structured information, and how these representations are utilized to solve complex tasks. This multidisciplinary foundation has informed his unique approach to computational linguistics and machine learning.

Natural Language Processing 74

Natural Language Processing Computational Linguistics Neural Network Machine Learning 74

NLP People

MAY 18, 2018

DFKI LT lab conducts advanced research in language technology and develops novel solutions related to information and knowledge management, content production, speech and text processing. For more information about job openings , projects , and publications visit their website. More information can be found on their webpage.

NLP 52

NLP Computational Linguistics Data Mining Natural Language Processing 52

ODSC - Open Data Science

APRIL 3, 2023

Another research line in SQuARE is how to make information retrieval more effective. Information retrieval is a key aspect in question answering since it is used to obtain the documents to extract the answers to the given questions. One type of user question is information-seeking. Euro) in 2021.

Neural Network 117

Neural Network Natural Language Processing NLP Computational Linguistics 117

NYU Center for Data Science

JANUARY 24, 2025

The paper will be presented at the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL2025). The project builds on Rudners long-standing collaboration with CSET, where he has published several papers on AI policy and governance since 2019. By StephenThomas

Computational Linguistics 70

Computational Linguistics Large Language Models Neural Network Computer Vision 70

AssemblyAI

SEPTEMBER 18, 2023

These feats of computational linguistics have redefined our understanding of machine-human interactions and paved the way for brand-new digital solutions and communications. Engineers train these models on vast amounts of information. Reliability: LLMs can inadvertently generate false information or fake news.

Large Language Models 130

Large Language Models BERT Auto-complete LLM 130

NLP People

APRIL 10, 2019

While ETH does not have a Linguistics department, its Data Analytics Lab , lead by Thomas Hofmann , focuses on topics in machine learning, natural language processing and understanding, data mining and information retrieval. Research foci include Big Data technology, data mining, machine learning, information retrieval and NLP.

NLP 52

NLP Computational Linguistics Natural Language Processing Data Mining 52

Marek Rei

NOVEMBER 4, 2024

Prompts are changed by introducing spelling errors, replacing synonyms, concatenating irrelevant information or translating from a different language. link] The paper proposes query rewriting as the solution to the problem of LLMs being overly affected by irrelevant information in the prompts. Character-level attacks rank second.

Machine Learning 80

Machine Learning NLP Large Language Models LLM 80

Flipboard

SEPTEMBER 7, 2023

We’re kind of at the point where we can make fire but do not even have the rudiments of what we’d need to understand it,” my friend Luke Gessler , a computational linguist, told me. We have no reason to believe any current AIs are sentient, but we also have no way of knowing whether or how that could change.

AI 181

AI AI Computational Linguistics Chatbots 181

Marktechpost

MARCH 22, 2024

This groundbreaking study delves into language model efficiency, aiming to streamline communication between humans and machines and reduce the verbosity of natural language without compromising the conveyed information’s essence. The technical foundation of this research is both innovative and robust. Check out the Paper.

Large Language Models 56

Large Language Models Computational Linguistics ML Artificial Intelligence 56

Allen AI

JULY 8, 2023

The *CL conferences created the NLP Reproducibility Checklist in 2020 to be completed by authors at submission to remind them of key information to include. First, they found evidence of an increase in reporting of information on efficiency, validation performance, summary statistics, and hyperparameters after the Checklist’s introduction.

Computational Linguistics 52

Computational Linguistics NLP Explainability AI Research 52

Topbots

JUNE 15, 2023

Discussion Implications of tokenization language disparity Overall, requiring more tokens (to tokenize the same message in a different language) means: You’re limited by how much information you can put in the prompt (because the context window is fixed). Association for Computational Linguistics. Indo-European, Sino-Tibetan).[

Natural Language Processing 59

Natural Language Processing Computational Linguistics NLP ChatGPT 59

Marktechpost

AUGUST 15, 2024

Accurately processing metaphors is vital for various NLP applications, including sentiment analysis, information retrieval, and machine translation. Given the intricate nature of metaphors and their reliance on context and background knowledge, MCI presents a unique challenge in computational linguistics.

NLP 60

NLP Large Language Models Computational Linguistics Neural Network 60

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.

Large Language Models 93

Large Language Models Natural Language Processing NLP Computational Linguistics 93

NLP People

JUNE 5, 2018

For more information check their jobs section. The company utilises algorithms for targeted data collection and semantic analysis to extract fine-grained information from various types of customer feedback and market opinions. From time to time the company hires NLP-related specialists for their office in Berlin.

NLP 52

NLP Data Mining Deep Learning Machine Learning 52

Topbots

JANUARY 30, 2023

Since the wind is coming from Maria’s direction, she asks “Maria” for a report on current weather conditions as an important piece of information. Another important limitation, as of now, is the recency of the information. For example, the communicative intent can be to convey information, socialise or ask someone to do something.

Large Language Models 52

Large Language Models Computational Linguistics LLM Natural Language Processing 52

The Stanford AI Lab Blog

FEBRUARY 1, 2022

Informed by prior work, we test the following 4 hypotheses: Redirect - Inspired by Brahnam 5 , we hypothesize that using explicit redirection when responding to an offensive user utterance is an effective strategy. Ideally, everyone would take turns responding to prompts, sharing information about themselves, and introducing new topics.

Computational Linguistics 40

Computational Linguistics Chatbots Robotics Natural Language Processing 40

Allen AI

MAY 30, 2023

We evaluate the approach using human evaluation: compared to four other baselines ClarifyDelphi produces more informative and more relevant questions. It would be more elegant to have a way to automatically predict when enough contextual information has been obtained and the system does not have to ask an additional question.

Computational Linguistics 52

Computational Linguistics Linked Data Chatbots NLP 52

AWS Machine Learning Blog

MAY 22, 2023

Solution overview The target task in this post is to, given a chunk of text in the prompt, return questions that are related to the text but can’t be answered based on the information it contains. This is a useful task to identify missing information in a description or identify whether a query needs more information to be answered.

Machine Learning 107

Machine Learning Natural Language Processing Computational Linguistics NLP 107

NLP People

JANUARY 2, 2019

Hundreds of researchers, students, recruiters, and business professionals came to Brussels this November to learn about recent advances, and share their own findings, in computational linguistics and Natural Language Processing (NLP).

BERT 52

BERT Natural Language Processing Computational Linguistics NLP 52

Mlearning.ai

FEBRUARY 6, 2023

From uncovering patterns of human behavior to predicting the spread of ideas and information, the application of graph theory in social network analysis holds immense promise. 2019 Annual Conference of the North American Chapter of the Association for Computational Linguistics. [7] Attention is not Explanation. Weigreffe, Y.

Explainable AI 52

Explainable AI Explainability ChatGPT Chatbots 52

John Snow Labs

DECEMBER 26, 2023

In today’s enormous digital environment, where information flows at breakneck speed, determining the sentiment concealed inside textual data has become critical. On the other hand, Sentiment analysis is a method for automatically identifying, extracting, and categorizing subjective information from textual data. Daly, Peter T.

Neural Network 52

Neural Network Computational Linguistics NLP Machine Learning 52

Sebastian Ruder

AUGUST 18, 2019

Different architectures show different layer-wise trends in terms of what information they capture ( Liu et al., The general setup in probing tasks used to study linguistic knowledge within contextual word representations ( Liu et al., On the whole, it is difficult to learn certain types of information from raw text.

NLP 75

NLP BERT Natural Language Processing Computational Linguistics 75

NLP People

SEPTEMBER 12, 2017

This job brought me in close contact with a large number of IT researchers, and some of them happened to work in computational linguistics and machine learning. It might be a bit too early for an informative answer, but what can students and professionals planning to move to Europe expect from personal and professional perspectives?

Computational Linguistics 52

Computational Linguistics Machine Learning Data Mining Natural Language Processing 52

Heartbeat

FEBRUARY 21, 2023

Picture by Anna Nekrashevich , Pexels.com Introduction Sentiment analysis is a natural language processing technique which identifies and extracts subjective information from source materials using computational linguistics and text analysis.

NLP 52

NLP Natural Language Processing Machine Learning Computational Linguistics 52

Sebastian Ruder

NOVEMBER 14, 2022

Initiatives   The Association for Computational Linguistics (ACL) has emphasized the importance of language diversity, with a special theme track at the main ACL 2022 conference on this topic. Practical data   For new datasets, it is thus ever more important to create data that is informed by real-world usage.

Natural Language Processing 52

Natural Language Processing NLP Computational Linguistics BERT 52

Bugra Akyildiz

JULY 16, 2023

Natural language processing (NLP) or computational linguistics is one of the most important technologies of the information age.

LLM 52

LLM Chatbots Neural Network Large Language Models 52

AWS Machine Learning Blog

MARCH 2, 2023

Financial market participants are faced with an overload of information that influences their decisions, and sentiment analysis stands out as a useful tool to help separate out the relevant and meaningful facts and figures. In the main() function, you can call the run() function as shown in the following code.

BERT 89

BERT Deep Learning Metadata Auto-complete 89

Explosion

DECEMBER 28, 2019

Ines’ talk in the language track, “Practical Transfer Learning for NLP with spaCy and Prodigy” , focused on the increasing trend of initializing models with information from large raw-text corpora, and how you can use this type of technique in spaCy and Prodigy. Sep 4: spacy-transformers kept getting better as we released v0.4.0,

NLP 52

NLP BERT Machine Learning Python 52

Sebastian Ruder

JANUARY 24, 2022

Alternatively, FNet [27] uses 1D Fourier Transforms instead of self-attention to mix information at the token level.   A prompt can be used to encode task-specific information, which can be worth up to 3,500 labeled examples, depending on the task [39]. The Uniform model (left) trains on all data without explicit time information.

NLP 52

NLP ML BERT Computational Linguistics 52

Sebastian Ruder

FEBRUARY 23, 2023

 Instead of learning module parameters directly, they can be generated using an auxiliary model (a hypernetwork) conditioned on additional information and metadata. We provide a high-level overview of some of the trade-offs of the different computation functions below. Computer vision and cross-modal learning.

Deep Learning 52

Deep Learning NLP Computer Vision Metadata 52

Applied Data Science

DECEMBER 23, 2022

As people played around with them, many problems such as bias and mis-information became prevalent. The first computational linguistics methods tried to bypass the immense complexity of human language learning by hard-coding syntax and grammar rules in their models. Some of this year’s breakthroughs created controversies.

Neural Network 52

Neural Network Data Science AI AI 52

Marek Rei

OCTOBER 4, 2019

It may inform discussion if we report one other statistic we’ve been able to retrieve thanks to data sharing by Emily Bender & Leon Derczynski, the program chairs for COLING 2018. One good reason to take our major conferences to new countries is to equalise the barrier of obtaining visas to attend.

NLP 52

NLP Computational Linguistics Automation ML 52

The Stanford AI Lab Blog

JANUARY 21, 2022

Conference of the North American Chapter of the Association for Computational Linguistics. ↩ Devlin, J., Annual Meeting of the Association for Computational Linguistics. ↩ Brown et al. Neural Information Processing Systems. ↩ Finn, C., . ↩ Peters, M., Neumann, M., Gardner, M.,

Robotics 40

Robotics Computational Linguistics BERT Computer Vision 40