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Natural Language Processing

Discovered via Academic Publications
→ Sustained

Macro Curiosity Trend

Daily Wikipedia pageviews tracking momentum. Dashed line represents 7-day moving average.

Commercial Validation

No explicit venture capital filings detected for entities directly matching this keyword phrase yet. This may indicate an early-stage, pre-commercial developer trend.

Media Narrative

Dominant Sentiment: Generative AI Maturation

Adjacent Technical Concepts

["AI-generated research papers" "AI generate summaries" "TrialMatchAI" "AI-powered clinical trial recommendation system" "Tiiny Pocket PC" "local AI" "120-billion-parameter language model"]

Discovery Context & Origin Evidence

Raw data extracts showing exactly how engineers, founders, and researchers are utilizing the term "Natural Language Processing" in the wild.

Academic Publication

A Survey on Evaluation of Large Language Models

2,120
Citations
2024-06-30
Published
... , and how to evaluate . Firstly, we provide an overview from the perspective of evaluation tasks, encompassing general natural language processing tasks, reasoning, medical usage, ethics, education, natural and social sciences, agent applications, and other areas. Secondly, we answer the ‘where’ and ‘how’ questions by diving into the evaluation methods and benchmarks, which serve as crucial components in assessing the performance of LLMs. Then, we summarize the success and failure cases of LLMs in different tasks. Finally, we shed light on several future challeng...
Academic Publication

A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions

1,109
Citations
2025-03-31
Published
The emergence of large language models (LLMs) has marked a significant breakthrough in natural language processing (NLP), fueling a paradigm shift in information acquisition. Nevertheless, LLMs are prone to hallucination, generating plausible yet nonfactual content. This phenomenon raises significant concerns over the reliability of LLMs in real-world information retrieval (IR) systems and has attracted intensive research to detect and mitigate such hallucinations. Given the open-ended general-purpose attributes inherent to LLMs, LLM hallucinations present distinct challenges that diverge from...
Academic Publication

Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond

393
Citations
2024-07-31
Published
... is article presents a comprehensive and practical guide for practitioners and end-users working with Large Language Models (LLMs) in their downstream Natural Language Processing (NLP) tasks. We provide discussions and insights into the usage of LLMs from the perspectives of models, data, and downstream tasks. First, we offer an introduction and brief summary of current language models. Then, we discuss the influence of pre-training data, training data, and test data. Most importantly, we provide a detailed discussion about the use and non-use cases of large language models for various natural ...
Academic Publication

A Comprehensive Overview of Large Language Models

364
Citations
2025-10-31
Published
Large Language Models (LLMs) have recently demonstrated remarkable capabilities in natural language processing tasks and beyond. This success of LLMs has led to a large influx of research contributions in this direction. These works encompass diverse topics such as architectural innovations, better training strategies, context length improvements, fine-tuning, multimodal LLMs, robotics, datasets, benchmarking, efficiency, and more. With the rapid development of techniques and regular breakthroughs in LLM research, it has become considerably challenging to perceive the bigger picture of the adv...

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