#computational linguistics vs CS
17 related articles
·3 min
Getting Started with AI Large Models: A Complete Technical Overview from Machine Learning to Agents
A systematic overview of the evolution from AI, machine learning, deep learning, and Transformer to LLMs, covering generative AI principles, model selection, and the future of AI Agents.
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·5 min
From AI to Large Models: Understanding the Conceptual Landscape and Technological Evolution of Artificial Intelligence
Understand how AI, machine learning, deep learning, large models, and generative AI relate to each other. From Deep Blue to ChatGPT, learn how Transformer architecture gave rise to LLMs.
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·3 min
Technical Terms Getting Transliterated in Multilingual Speech Recognition? Four Solutions Explained
When Korean/Japanese ASR transliterates GitHub as 기터부 or ギットハブ, what can developers do? This article analyzes four solutions: correction dictionaries, hotword biasing, model fine-tuning, and more.
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·3 min
What If You Selected the Wrong Paper Type on the ARR Author Form? Impact and Solutions
Selected Short on the ARR Author Form but submitted a Long paper? Learn how ARR's two-form system works, why paper-level metadata is authoritative, and how to fix the error.
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·3 min
Humanities to NLP: Is a Cross-Disciplinary Master's in Computational Linguistics Worth It?
Can an English major pursue a Master's in Computational Linguistics to enter NLP? This article analyzes feasibility, program selection strategies, and practical advice for humanities-to-NLP career changers.
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·4 min
Word Embedding Learning Roadmap: A Complete Guide from word2vec to Transformer Embeddings
A systematic learning path for NLP beginners covering word2vec principles and implementation, GloVe comparison, Transformer contextual embeddings, required math foundations, and recommended resources.
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·3 min
End-to-End Speech Recognition: Which Classic Challenges Have Actually Been Solved?
Analyzing how end-to-end ASR models perform on five classic challenges: context understanding solved, noise improved but limited, accent gaps hidden by averages, code-switching nearly stagnant.
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·3 min
Linguistics to Computational Linguistics: Can You Still Find a Job in the LLM Era?
Can a linguistics background lead to a career in computational linguistics in the LLM era? This article analyzes job prospects, differentiation strategies, and future-proof career positioning.
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·3 min
Training ASR Models with Simulated Call Center Audio: Can the Gap Between Simulated and Real Data Be Bridged?
Deep dive into training ASR models with simulated call center audio: analyzing codec simulation, code-switching, and diarization bottlenecks that reveal the gap between simulated and real phone data.
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·3 min
EMNLP 2026 Launches AI Reviewing Experiment: A Turning Point for Academic Peer Review
EMNLP 2026 introduces AI-generated reviews in ACL Rolling Review, exploring LLM-assisted academic peer review. Analysis of the experiment's background, mechanics, controversies, and implications.
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·3 min
EMNLP 2026 Launches AI Reviewing Experiment: A Transformation in Academic Peer Review
EMNLP 2026 introduces AI-generated reviews in ACL Rolling Review, exploring LLM-assisted academic peer review. Analysis of the experiment's background, core content, controversies, and implications.
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·4 min
AI Large Language Models for Beginners: Core Concepts, History, and China's Model Landscape
A beginner's guide to AI large models: clarify the relationships between AI, ML, deep learning, and LLMs, trace the journey from Deep Blue to ChatGPT and DeepSeek, and explore China's model landscape.
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·2 min
GPT Live Full-Duplex Voice AI: Speak and Listen at Once, Reason and Translate
OpenAI unveils GPT Live One voice model with full-duplex conversation—AI listens and responds while you speak. Real-time reasoning, web search, multitasking, and bidirectional translation redefine voice AI.
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·2 min
Revisiting 'Stochastic Parrots': Emily Bender on LLM Understanding and the Battle Over Meaning
Emily Bender clarifies the original meaning of 'Stochastic Parrots': LLMs generate text via statistical modeling but lack true understanding of meaning. An overview of the form-vs-meaning debate and its implications for AI honesty.
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·4 min
Why Large Language Models Are Starting to 'Invent Words': The Nature of LLM Language Boundaries
Top LLMs are pushing beyond existing human vocabulary, producing neologisms and expressive distortion. This article analyzes the tension between LLM high-dimensional semantic spaces and natural language symbol systems.
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Product Reviews·2 min
Bolt.new Hands-On Review: Can Vibe Coding Actually Build Real Projects?
Hands-on review of building a retro gaming blog with Bolt.new. Deep dive into vibe coding's workflow, iteration pain points, code quality issues, and real-world applicability.
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Deep Dives·1 min
Beginner's Guide to AI Agents: Core Principles, Technical Architecture, and Application Scenarios Explained
A systematic guide to AI Agents covering core principles of perception, decision-making, and action, plus the technical stack of LLMs, tool calling, memory systems, and RAG, with real-world use cases.
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