AA-LCR
AA-LCR (Artificial Analysis Long Context Reasoning) is a benchmark for large language models that evaluates the ability to reason across multiple real-world documents totalling approximately 100,000 tokens per…
Natural Language Processing
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Showing 1-60 of 239 articles
AI Summary Generators
AI summary generators are software tools that use natural language processing and, increasingly, large language models to condense documents, articles, meetings, videos, emails, and other source material into…
AI search
AI search (also called AI-powered search, generative search, or an answer engine) is a class of search engine and search feature that uses large language models (LLMs) and generative AI to produce a direct
AI21 Labs
AI21 Labs is an Israeli artificial intelligence company, founded in 2017 by Yoav Shoham, Ori Goshen, and Amnon Shashua, that develops large language models (LLMs) and AI orchestration systems for enterprise…
ALBERT
ALBERT (A Lite BERT) is a parameter-efficient variant of the BERT language model developed by researchers at Google Research and the Toyota Technological Institute at Chicago (TTIC).
Agent memory
Agent memory is the set of systems that let an AI agent retain and recall information beyond a single context window, so it can carry knowledge, preferences, and experience from one interaction or session into…
Agentic Context Engineering
Agentic Context Engineering (ACE) is a framework for scalable and efficient context adaptation in large language models (LLMs) that lets an AI system improve itself by treating its own context as an evolving
Agentic RAG
Agentic RAG (agentic retrieval-augmented generation) is a retrieval-augmented generation design pattern in which one or more autonomous large language model AI agents plan, execute, and revise a sequence of…
AlpacaEval
AlpacaEval is an automatic evaluation framework for instruction-following large language models (LLMs) developed by Stanford University's Tatsu Lab
Attention Is All You Need
"Attention Is All You Need" is the 2017 research paper that introduced the transformer, the neural network architecture that underpins virtually every modern large language model.
BART (language model)
BART (an acronym for Bidirectional and Auto-Regressive Transformers) is a transformer-based encoder-decoder language model introduced by Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman…
BBQ (Bias Benchmark for QA)
BBQ (the Bias Benchmark for QA) is a hand-built evaluation dataset that measures whether a question answering (QA) language model relies on social stereotypes when it answers.
BERTScore
BERTScore is an automatic, reference-based metric for evaluating text generation that scores a candidate sentence against one or more references by comparing the contextual embeddings of their tokens rather…
BIG-Bench Hard
BIG-Bench Hard (BBH) is a suite of 23 challenging tasks drawn from the BIG-Bench benchmark, selected because they are "the [tasks] for which prior language model evaluations did not outperform the average…
BLEU (Bilingual Evaluation Understudy)
BLEU (Bilingual Evaluation Understudy) is an automatic evaluation metric that scores the quality of machine translation output by measuring how many word sequences (n-grams) it shares with one or more human…
Bag of Words
The bag of words (BoW) model is a text representation method that converts a document into a fixed-length numeric vector by counting how often each word from a predefined vocabulary appears, while discarding…
Bahdanau attention
Bahdanau attention is the first attention mechanism for neural networks, introduced in 2014 to let a sequence-to-sequence decoder soft-align to every encoder hidden state instead of relying on a single…
Bert-base-uncased model
PyTorch, TensorFlow, JAX, Rust, Core ML, Safetensors, Transformers
Bidirectional language model
A bidirectional language model is a language model that, when computing a representation for a token, conditions on both the tokens that come before it (the left context) and the tokens that come after it (the…
Bigram
A bigram (also written 2-gram) is a contiguous sequence of two adjacent elements, typically two words or two characters, taken from a body of text or speech.
BookCorpus
BookCorpus (also written BooksCorpus, and sometimes called the Toronto Book Corpus) is a text dataset built from free, self-published English-language ebooks scraped from the distribution platform Smashwords.
BoolQ
BoolQ (Boolean Questions) is a natural language processing benchmark dataset of 15,942 naturally occurring yes/no question answering examples, each pairing a real Google search query with a Wikipedia passage…
Burstiness
Burstiness is a statistical property of a text that measures how unevenly its sentence lengths, vocabulary, and per-sentence unpredictability are distributed across the document.
Byte-Pair Encoding
Byte-pair encoding (BPE) is a subword tokenization algorithm that splits text into tokens by starting from individual characters or bytes and iteratively merging the most frequent adjacent pair into a new token
C4 (Colossal Clean Crawled Corpus)
C4 (Colossal Clean Crawled Corpus) is a roughly 750 GB, cleaned, English-language web text dataset of about 365 million documents and 156 billion tokens that Google created from the April 2019 Common Crawl…
CRUXEval
CRUXEval (Code Reasoning, Understanding, and eXecution Evaluation) is a benchmark designed to measure how well large language models can reason about, understand, and mentally execute short Python programs.
CamemBERT
CamemBERT is a French monolingual language model based on the RoBERTa architecture, released in late 2019 by researchers at Inria, Facebook AI Research, and Sorbonne Université.
Candidate Sampling
Candidate sampling is a family of training-time optimization techniques used in machine learning to reduce the computational cost of models that must choose among a very large number of output classes.
Causal Language Model
A causal language model (CLM), also called an autoregressive language model or a decoder-only language model, is a language model that predicts the next token in a sequence using only the tokens that precede…
Chain of Density prompting
Chain of Density (CoD) is a prompting technique for abstractive text summarization with large language models, introduced in the 2023 paper "From Sparse to Dense: GPT-4 Summarization with Chain of Density…
Chain-of-Thought
Chain-of-thought (CoT) is a sequence of intermediate steps that a language model generates before its final answer.
Christopher Manning
Christopher Manning is an Australian-American computer scientist and computational linguist at Stanford University who is one of the most cited researchers in natural language processing and a central figure…
Chunking (information retrieval)
Chunking is the preprocessing step in document indexing and retrieval-augmented generation (RAG) systems in which a long document or corpus is split into smaller passages, called chunks, that are then embedded…
Claude (language model)
Claude is a family of large language models (LLMs) developed by Anthropic, an American artificial intelligence safety and research company.
Claude Sonnet 4.5
Claude Sonnet 4.5 is a multimodal large language model (LLM) developed by Anthropic and released on September 29, 2025, which Anthropic described at launch as "the best coding model in the world." It is a…
Cohere
Cohere is a Canadian artificial intelligence company that develops language, retrieval, speech, and multimodal models for businesses and public-sector organizations.
ColBERT
ColBERT (Contextualized Late Interaction over BERT) is a neural information retrieval model that encodes queries and documents into matrices of token-level vectors and scores them with a late-interaction…
Command R
Command R is a family of enterprise large language models from Cohere, launched in March 2024 and built specifically for retrieval-augmented generation (RAG), multi-step tool use, and grounded text generation…
Common Corpus
Common Corpus is the largest fully open, multilingual dataset for pretraining large language models, assembled and released by the French AI research lab Pleias.
Common Crawl
Common Crawl is a nonprofit 501(c)(3) organization that maintains a free, open repository of web crawl data, and it is the single largest publicly available source of text used to train large language models.
Common Pile
Common Pile v0.1 is an 8 terabyte corpus of openly licensed and public domain text, released on June 5, 2025, by EleutherAI and a consortium of more than two dozen academic and industry collaborators.
CommonsenseQA
CommonsenseQA is a multiple-choice question answering benchmark of 12,247 questions, introduced in 2019 by Alon Talmor, Jonathan Herzig, Nicholas Lourie, and Jonathan Berant
Compass (Shopee language model)
Compass is a proprietary family of large language models developed by Shopee and its parent company, Sea, for Southeast Asian languages and e-commerce tasks.
Computer-use agent
A computer-use agent (CUA) is a category of AI agent in artificial intelligence that performs tasks by directly operating a general-purpose computer's graphical user interface (GUI) the way a human does, by…
Conditional Random Field
A conditional random field (CRF) is a discriminative probabilistic model for structured prediction, used most often to assign a label to every position in an input sequence.
Context window
A context window is the finite token sequence that a language model can process for one invocation.
Contextual AI
Contextual AI is an American enterprise artificial intelligence company headquartered in Mountain View, California, that builds production-grade systems based on retrieval-augmented generation.
Conversational Models
Conversational models are computational systems designed to carry on a dialogue with human users in natural language
Coreference Resolution
Coreference resolution is the natural language processing task of finding all the expressions in a text that refer to the same entity and grouping them together.
Cosine similarity
Cosine similarity is a measure of similarity between two non-zero vectors that calculates the cosine of the angle between them, defined as the dot product of the vectors divided by the product of their…
Crash Blossom
A crash blossom is a newspaper headline that is unintentionally ambiguous because its compressed wording allows more than one valid parse, producing an unintended (and often comical) alternative reading.
Cross-encoder
A cross-encoder is a neural network architecture that scores a pair of texts by feeding them jointly into a single transformer (such as BERT) and reading out one scalar score for the pair, for example a…
DCLM (DataComp for Language Models)
DCLM, short for DataComp for Language Models (also styled DataComp-LM), is an open benchmark, dataset, and software framework, released in June 2024
DROP (Discrete Reasoning Over Paragraphs)
DROP** (Discrete Reasoning Over Paragraphs) is a reading comprehension benchmark that requires artificial intelligence systems to perform discrete reasoning operations over textual content.
DSPy
DSPy (short for Declarative Self-improving Python) is an open-source framework, developed at Stanford NLP, for programming rather than prompting large language models (LLMs).
DeBERTa
DeBERTa (Decoding-enhanced BERT with Disentangled Attention) is a family of pre-trained language models developed by Microsoft Research that improves BERT and RoBERTa with two innovations: a disentangled…
Decoding strategies
Decoding strategies are the algorithms that select output tokens from a language model's next-token probability distribution during text generation.
Deepgram
Deepgram is an American voice artificial intelligence company, founded in 2015 and headquartered in San Francisco, that builds proprietary deep learning models for speech recognition, text-to-speech synthesis…
Dense Passage Retrieval (DPR)
Dense Passage Retrieval (DPR) is a neural information retrieval method that uses a dual-encoder BERT architecture to map questions and passages into dense vectors
Direct Preference Optimization (DPO)
Direct Preference Optimization (DPO) is a method for aligning large language models with human preferences that replaces the multi-stage reinforcement learning from human feedback (RLHF) pipeline with a single…