- See Also
-
Links
- “Tag2Text: Guiding Vision-Language Model via Image Tagging”, Et Al 2023
- “ProofNet: Autoformalizing and Formally Proving Undergraduate-Level Mathematics”, Et Al 2023
- “Characterizing Attribution and Fluency Tradeoffs for Retrieval-Augmented Large Language Models”, Et Al 2023
- “In-Context Retrieval-Augmented Language Models”, Et Al 2023
- “Crawling the Internal Knowledge-Base of Language Models”, Et Al 2023
- “InPars-Light: Cost-Effective Unsupervised Training of Efficient Rankers”, Et Al 2023
- “Why Do Nearest Neighbor Language Models Work?”, Et Al 2023
- “Precise Zero-Shot Dense Retrieval without Relevance Labels”, Et Al 2022
- “One Embedder, Any Task: Instruction-Finetuned Text Embeddings (INSTRUCTOR)”, Et Al 2022
- “NPM: Nonparametric Masked Language Modeling”, Et Al 2022
- “Retrieval-Augmented Multimodal Language Modeling”, Et Al 2022
- “TART: Task-aware Retrieval With Instructions”, Et Al 2022
- “RARR: Attributed Text Generation via Post-hoc Research and Revision”, Et Al 2022
- “ReAct: Synergizing Reasoning and Acting in Language Models”, Et Al 2022
- “FiD-Light: Efficient and Effective Retrieval-Augmented Text Generation”, Et Al 2022
- “Generate rather than Retrieve (GenRead): Large Language Models Are Strong Context Generators”, Et Al 2022
- “Vote-K: Selective Annotation Makes Language Models Better Few-Shot Learners”, Et Al 2022
- “Nearest Neighbor Non-autoregressive Text Generation”, Et Al 2022
- “CorpusBrain: Pre-train a Generative Retrieval Model for Knowledge-Intensive Language Tasks”, Et Al 2022
- “NewsStories: Illustrating Articles With Visual Summaries”, Et Al 2022
- “Text-Guided Synthesis of Artistic Images With Retrieval-Augmented Diffusion Models”, Et Al 2022
- “Re2G: Retrieve, Rerank, Generate”, Et Al 2022
- “Large-Scale Retrieval for Reinforcement Learning”, Et Al 2022
- “A Neural Corpus Indexer for Document Retrieval”, Et Al 2022
- “Boosting Search Engines With Interactive Agents”, Et Al 2022
- “Hopular: Modern Hopfield Networks for Tabular Data”, Et Al 2022
- “NaturalProver: Grounded Mathematical Proof Generation With Language Models”, Et Al 2022
- “Down and Across: Introducing Crossword-Solving As a New NLP Benchmark”, Et Al 2022
- “RankGen: Improving Text Generation With Large Ranking Models”, Et Al 2022
- “Unifying Language Learning Paradigms”, Et Al 2022
- “Semi-Parametric Neural Image Synthesis”, Et Al 2022
- “KNN-Diffusion: Image Generation via Large-Scale Retrieval”, Et Al 2022
- “Language Models That Seek for Knowledge: Modular Search & Generation for Dialogue and Prompt Completion”, Et Al 2022
- “Unsupervised Vision-and-Language Pre-training via Retrieval-based Multi-Granular Alignment”, Et Al 2022
- “Retrieval Augmented Classification for Long-Tail Visual Recognition”, Et Al 2022
- “Retrieval-Augmented Reinforcement Learning”, Et Al 2022
- “Transformer Memory As a Differentiable Search Index”, Et Al 2022
- “InPars: Data Augmentation for Information Retrieval Using Large Language Models”, Et Al 2022
- “LaMDA: Language Models for Dialog Applications”, Et Al 2022
- “Memory-assisted Prompt Editing to Improve GPT-3 After Deployment”, Et Al 2022
- “A Thousand Words Are Worth More Than a Picture: Natural Language-Centric Outside-Knowledge Visual Question Answering”, Et Al 2022
- “WebGPT: Improving the Factual Accuracy of Language Models through Web Browsing”, Et Al 2021
- “WebGPT: Browser-assisted Question-answering With Human Feedback”, Et Al 2021
- “Contriever: Towards Unsupervised Dense Information Retrieval With Contrastive Learning”, Et Al 2021
- “Learning To Retrieve Prompts for In-Context Learning”, Et Al 2021
- “Large Dual Encoders Are Generalizable Retrievers”, Et Al 2021
- “Boosted Dense Retriever”, Et Al 2021
- “Spider: Learning to Retrieve Passages without Supervision”, Et Al 2021
- “You Only Need One Model for Open-domain Question Answering”, Et Al 2021
- “Improving Language Models by Retrieving from Trillions of Tokens”, Et Al 2021
- “Human Parity on CommonsenseQA: Augmenting Self-Attention With External Attention”, Et Al 2021
- “Florence: A New Foundation Model for Computer Vision”, Et Al 2021
- “LiT: Zero-Shot Transfer With Locked-image Text Tuning”, Et Al 2021
- “HTCN: Harmonious Text Colorization Network for Visual-Textual Presentation Design”, Et Al 2021
- “CLOOB: Modern Hopfield Networks With InfoLOOB Outperform CLIP”, Et Al 2021
- “Memorizing Transformers”, Et Al 2021
- “One Loss for All: Deep Hashing With a Single Cosine Similarity Based Learning Objective”, Et Al 2021
- “SPLADE V2: Sparse Lexical and Expansion Model for Information Retrieval”, Et Al 2021
- “EfficientCLIP: Efficient Cross-Modal Pre-training by Ensemble Confident Learning and Language Modeling”, Et Al 2021
- “Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models”, Et Al 2021
- “Contrastive Language-Image Pre-training for the Italian Language”, Et Al 2021
- “Billion-Scale Pretraining With Vision Transformers for Multi-Task Visual Representations”, Et Al 2021
- “Internet-Augmented Dialogue Generation”, Et Al 2021
- “CLIP2Video: Mastering Video-Text Retrieval via Image CLIP”, Et Al 2021
- “A Multi-Level Attention Model for Evidence-Based Fact Checking”, Et Al 2021
- “Towards Mental Time Travel: a Hierarchical Memory for Reinforcement Learning Agents”, Et Al 2021
- “RetGen: A Joint Framework for Retrieval and Grounded Text Generation Modeling”, Et Al 2021
- “Not All Memories Are Created Equal: Learning to Forget by Expiring”, Et Al 2021
- “Rethinking Search: Making Domain Experts out of Dilettantes”, Et Al 2021
- “SimCSE: Simple Contrastive Learning of Sentence Embeddings”, Et Al 2021
- “BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models”, Et Al 2021
- “Retrieval Augmentation Reduces Hallucination in Conversation”, Et Al 2021
- “NaturalProofs: Mathematical Theorem Proving in Natural Language”, Et Al 2021
- “China’s GPT-3? BAAI Introduces Superscale Intelligence Model ‘Wu Dao 1.0’: The Beijing Academy of Artificial Intelligence (BAAI) Releases Wu Dao 1.0, China’s First Large-scale Pretraining Model.”, 2021
- “Get Your Vitamin C! Robust Fact Verification With Contrastive Evidence (VitaminC)”, Et Al 2021
- “ALIGN: Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision”, Et Al 2021
- “Decoupling the Role of Data, Attention, and Losses in Multimodal Transformers”, Et Al 2021
- “Scaling Deep Contrastive Learning Batch Size under Memory Limited Setup”, Et Al 2021
- “Current Limitations of Language Models: What You Need Is Retrieval”, 2020
- “Leveraging Passage Retrieval With Generative Models for Open Domain Question Answering”, 2020
- “Pre-training via Paraphrasing”, Et Al 2020
- “Memory Transformer”, Et Al 2020
- “M3P: Learning Universal Representations via Multitask Multilingual Multimodal Pre-training”, Et Al 2020
- “Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks”, Et Al 2020
- “Dense Passage Retrieval for Open-Domain Question Answering”, Et Al 2020
- “Learning to Scale Multilingual Representations for Vision-Language Tasks”, Et Al 2020
- “How Much Knowledge Can You Pack Into the Parameters of a Language Model?”, Et Al 2020
- “REALM: Retrieval-Augmented Language Model Pre-Training”, Et Al 2020
- “MULE: Multimodal Universal Language Embedding”, Et Al 2019
- “Language Models As Knowledge Bases?”, Et Al 2019
- “Metalearned Neural Memory”, Et Al 2019
- “ELI5: Long Form Question Answering”, Et Al 2019
- “Large Memory Layers With Product Keys”, Et Al 2019
- “OK-VQA: A Visual Question Answering Benchmark Requiring External Knowledge”, Et Al 2019
- “Top-K Off-Policy Correction for a REINFORCE Recommender System”, Et Al 2018
- “FEVER: a Large-scale Dataset for Fact Extraction and VERification”, Et Al 2018
- “Towards Deep Modeling of Music Semantics Using EEG Regularizers”, Et Al 2017
- “Learning to Organize Knowledge and Answer Questions With N-Gram Machines”, Et Al 2017
- “Seq2SQL: Generating Structured Queries from Natural Language Using Reinforcement Learning”, Et Al 2017
- “Bolt: Accelerated Data Mining With Fast Vector Compression”, 2017
- “Neural Episodic Control”, Et Al 2017
- “Improving Neural Language Models With a Continuous Cache”, Et Al 2016
- “Scaling Memory-Augmented Neural Networks With Sparse Reads and Writes”, Et Al 2016
- “Deep Neural Networks for YouTube Recommendations”, Et Al 2016
- “One-shot Learning With Memory-Augmented Neural Networks”, Et Al 2016
- “PlaNet—Photo Geolocation With Convolutional Neural Networks”, Et Al 2016
- “Learning to Win by Reading Manuals in a Monte-Carlo Framework”, Et Al 2014
- “This Week’s Citation Classic: Nearest Neighbor Pattern Classification”, 1982
- “Nearest Neighbor Pattern Classification”, 1967
- “ANN-Benchmarks Is a Benchmarking Environment for Approximate Nearest Neighbor Algorithms Search. This Website Contains the Current Benchmarking Results. Please Visit Https://github.com/erikbern/ann-benchmarks/ to Get an Overview over Evaluated Data Sets and Algorithms. Make a Pull Request on Github to Add Your Own Code or Improvements to the Benchmarking System.”
- “This Anime Does Not Exist, Search: This Notebook Uses the Precomputed CLIP Feature Vectors for 100k Images from TADNE”
- Wikipedia
- Miscellaneous
- Link Bibliography
See Also
Links
“Tag2Text: Guiding Vision-Language Model via Image Tagging”, Et Al 2023
“Tag2Text: Guiding Vision-Language Model via Image Tagging”, 2023-03-10 ( ; similar)
“ProofNet: Autoformalizing and Formally Proving Undergraduate-Level Mathematics”, Et Al 2023
“ProofNet: Autoformalizing and Formally Proving Undergraduate-Level Mathematics”, 2023-02-24 ( ; similar; bibliography)
“Characterizing Attribution and Fluency Tradeoffs for Retrieval-Augmented Large Language Models”, Et Al 2023
“Characterizing Attribution and Fluency Tradeoffs for Retrieval-Augmented Large Language Models”, 2023-02-11 ( ; similar)
“In-Context Retrieval-Augmented Language Models”, Et Al 2023
“In-Context Retrieval-Augmented Language Models”, 2023-01-31 ( ; similar)
“Crawling the Internal Knowledge-Base of Language Models”, Et Al 2023
“Crawling the Internal Knowledge-Base of Language Models”, 2023-01-30 ( ; similar)
“InPars-Light: Cost-Effective Unsupervised Training of Efficient Rankers”, Et Al 2023
“InPars-Light: Cost-Effective Unsupervised Training of Efficient Rankers”, 2023-01-08 ( ; similar)
“Why Do Nearest Neighbor Language Models Work?”, Et Al 2023
“Why do Nearest Neighbor Language Models Work?”, 2023-01-07 ( ; similar)
“Precise Zero-Shot Dense Retrieval without Relevance Labels”, Et Al 2022
“Precise Zero-Shot Dense Retrieval without Relevance Labels”, 2022-12-20 ( ; similar; bibliography)
“One Embedder, Any Task: Instruction-Finetuned Text Embeddings (INSTRUCTOR)”, Et Al 2022
“One Embedder, Any Task: Instruction-Finetuned Text Embeddings (INSTRUCTOR)”, 2022-12-19 ( ; similar; bibliography)
“NPM: Nonparametric Masked Language Modeling”, Et Al 2022
“NPM: Nonparametric Masked Language Modeling”, 2022-12-02 ( ; similar; bibliography)
“Retrieval-Augmented Multimodal Language Modeling”, Et Al 2022
“Retrieval-Augmented Multimodal Language Modeling”, 2022-11-22 ( ; similar; bibliography)
“TART: Task-aware Retrieval With Instructions”, Et Al 2022
“TART: Task-aware Retrieval with Instructions”, 2022-11-16 ( ; similar)
“RARR: Attributed Text Generation via Post-hoc Research and Revision”, Et Al 2022
“RARR: Attributed Text Generation via Post-hoc Research and Revision”, 2022-10-17 ( ; similar; bibliography)
“ReAct: Synergizing Reasoning and Acting in Language Models”, Et Al 2022
“ReAct: Synergizing Reasoning and Acting in Language Models”, 2022-10-06 ( ; similar)
“FiD-Light: Efficient and Effective Retrieval-Augmented Text Generation”, Et Al 2022
“FiD-Light: Efficient and Effective Retrieval-Augmented Text Generation”, 2022-09-28 ( ; similar)
“Generate rather than Retrieve (GenRead): Large Language Models Are Strong Context Generators”, Et Al 2022
“Generate rather than Retrieve (GenRead): Large Language Models are Strong Context Generators”, 2022-09-21 ( ; similar)
“Vote-K: Selective Annotation Makes Language Models Better Few-Shot Learners”, Et Al 2022
“Vote-K: Selective Annotation Makes Language Models Better Few-Shot Learners”, 2022-09-05 ( ; similar; bibliography)
“Nearest Neighbor Non-autoregressive Text Generation”, Et Al 2022
“Nearest Neighbor Non-autoregressive Text Generation”, 2022-08-26 ( ; similar)
“CorpusBrain: Pre-train a Generative Retrieval Model for Knowledge-Intensive Language Tasks”, Et Al 2022
“CorpusBrain: Pre-train a Generative Retrieval Model for Knowledge-Intensive Language Tasks”, 2022-08-16 ( ; similar)
“NewsStories: Illustrating Articles With Visual Summaries”, Et Al 2022
“NewsStories: Illustrating articles with visual summaries”, 2022-07-26 ( ; similar; bibliography)
“Text-Guided Synthesis of Artistic Images With Retrieval-Augmented Diffusion Models”, Et Al 2022
“Text-Guided Synthesis of Artistic Images with Retrieval-Augmented Diffusion Models”, 2022-07-26 ( ; backlinks; similar)
“Re2G: Retrieve, Rerank, Generate”, Et Al 2022
“Re2G: Retrieve, Rerank, Generate”, 2022-07-13 ( ; similar; bibliography)
“Large-Scale Retrieval for Reinforcement Learning”, Et Al 2022
“Large-Scale Retrieval for Reinforcement Learning”, 2022-06-10 ( ; similar; bibliography)
“A Neural Corpus Indexer for Document Retrieval”, Et Al 2022
“A Neural Corpus Indexer for Document Retrieval”, 2022-06-06 ( ; similar)
“Boosting Search Engines With Interactive Agents”, Et Al 2022
“Boosting Search Engines with Interactive Agents”, 2022-06-04 ( ; similar; bibliography)
“Hopular: Modern Hopfield Networks for Tabular Data”, Et Al 2022
“Hopular: Modern Hopfield Networks for Tabular Data”, 2022-06-01 ( ; similar)
“NaturalProver: Grounded Mathematical Proof Generation With Language Models”, Et Al 2022
“NaturalProver: Grounded Mathematical Proof Generation with Language Models”, 2022-05-25 ( ; similar; bibliography)
“Down and Across: Introducing Crossword-Solving As a New NLP Benchmark”, Et Al 2022
“Down and Across: Introducing Crossword-Solving as a New NLP Benchmark”, 2022-05-20 ( ; similar)
“RankGen: Improving Text Generation With Large Ranking Models”, Et Al 2022
“RankGen: Improving Text Generation with Large Ranking Models”, 2022-05-19 ( ; similar)
“Unifying Language Learning Paradigms”, Et Al 2022
“Unifying Language Learning Paradigms”, 2022-05-10 ( ; similar; bibliography)
“Semi-Parametric Neural Image Synthesis”, Et Al 2022
“Semi-Parametric Neural Image Synthesis”, 2022-04-25 ( ; similar)
“KNN-Diffusion: Image Generation via Large-Scale Retrieval”, Et Al 2022
“KNN-Diffusion: Image Generation via Large-Scale Retrieval”, 2022-04-06 ( ; similar)
“Language Models That Seek for Knowledge: Modular Search & Generation for Dialogue and Prompt Completion”, Et Al 2022
“Language Models that Seek for Knowledge: Modular Search & Generation for Dialogue and Prompt Completion”, 2022-03-24 ( ; similar; bibliography)
“Unsupervised Vision-and-Language Pre-training via Retrieval-based Multi-Granular Alignment”, Et Al 2022
“Unsupervised Vision-and-Language Pre-training via Retrieval-based Multi-Granular Alignment”, 2022-03-01 ( ; similar)
“Retrieval Augmented Classification for Long-Tail Visual Recognition”, Et Al 2022
“Retrieval Augmented Classification for Long-Tail Visual Recognition”, 2022-02-22 (similar)
“Retrieval-Augmented Reinforcement Learning”, Et Al 2022
“Retrieval-Augmented Reinforcement Learning”, 2022-02-17 ( ; similar)
“Transformer Memory As a Differentiable Search Index”, Et Al 2022
“Transformer Memory as a Differentiable Search Index”, 2022-02-14 (similar)
“InPars: Data Augmentation for Information Retrieval Using Large Language Models”, Et Al 2022
“InPars: Data Augmentation for Information Retrieval using Large Language Models”, 2022-02-10 ( ; backlinks; similar)
“LaMDA: Language Models for Dialog Applications”, Et Al 2022
“LaMDA: Language Models for Dialog Applications”, 2022-01-20 ( ; similar)
“Memory-assisted Prompt Editing to Improve GPT-3 After Deployment”, Et Al 2022
“Memory-assisted prompt editing to improve GPT-3 after deployment”, 2022-01-16 ( ; similar)
“A Thousand Words Are Worth More Than a Picture: Natural Language-Centric Outside-Knowledge Visual Question Answering”, Et Al 2022
“A Thousand Words Are Worth More Than a Picture: Natural Language-Centric Outside-Knowledge Visual Question Answering”, 2022-01-14 (similar)
“WebGPT: Improving the Factual Accuracy of Language Models through Web Browsing”, Et Al 2021
“WebGPT: Improving the factual accuracy of language models through web browsing”, 2021-12-16 ( ; similar; bibliography)
“WebGPT: Browser-assisted Question-answering With Human Feedback”, Et Al 2021
“WebGPT: Browser-assisted question-answering with human feedback”, 2021-12-16 ( ; similar; bibliography)
“Contriever: Towards Unsupervised Dense Information Retrieval With Contrastive Learning”, Et Al 2021
“Contriever: Towards Unsupervised Dense Information Retrieval with Contrastive Learning”, 2021-12-16 (similar; bibliography)
“Learning To Retrieve Prompts for In-Context Learning”, Et Al 2021
“Learning To Retrieve Prompts for In-Context Learning”, 2021-12-16 ( ; similar)
“Large Dual Encoders Are Generalizable Retrievers”, Et Al 2021
“Large Dual Encoders Are Generalizable Retrievers”, 2021-12-15 ( ; similar; bibliography)
“Boosted Dense Retriever”, Et Al 2021
“Boosted Dense Retriever”, 2021-12-14 ( ; similar)
“Spider: Learning to Retrieve Passages without Supervision”, Et Al 2021
“Spider: Learning to Retrieve Passages without Supervision”, 2021-12-14 (similar)
“You Only Need One Model for Open-domain Question Answering”, Et Al 2021
“You Only Need One Model for Open-domain Question Answering”, 2021-12-14 ( ; similar)
“Improving Language Models by Retrieving from Trillions of Tokens”, Et Al 2021
“Improving language models by retrieving from trillions of tokens”, 2021-12-08 ( ; similar; bibliography)
“Human Parity on CommonsenseQA: Augmenting Self-Attention With External Attention”, Et Al 2021
“Human Parity on CommonsenseQA: Augmenting Self-Attention with External Attention”, 2021-12-06 ( ; similar)
“Florence: A New Foundation Model for Computer Vision”, Et Al 2021
“Florence: A New Foundation Model for Computer Vision”, 2021-11-22 ( ; similar; bibliography)
“LiT: Zero-Shot Transfer With Locked-image Text Tuning”, Et Al 2021
“LiT: Zero-Shot Transfer with Locked-image Text Tuning”, 2021-11-15 ( ; similar; bibliography)
“HTCN: Harmonious Text Colorization Network for Visual-Textual Presentation Design”, Et Al 2021
“HTCN: Harmonious Text Colorization Network for Visual-Textual Presentation Design”, 2021-10-22 ( ; similar)
“CLOOB: Modern Hopfield Networks With InfoLOOB Outperform CLIP”, Et Al 2021
“CLOOB: Modern Hopfield Networks with InfoLOOB Outperform CLIP”, 2021-10-05 ( ; similar; bibliography)
“Memorizing Transformers”, Et Al 2021
“Memorizing Transformers”, 2021-10-05 ( ; similar; bibliography)
“One Loss for All: Deep Hashing With a Single Cosine Similarity Based Learning Objective”, Et Al 2021
“One Loss for All: Deep Hashing with a Single Cosine Similarity based Learning Objective”, 2021-09-29 (similar)
“SPLADE V2: Sparse Lexical and Expansion Model for Information Retrieval”, Et Al 2021
“SPLADE v2: Sparse Lexical and Expansion Model for Information Retrieval”, 2021-09-21 ( ; similar)
“EfficientCLIP: Efficient Cross-Modal Pre-training by Ensemble Confident Learning and Language Modeling”, Et Al 2021
“EfficientCLIP: Efficient Cross-Modal Pre-training by Ensemble Confident Learning and Language Modeling”, 2021-09-10 ( ; similar)
“Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models”, Et Al 2021
“Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models”, 2021-08-19 ( ; similar; bibliography)
“Contrastive Language-Image Pre-training for the Italian Language”, Et Al 2021
“Contrastive Language-Image Pre-training for the Italian Language”, 2021-08-19 ( ; similar)
“Billion-Scale Pretraining With Vision Transformers for Multi-Task Visual Representations”, Et Al 2021
“Billion-Scale Pretraining with Vision Transformers for Multi-Task Visual Representations”, 2021-08-12 ( ; similar)
“Internet-Augmented Dialogue Generation”, Et Al 2021
“Internet-Augmented Dialogue Generation”, 2021-07-15 ( ; similar; bibliography)
“CLIP2Video: Mastering Video-Text Retrieval via Image CLIP”, Et Al 2021
“CLIP2Video: Mastering Video-Text Retrieval via Image CLIP”, 2021-06-21 ( ; similar; bibliography)
“A Multi-Level Attention Model for Evidence-Based Fact Checking”, Et Al 2021
“A Multi-Level Attention Model for Evidence-Based Fact Checking”, 2021-06-02 ( ; backlinks; similar)
“Towards Mental Time Travel: a Hierarchical Memory for Reinforcement Learning Agents”, Et Al 2021
“Towards mental time travel: a hierarchical memory for reinforcement learning agents”, 2021-05-28 ( ; similar)
“RetGen: A Joint Framework for Retrieval and Grounded Text Generation Modeling”, Et Al 2021
“RetGen: A Joint framework for Retrieval and Grounded Text Generation Modeling”, 2021-05-14 ( ; similar)
“Not All Memories Are Created Equal: Learning to Forget by Expiring”, Et Al 2021
“Not All Memories are Created Equal: Learning to Forget by Expiring”, 2021-05-13 ( ; similar)
“Rethinking Search: Making Domain Experts out of Dilettantes”, Et Al 2021
“Rethinking Search: Making Domain Experts out of Dilettantes”, 2021-05-05 (similar)
“SimCSE: Simple Contrastive Learning of Sentence Embeddings”, Et Al 2021
“SimCSE: Simple Contrastive Learning of Sentence Embeddings”, 2021-04-18 ( ; backlinks; similar)
“BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models”, Et Al 2021
“BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models”, 2021-04-17 (backlinks; similar)
“Retrieval Augmentation Reduces Hallucination in Conversation”, Et Al 2021
“Retrieval Augmentation Reduces Hallucination in Conversation”, 2021-04-15 ( ; similar; bibliography)
“NaturalProofs: Mathematical Theorem Proving in Natural Language”, Et Al 2021
“NaturalProofs: Mathematical Theorem Proving in Natural Language”, 2021-03-24 ( ; backlinks; similar)
“China’s GPT-3? BAAI Introduces Superscale Intelligence Model ‘Wu Dao 1.0’: The Beijing Academy of Artificial Intelligence (BAAI) Releases Wu Dao 1.0, China’s First Large-scale Pretraining Model.”, 2021
“China’s GPT-3? BAAI Introduces Superscale Intelligence Model ‘Wu Dao 1.0’: The Beijing Academy of Artificial Intelligence (BAAI) releases Wu Dao 1.0, China’s first large-scale pretraining model.”, 2021-03-23 ( ; similar; bibliography)
“Get Your Vitamin C! Robust Fact Verification With Contrastive Evidence (VitaminC)”, Et Al 2021
“Get Your Vitamin C! Robust Fact Verification with Contrastive Evidence (VitaminC)”, 2021-03-15 ( ; backlinks; similar)
“ALIGN: Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision”, Et Al 2021
“ALIGN: Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision”, 2021-02-11 ( ; similar; bibliography)
“Decoupling the Role of Data, Attention, and Losses in Multimodal Transformers”, Et Al 2021
“Decoupling the Role of Data, Attention, and Losses in Multimodal Transformers”, 2021-01-31 ( ; similar)
“Scaling Deep Contrastive Learning Batch Size under Memory Limited Setup”, Et Al 2021
“Scaling Deep Contrastive Learning Batch Size under Memory Limited Setup”, 2021-01-18 (similar)
“Current Limitations of Language Models: What You Need Is Retrieval”, 2020
“Current Limitations of Language Models: What You Need is Retrieval”, 2020-09-15 ( ; backlinks; similar)
“Leveraging Passage Retrieval With Generative Models for Open Domain Question Answering”, 2020
“Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering”, 2020-07-02 ( ; similar)
“Pre-training via Paraphrasing”, Et Al 2020
“Pre-training via Paraphrasing”, 2020-06-26 ( ; similar)
“Memory Transformer”, Et Al 2020
“Memory Transformer”, 2020-06-20 ( ; backlinks; similar)
“M3P: Learning Universal Representations via Multitask Multilingual Multimodal Pre-training”, Et Al 2020
“M3P: Learning Universal Representations via Multitask Multilingual Multimodal Pre-training”, 2020-06-04 ( ; similar)
“Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks”, Et Al 2020
“Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks”, 2020-05-22 ( ; similar)
“Dense Passage Retrieval for Open-Domain Question Answering”, Et Al 2020
“Dense Passage Retrieval for Open-Domain Question Answering”, 2020-04-10 (similar)
“Learning to Scale Multilingual Representations for Vision-Language Tasks”, Et Al 2020
“Learning to Scale Multilingual Representations for Vision-Language Tasks”, 2020-04-09 ( ; similar)
“How Much Knowledge Can You Pack Into the Parameters of a Language Model?”, Et Al 2020
“How Much Knowledge Can You Pack Into the Parameters of a Language Model?”, 2020-02-10 ( ; similar)
“REALM: Retrieval-Augmented Language Model Pre-Training”, Et Al 2020
“REALM: Retrieval-Augmented Language Model Pre-Training”, 2020-02-10 ( ; similar)
“MULE: Multimodal Universal Language Embedding”, Et Al 2019
“MULE: Multimodal Universal Language Embedding”, 2019-09-08 ( ; similar)
“Language Models As Knowledge Bases?”, Et Al 2019
“Language Models as Knowledge Bases?”, 2019-09-03 ( ; similar)
“Metalearned Neural Memory”, Et Al 2019
“Metalearned Neural Memory”, 2019-07-23 ( ; similar)
“ELI5: Long Form Question Answering”, Et Al 2019
“ELI5: Long Form Question Answering”, 2019-07-22 (similar)
“Large Memory Layers With Product Keys”, Et Al 2019
“Large Memory Layers with Product Keys”, 2019-07-10 ( ; similar)
“OK-VQA: A Visual Question Answering Benchmark Requiring External Knowledge”, Et Al 2019
“OK-VQA: A Visual Question Answering Benchmark Requiring External Knowledge”, 2019-05-31 ( ; similar)
“Top-K Off-Policy Correction for a REINFORCE Recommender System”, Et Al 2018
“Top-K Off-Policy Correction for a REINFORCE Recommender System”, 2018-12-06 ( ; similar)
“FEVER: a Large-scale Dataset for Fact Extraction and VERification”, Et Al 2018
“FEVER: a large-scale dataset for Fact Extraction and VERification”, 2018-03-14 ( ; backlinks; similar)
“Towards Deep Modeling of Music Semantics Using EEG Regularizers”, Et Al 2017
“Towards Deep Modeling of Music Semantics using EEG Regularizers”, 2017-12-14 ( ; similar)
“Learning to Organize Knowledge and Answer Questions With N-Gram Machines”, Et Al 2017
“Learning to Organize Knowledge and Answer Questions with N-Gram Machines”, 2017-11-17 ( ; backlinks; similar)
“Seq2SQL: Generating Structured Queries from Natural Language Using Reinforcement Learning”, Et Al 2017
“Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning”, 2017-08-31 ( ; backlinks; similar)
“Bolt: Accelerated Data Mining With Fast Vector Compression”, 2017
“Bolt: Accelerated Data Mining with Fast Vector Compression”, 2017-06-30 ( ; similar)
“Neural Episodic Control”, Et Al 2017
“Neural Episodic Control”, 2017-03-06 ( ; similar)
“Improving Neural Language Models With a Continuous Cache”, Et Al 2016
“Improving Neural Language Models with a Continuous Cache”, 2016-12-13 ( ; similar)
“Scaling Memory-Augmented Neural Networks With Sparse Reads and Writes”, Et Al 2016
“Scaling Memory-Augmented Neural Networks with Sparse Reads and Writes”, 2016-10-27 (similar)
“Deep Neural Networks for YouTube Recommendations”, Et Al 2016
“Deep Neural Networks for YouTube Recommendations”, 2016-09-15 ( ; similar)
“One-shot Learning With Memory-Augmented Neural Networks”, Et Al 2016
“One-shot Learning with Memory-Augmented Neural Networks”, 2016-05-19 ( ; similar)
“PlaNet—Photo Geolocation With Convolutional Neural Networks”, Et Al 2016
“PlaNet—Photo Geolocation with Convolutional Neural Networks”, 2016-02-17 ( ; similar)
“This Week’s Citation Classic: Nearest Neighbor Pattern Classification”, 1982
“This Week's Citation Classic: Nearest Neighbor Pattern Classification”, 1982-03-05 ( ; backlinks; similar; bibliography)
“Nearest Neighbor Pattern Classification”, 1967
“Nearest neighbor pattern classification”, 1967-01 ( ; backlinks; similar)
“ANN-Benchmarks Is a Benchmarking Environment for Approximate Nearest Neighbor Algorithms Search. This Website Contains the Current Benchmarking Results. Please Visit Https://github.com/erikbern/ann-benchmarks/ to Get an Overview over Evaluated Data Sets and Algorithms. Make a Pull Request on Github to Add Your Own Code or Improvements to the Benchmarking System.”
“ANN-Benchmarks is a benchmarking environment for approximate nearest neighbor algorithms search. This website contains the current benchmarking results. Please visit https://github.com/erikbern/ann-benchmarks/ to get an overview over evaluated data sets and algorithms. Make a pull request on Github to add your own code or improvements to the benchmarking system.” (backlinks)
“This Anime Does Not Exist, Search: This Notebook Uses the Precomputed CLIP Feature Vectors for 100k Images from TADNE”
Wikipedia
Miscellaneous
Link Bibliography
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https://arxiv.org/abs/2302.12433
: “ProofNet: Autoformalizing and Formally Proving Undergraduate-Level Mathematics”, Zhangir Azerbayev, Bartosz Piotrowski, Hailey Schoelkopf, Edward W. Ayers, Dragomir Radev, Jeremy Avigad: -
https://arxiv.org/abs/2212.10496
: “Precise Zero-Shot Dense Retrieval without Relevance Labels”, Luyu Gao, Xueguang Ma, Jimmy Lin, Jamie Callan: -
https://arxiv.org/abs/2212.09741
: “One Embedder, Any Task: Instruction-Finetuned Text Embeddings (INSTRUCTOR)”, : -
https://arxiv.org/abs/2212.01349#facebook
: “NPM: Nonparametric Masked Language Modeling”, Sewon Min, Weijia Shi, Mike Lewis, Xilun Chen, Wen-tau Yih, Hannaneh Hajishirzi, Luke Zettlemoyer: -
https://arxiv.org/abs/2211.12561#facebook
: “Retrieval-Augmented Multimodal Language Modeling”, : -
https://arxiv.org/abs/2210.08726#google
: “RARR: Attributed Text Generation via Post-hoc Research and Revision”, : -
https://arxiv.org/abs/2209.01975
: “Vote-<em>K< / em>: Selective Annotation Makes Language Models Better Few-Shot Learners”, : -
https://arxiv.org/abs/2207.13061
: “NewsStories: Illustrating Articles With Visual Summaries”, Reuben Tan, Bryan A. Plummer, Kate Saenko, J. P. Lewis, Avneesh Sud, Thomas Leung: -
https://arxiv.org/abs/2207.06300#ibm
: “Re2G: Retrieve, Rerank, Generate”, Michael Glass, Gaetano Rossiello, Md Faisal Mahbub Chowdhury, Ankita Rajaram Naik, Pengshan Cai, Alfio Gliozzo: -
https://arxiv.org/abs/2206.05314#deepmind
: “Large-Scale Retrieval for Reinforcement Learning”, Peter C. Humphreys, Arthur Guez, Olivier Tieleman, Laurent Sifre, Théophane Weber, Timothy Lillicrap: -
https://openreview.net/forum?id=0ZbPmmB61g#google
: “Boosting Search Engines With Interactive Agents”, : -
https://arxiv.org/abs/2205.12910#allen
: “NaturalProver: Grounded Mathematical Proof Generation With Language Models”, Sean Welleck, Jiacheng Liu, Ximing Lu, Hannaneh Hajishirzi, Yejin Choi: -
https://arxiv.org/abs/2205.05131#google
: “Unifying Language Learning Paradigms”, : -
https://arxiv.org/abs/2203.13224#facebook
: “Language Models That Seek for Knowledge: Modular Search & Generation for Dialogue and Prompt Completion”, Kurt Shuster, Mojtaba Komeili, Leonard Adolphs, Stephen Roller, Arthur Szlam, Jason Weston: -
https://openai.com/blog/webgpt/
: “WebGPT: Improving the Factual Accuracy of Language Models through Web Browsing”, Jacob Hilton, Suchir Balaji, Reiichiro Nakano, John Schulman: -
https://arxiv.org/abs/2112.09332#openai
: “WebGPT: Browser-assisted Question-answering With Human Feedback”, : -
https://arxiv.org/abs/2112.09118#facebook
: “Contriever: Towards Unsupervised Dense Information Retrieval With Contrastive Learning”, Gautier Izacard, Mathilde Caron, Lucas Hosseini, Sebastian Riedel, Piotr Bojanowski, Arm, Joulin, Edouard Grave: -
https://arxiv.org/abs/2112.07899#google
: “Large Dual Encoders Are Generalizable Retrievers”, : -
https://arxiv.org/abs/2112.04426#deepmind
: “Improving Language Models by Retrieving from Trillions of Tokens”, : -
https://arxiv.org/abs/2111.11432#microsoft
: “Florence: A New Foundation Model for Computer Vision”, : -
https://arxiv.org/abs/2111.07991#google
: “LiT: Zero-Shot Transfer With Locked-image Text Tuning”, Xiaohua Zhai, Xiao Wang, Basil Mustafa, Andreas Steiner, Daniel Keysers, Alexander Kolesnikov, Lucas Beyer: -
https://openreview.net/forum?id=qw674L9PfQE
: “CLOOB: Modern Hopfield Networks With InfoLOOB Outperform CLIP”, : -
https://arxiv.org/abs/2203.08913#google
: “Memorizing Transformers”, Yuhuai Wu, Markus Norman Rabe, DeLesley Hutchins, Christian Szegedy: -
https://arxiv.org/abs/2108.08877#google
: “Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models”, Jianmo Ni, Gustavo Hernández Ábrego, Noah Constant, Ji Ma, Keith B. Hall, Daniel Cer, Yinfei Yang: -
https://arxiv.org/abs/2107.07566#facebook
: “Internet-Augmented Dialogue Generation”, Mojtaba Komeili, Kurt Shuster, Jason Weston: -
https://arxiv.org/abs/2106.11097
: “CLIP2Video: Mastering Video-Text Retrieval via Image CLIP”, Han Fang, Pengfei Xiong, Luhui Xu, Yu Chen: -
https://arxiv.org/abs/2104.07567#facebook
: “Retrieval Augmentation Reduces Hallucination in Conversation”, Kurt Shuster, Spencer Poff, Moya Chen, Douwe Kiela, Jason Weston: -
https://syncedreview.com/2021/03/23/chinas-gpt-3-baai-introduces-superscale-intelligence-model-wu-dao-1-0/#baai
: “China’s GPT-3? BAAI Introduces Superscale Intelligence Model ‘Wu Dao 1.0’: The Beijing Academy of Artificial Intelligence (BAAI) Releases Wu Dao 1.0, China’s First Large-scale Pretraining Model.”, Synced: -
https://arxiv.org/abs/2102.05918#google
: “ALIGN: Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision”, : -
1982-cover.pdf
: “This Week's Citation Classic: Nearest Neighbor Pattern Classification”, Thomas M. Cover: