“Seq2Seq models are widely used for tasks like machine translation and text summarization, where the input text is transformed into another text.”

“This article discusses the implementation of tokenization and word segmentation.”

“Experimental results underscore Axlerod's effectiveness, achieving an overall accuracy of 93.18% in policy retrieval tasks while reducing the average search time by 2.42 seconds.”

“Google is releasing TranslateGemma.”

“OpenAI has launched ChatGPT Translate, a standalone web translation tool that supports over 50 languages and is positioned as a direct competitor to Google Translate.”

“The author, after a week of testing, felt that the system was complete enough to consider switching from the standard Windows IME.”

“OpenAI's new standalone translation tool supports over 50 languages and features AI-powered prompt customization.”

“Specifically, natural language processing (NLP) and machine learning (ML) techniques can identify potential PTSD cases among these populations, achieving accuracy rates between 74% and 90%.”

“AI integration into data pipelines appears to be becoming more convenient, so let's give it a try.”

“Seeded topic modeling, integration with LLMs, and training on summarized data are the fresh parts of the NLP toolkit.”

“This series dissects the inner workings of LLMs, from full scratch implementations with Python and NumPy, to cutting-edge techniques used in Qwen-32B class models.”

“紙の参考書やスキャンPDFが検索できない”

“本記事のコードは、Temperature / Top-p / Top-k の挙動差を API なしで体感する最小実験です。”

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“Enterprises are sitting on vast quantities of unstructured data, from call records and video footage to customer complaint histories and supply chain signals.”

“RAG（Retrieval-Augmented Generation）は、大規模言語モデルに外部知識を与えて回答精度を高める技術です。”

“Artificial intelligence is becoming a practical layer in this process.”

“This performance disparity stems not from inherent model limitations but from a critical scarcity of high-quality training data.”

“この記事では、Amazonレビューのテキストデータを使って レビューがポジティブかネガティブかを分類する二値分類タスクを実装しました。”

“「本当に正確に論理的な推論ができているのか？」”

“投資ポートフォリオ最適化は、金融工学の中でも非常にチャレンジングかつ実務的なテーマです。”

“Are there any venues which are not in generic AI but accept NLP-focused work mostly?”

“Introducing Falcon-H1-Arabic: Pushing the Boundaries of Arabic Language AI with Hybrid Architecture”

“Latest research trends in architecture, efficiency, multimodal learning, reasoning ability, and safety.”

“Click to view original text>”

“Is this proof that the platform is biased? Hopefully not cause I use chatgpt for a lot of things”

“This article summarizes Chapter 1 of the book 'Deep Learning from Scratch 2: Natural Language Processing'.”

“This article is the second part of the series, following "Introduction to Generative AI Part 1: Basics."”

“The article quotes user comments from previous discussions on the topic, providing context for the design decisions. It also mentions the use of specific tools and libraries like PanPhon, Epitran, and Claude 3.7 Sonnet.”

“Big AI is accelerating [the ecological, meaning, and language crises] all.”

“The paper introduces a course on Ethical Aspects in NLP and its pedagogical approach, grounded in active learning through interactive sessions, hands-on activities, and "learning by teaching" methods.”

“The article's core question is: "What techniques actually work in practice to make NLP systems robust to this kind of variability?"”

“The LLM-based extractor achieves higher accuracy with fewer labeled samples, whereas the Sentence-BERT with SVM classifiers provides significantly lower latency suitable for real-time operation.”

“The proposed framework demonstrates the potential to streamline real estate transactions, strengthen stakeholder trust, and enable scalable, secure digital processes.”

“The multilingual fine-tuned mT5 baseline outperforms most other approaches including zero-shot LLM performance for most metrics.”

“I’m trying to build a strong foundation in AI/ML and I’m particularly interested in NLP. I understand that unsupervised learning plays a big role in tasks like topic modeling, word embeddings, and clustering text data. My question: Which unsupervised learning algorithms should I focus on first if my goal is to specialize in NLP?”

“WM-SAR consistently outperforms existing deep learning and LLM-based methods.”

“Simulation results show that shared-standby redundancy outperforms the conventional dedicated-active approach by up to 84%.”

“CRMS reduces latency by over 14% and improves energy efficiency compared with heuristic and search-based baselines.”

“StressRoBERTa achieves 82% F1-score, outperforming the best shared task system (79% F1) by 3 percentage points.”

“Prompt injection induces substantial changes in review scores and accept/reject decisions for English, Japanese, and Chinese injections, while Arabic injections produce little to no effect.”

“The paper introduces a new dataset, CHQ-Sum, that contains 1507 domain-expert annotated consumer health questions and corresponding summaries.”

“"Currently, the market is still in a stage of fierce competition without an absolute leader."”

“TabiBERT attains 77.58 on TabiBench, outperforming BERTurk by 1.62 points and establishing state-of-the-art on five of eight categories.”

“LENS outperforms strong baselines on standard NLP metrics and task-specific measures of symptom-severity accuracy.”

“Transformer models consistently outperform the ML and DL models for both MLE and SC tasks.”

“GPT-2 is a language model announced by OpenAI in 2019.”

“Early cases were largely linked to travel to (or contact with travelers from) Hubei Province, while later transmission was increasingly associated with social activities.”

“Domain-adapted XLM-R consistently outperforms its vanilla counterpart.”