Enhancing Large Language Models with Retrieval Augmented Generation.

• Unlimiformer: Long-Range Transformers with Unlimited Length Input. [2023.10.30] [Arxiv]

• Active Retrieval Augmented Generation. [2023.10.22] [Arxiv]

• Understanding Retrieval Augmentation for Long-Form Question Answering. [2023.10.18] [Arxiv]

• Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection. [2023.10.17][Arxiv][Code]

• RaLLe: A Framework for Developing and Evaluating Retrieval-Augmented Large Language Models. [2023.10.16] [Arxiv]

• RegaVAE: A Retrieval-Augmented Gaussian Mixture Variational Auto-Encoder for Language Modeling. [2023.10.16] [Arxiv]

• Chameleon: a Heterogeneous and Disaggregated Accelerator System for Retrieval-Augmented Language Models. [2023.10.15] [Arxiv]

• FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation. [2023.10.11] [Arxiv]

• InstructRetro: Instruction Tuning post Retrieval-Augmented Pretraining. [2023.10.11] [Arxiv]

• Goodtriever: Adaptive Toxicity Mitigation with Retrieval-augmented Models. [2023.10.11] [Arxiv]

• Retrieve Anything To Augment Large Language Models. [2023.10.11] [Arxiv]

• VerifAI: Verified Generative AI. [2023.10.11][Arxiv]

• Crossing the Threshold: Idiomatic Machine Translation through Retrieval Augmentation and Loss Weighting. [2023.10.10] [Arxiv]

• RAUCG: Retrieval-Augmented Unsupervised Counter Narrative Generation for Hate Speech. [2023.10.09] [Arxiv]

• GROVE: A Retrieval-augmented Complex Story Generation Framework with A Forest of Evidence. [2023.10.08] [Arxiv]

• Augmented Embeddings for Custom Retrievals. [2023.10.08] [Arxiv]

• Retrieval-Generation Synergy Augmented Large Language Models. [2023.10.08] [Arxiv]

• Self-Knowledge Guided Retrieval Augmentation for Large Language Models. [2023.10.08] [Arxiv]

• RA-DIT: Retrieval-Augmented Dual Instruction Tuning. [2023.10.08] [Arxiv]

• Retrieving Multimodal Information for Augmented Generation: A Survey. [2023.10.07] [Arxiv]

• RECOMP: Improving Retrieval-Augmented LMs with Compression and Selective Augmentation. [2023.10.06] [Arxiv]

• Keyword Augmented Retrieval: Novel framework for Information Retrieval integrated with speech interface. [2023.10.06] [Arxiv]

• Enhancing Financial Sentiment Analysis via Retrieval Augmented Large Language Models. [2023.10.06] [Arxiv]

• Retrieval-augmented Generation to Improve Math Question-Answering: Trade-offs Between Groundedness and Human Preference. [2023.10.04] [Arxiv]

• Making Retrieval-Augmented Language Models Robust to Irrelevant Context. [2023.10.02] [Arxiv]

• BTR: Binary Token Representations for Efficient Retrieval Augmented Language Models. [2023.10.02] [Arxiv]

• Fine-grained Late-interaction Multi-modal Retrieval for Retrieval Augmented Visual Question Answering. [2023.09.29] [Arxiv]

• Interpretable Long-Form Legal Question Answering with Retrieval-Augmented Large Language Models. [2023.09.29] [Arxiv]

• RAGAS: Automated Evaluation of Retrieval Augmented Generation. [2023.09.26] [Arxiv]

• Furthest Reasoning with Plan Assessment: Stable Reasoning Path with Retrieval-Augmented Large Language Models. [2023.09.22] [Arxiv]

• RUEL: Retrieval-Augmented User Representation with Edge Browser Logs for Sequential Recommendation. [2023.09.19] [Arxiv]

• Decoupling Knowledge from Memorization: Retrieval-augmented Prompt Learning. [2023.09.19] [Arxiv]

• Revisiting and Improving Retrieval-Augmented Deep Assertion Generation. [2023.09.18] [Arxiv]

• RECAP: Retrieval-Augmented Audio Captioning. [2023.09.18] [Arxiv]

• Differentiable Retrieval Augmentation via Generative Language Modeling for E-commerce Query Intent Classification. [2023.09.15] [Arxiv]

• Retrieval-Augmented Text-to-Audio Generation. [2023.09.14] [Arxiv]

• RAP-Gen: Retrieval-Augmented Patch Generation with CodeT5 for Automatic Program Repair. [2023.09.12] [Arxiv]

• Retrieval-Augmented Meta Learning for Low-Resource Text Classification. [2023.09.10] [Arxiv]

• RAHNet: Retrieval Augmented Hybrid Network for Long-tailed Graph Classification. [2023.09.07] [Arxiv]

• Benchmarking Large Language Models in Retrieval-Augmented Generation. [2023.09.04] [Arxiv]

• Retrieval-augmented GPT-3.5-based Text-to-SQL Framework with Sample-aware Prompting and Dynamic Revision Chain. [2023.09.04] [Arxiv]

• RAMP: Retrieval-Augmented MOS Prediction via Confidence-based Dynamic Weighting. [2023.08.31] [Arxiv]

• Vector Search with OpenAI Embeddings: Lucene Is All You Need. [2023.08.29] [Arxiv]

• Soft Prompt Tuning for Augmenting Dense Retrieval with Large Language Models. [2023.08.29] [Arxiv]

• RSpell: Retrieval-augmented Framework for Domain Adaptive Chinese Spelling Check. [2023.08.16] [Arxiv]

• Enhancing Performance on Seen and Unseen Dialogue Scenarios using Retrieval-Augmented End-to-End Task-Oriented System. [2023.08.16] [Arxiv]

• RAVEN: In-Context Learning with Retrieval Augmented Encoder-Decoder Language Models. [2023.08.15] [Arxiv]

• Diffusion Based Augmentation for Captioning and Retrieval in Cultural Heritage. [2023.08.14] [Arxiv]

• Encode-Store-Retrieve: Enhancing Memory Augmentation through Language-Encoded Egocentric Perception. [2023.08.10] [Arxiv]

• Hybrid Retrieval-Augmented Generation for Real-time Composition Assistance. [2023.08.08] [Arxiv]

• Retrieval-based Knowledge Augmented Vision Language Pre-training. [2023.08.06] [Arxiv]

• Retrieval Augmented Generation and Representative Vector Summarization for large unstructured textual data in Medical Education. [2023.08.01] [Arxiv]

• In-Context Retrieval-Augmented Language Models. [2023.08.01] [Arxiv]

• Select and Augment: Enhanced Dense Retrieval Knowledge Graph Augmentation. [2023.07.28] [Arxiv]

• Exploring Annotation-free Image Captioning with Retrieval-augmented Pseudo Sentence Generation. [2023.07.28] [Arxiv]

• RRAML: Reinforced Retrieval Augmented Machine Learning. [2023.07.27] [Arxiv]

• VITR: Augmenting Vision Transformers with Relation-Focused Learning for Cross-Modal Information Retrieval. [2023.07.27] [Arxiv]

• TabR: Unlocking the Power of Retrieval-Augmented Tabular Deep Learning. [2023.07.26] [Arxiv]

• Prompt Generate Train (PGT): Few-shot Domain Adaption of Retrieval Augmented Generation Models for Open Book Question-Answering. [2023.07.25] [Arxiv]

• Investigating the Factual Knowledge Boundary of Large Language Models with Retrieval Augmentation. [2023.07.23] [Arxiv]

• Animate-A-Story: Storytelling with Retrieval-Augmented Video Generation. [2023.07.13] [Arxiv]

• Cross-Lingual Retrieval Augmented Prompt for Low-Resource Languages. [2023.07.10] [Arxiv]

• TRAC: Trustworthy Retrieval Augmented Chatbot. [2023.07.06] [Arxiv]

• Improving Retrieval-Augmented Large Language Models via Data Importance Learning. [2023.07.06] [Arxiv]

• Surface-Based Retrieval Reduces Perplexity of Retrieval-Augmented Language Models. [2023.07.04] [Arxiv]

• Diverse Retrieval-Augmented In-Context Learning for Dialogue State Tracking. [2023.07.03] [Arxiv]

• When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric Memories. [2023.07.02][Arxiv]

• LeanDojo: Theorem Proving with Retrieval-Augmented Language Models. [2023.06.27] [Arxiv]

• SAIL: Search-Augmented Instruction Learning. [2023.06.25][Arxiv]

• Long-range Language Modeling with Self-retrieval. [2023.06.23] [Arxiv]

• Retrieval-Based Transformer for Table Augmentation. [2023.06.20] [Arxiv]

• Weakly-Supervised Scientific Document Classification via Retrieval-Augmented Multi-Stage Training. [2023.06.12] [Arxiv]

• Speech-to-Text Adapter and Speech-to-Entity Retriever Augmented LLMs for Speech Understanding. [2023.06.08] [Arxiv]

• RETA-LLM: A Retrieval-Augmented Large Language Model Toolkit. [2023.06.08] [Arxiv]

• Large language models can be easily distracted by irrelevant context. [2023.06.06][Arxiv]

• Retrieval-Augmented Multimodal Language Modeling. [2023.06.05] [Arxiv]

• Pre-computed memory or on-the-fly encoding? A hybrid approach to retrieval augmentation makes the most of your compute. [2023.06.02] [Arxiv]

• Reimagining Retrieval Augmented Language Models for Answering Queries. [2023.06.01] [Arxiv]

• Almanac: Retrieval-Augmented Language Models for Clinical Medicine. [2023.05.31] [Arxiv]

• LMCap: Few-shot Multilingual Image Captioning by Retrieval Augmented Language Model Prompting. [2023.05.31] [Arxiv]

• Label-Retrieval-Augmented Diffusion Models for Learning from Noisy Labels. [2023.05.30] [Arxiv]

• Improving accuracy of GPT-3/4 results on biomedical data using a retrieval-augmented language model. [2023.05.30] [Arxiv]

• Prompt-Guided Retrieval Augmentation for Non-Knowledge-Intensive Tasks. [2023.05.28] [Arxiv]

• Augmentation-Adapted Retriever Improves Generalization of Language Models as Generic Plug-In. [2023.05.26] [Arxiv]

• Nonparametric Masked Language Modeling. [2023.05.25] [Arxiv]

• KNN-LM Does Not Improve Open-ended Text Generation. [2023.05.24] [Arxiv]

• Enhancing Retrieval-Augmented Large Language Models with Iterative Retrieval-Generation Synergy. [2023.05.24] [Arxiv]

• Referral Augmentation for Zero-Shot Information Retrieval. [2023.05.24] [Arxiv]

• Enabling Large Language Models to Generate Text with Citations. [2023.05.24][Arxiv]

• REPLUG: Retrieval-Augmented Black-Box Language Models. [2023.05.24] [Arxiv]

• Query Rewriting for Retrieval-Augmented Large Language Models. [2023.05.23] [Arxiv]

• Retrieval-augmented Multi-label Text Classification. [2023.05.22] [Arxiv]

• MALM: Mask Augmentation based Local Matching for Food-Recipe Retrieval. [2023.05.18] [Arxiv]

• Tram: A Token-level Retrieval-augmented Mechanism for Source Code Summarization. [2023.05.18] [Arxiv]

• Lift Yourself Up: Retrieval-augmented Text Generation with Self Memory. [2023.05.17] [Arxiv]

• DAMO-NLP at SemEval-2023 Task 2: A Unified Retrieval-augmented System for Multilingual Named Entity Recognition. [2023.05.16] [Arxiv]

• Can Retriever-Augmented Language Models Reason? The Blame Game Between the Retriever and the Language Model. [2023.05.06] [Arxiv]

• Augmenting Passage Representations with Query Generation for Enhanced Cross-Lingual Dense Retrieval. [2023.05.06] [Arxiv]

• Retrieval Augmented Chest X-Ray Report Generation using OpenAI GPT models. [2023.05.05] [Arxiv]

• Discern and Answer: Mitigating the Impact of Misinformation in Retrieval-Augmented Models with Discriminators. [2023.05.02] [Arxiv]

• Retrieval Enhanced Data Augmentation for Question Answering on Privacy Policies. [2023.04.22] [Arxiv]

• A data augmentation perspective on diffusion models and retrieval. [2023.04.20] [Arxiv]

• Retrieval-Augmented Classification with Decoupled Representation. [2023.04.11] [Arxiv]

• LADER: Log-Augmented DEnse Retrieval for Biomedical Literature Search. [2023.04.10] [Arxiv]

• ReMoDiffuse: Retrieval-Augmented Motion Diffusion Model. [2023.04.03] [Arxiv]

• REVEAL: Retrieval-Augmented Visual-Language Pre-Training with Multi-Source Multimodal Knowledge Memory. [2023.04.03] [Arxiv]

• SmallCap: Lightweight Image Captioning Prompted with Retrieval Augmentation. [2023.03.28] [Arxiv]

• On the Calibration and Uncertainty with Pólya-Gamma Augmentation for Dialog Retrieval Models. [2023.03.15] [Arxiv]

• Suffix Retrieval-Augmented Language Modeling. [2023.03.14] [Arxiv]

• Semantic-Preserving Augmentation for Robust Image-Text Retrieval. [2023.03.09] [Arxiv]

• AugTriever: Unsupervised Dense Retrieval by Scalable Data Augmentation. [2023.03.07] [Arxiv]

• RAMM: Retrieval-augmented Biomedical Visual Question Answering with Multi-modal Pre-training. [2023.03.01] [Arxiv]

• Retrieved Sequence Augmentation for Protein Representation Learning. [2023.02.24] [Arxiv]

• X-TRA: Improving Chest X-ray Tasks with Cross-Modal Retrieval Augmentation. [2023.02.22] [Arxiv]

• DocPrompting: Generating Code by Retrieving the Docs. [2023.02.18] [Arxiv]

• Retrieval-augmented Image Captioning. [2023.02.16] [Arxiv]

• How to Train Your DRAGON: Diverse Augmentation Towards Generalizable Dense Retrieval. [2023.02.14] [Arxiv]

• Characterizing Attribution and Fluency Tradeoffs for Retrieval-Augmented Large Language Models. [2023.02.14] [Arxiv]

• Attributed Question Answering: Evaluation and Modeling for Attributed Large Language Models. [2023.02.10] [Arxiv]

• Re-ViLM: Retrieval-Augmented Visual Language Model for Zero and Few-Shot Image Captioning. [2023.02.09] [Arxiv]

• Augmenting Zero-Shot Dense Retrievers with Plug-in Mixture-of-Memories. [2023.02.07] [Arxiv]

• Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP. [2023.01.23] [Arxiv]

• Learning Customized Visual Models with Retrieval-Augmented Knowledge. [2023.01.17] [Arxiv]

• Generation-Augmented Query Expansion For Code Retrieval. [2022.12.20] [Arxiv]

• Augmenting Scientific Creativity with Retrieval across Knowledge Domains. [2022.12.14] [Arxiv]

• Training Language Models with Memory Augmentation. [2022.11.29] [Arxiv]

• Re-Imagen: Retrieval-Augmented Text-to-Image Generator. [2022.11.21] [Arxiv]

• Atlas: Few-shot Learning with Retrieval Augmented Language Models. [2022.11.16] [Arxiv]

• Retrieval-Augmented Generative Question Answering for Event Argument Extraction. [2022.11.13] [Arxiv]

• kNN-Prompt: Nearest Neighbor Zero-Shot Inference. [2022.11.01] [Arxiv]

• Improving Natural-Language-based Audio Retrieval with Transfer Learning and Audio & Text Augmentations. [2022.10.29] [Arxiv]

• Retrieval Augmented Visual Question Answering with Outside Knowledge. [2022.10.29] [Arxiv]

• You can't pick your neighbors, or can you? When and how to rely on retrieval in the kNN-LM. [2022.10.28] [Arxiv]

• QUILL: Query Intent with Large Language Models using Retrieval Augmentation and Multi-stage Distillation. [2022.10.27] [Arxiv]

• XRICL: Cross-lingual Retrieval-Augmented In-Context Learning for Cross-lingual Text-to-SQL Semantic Parsing. [2022.10.24] [Arxiv]

• Retrieval Augmentation for Commonsense Reasoning: A Unified Approach. [2022.10.23] [Arxiv]

• RACE: Retrieval-Augmented Commit Message Generation. [2022.10.22] [Arxiv]

• MuRAG: Multimodal Retrieval-Augmented Generator for Open Question Answering over Images and Text. [2022.10.20] [Arxiv]

• Unsupervised Cross-Task Generalization via Retrieval Augmentation. [2022.10.17] [Arxiv]

• Category-Level Pose Retrieval with Contrastive Features Learnt with Occlusion Augmentation. [2022.10.12] [Arxiv]

• Retrieval Augmentation for T5 Re-ranker using External Sources. [2022.10.11] [Arxiv]

• Improving Robustness of Retrieval Augmented Translation via Shuffling of Suggestions. [2022.10.10] [Arxiv]

• Improving Retrieval Augmented Neural Machine Translation by Controlling Source and Fuzzy-Match Interactions. [2022.10.10] [Arxiv]

• Improving the Domain Adaptation of Retrieval Augmented Generation (RAG) Models for Open Domain Question Answering. [2022.10.05] [Arxiv]

• FiD-Light: Efficient and Effective Retrieval-Augmented Text Generation. [2022.09.28] [Arxiv]

• SCL-RAI: Span-based Contrastive Learning with Retrieval Augmented Inference for Unlabeled Entity Problem in NER. [2022.09.24] [Arxiv]

• Segment Augmentation and Differentiable Ranking for Logo Retrieval. [2022.09.13] [Arxiv]

• MQRetNN: Multi-Horizon Time Series Forecasting with Retrieval Augmentation. [2022.09.08] [Arxiv]

• Unsupervised Dense Information Retrieval with Contrastive Learning. [2022.08.29] [Arxiv]

• Retrieval-Augmented Transformer for Image Captioning. [2022.08.22] [Arxiv]

• A Feature-space Multimodal Data Augmentation Technique for Text-video Retrieval. [2022.08.03] [Arxiv]

• Paired Cross-Modal Data Augmentation for Fine-Grained Image-to-Text Retrieval. [2022.07.28] [Arxiv]

• Text-Guided Synthesis of Artistic Images with Retrieval-Augmented Diffusion Models. [2022.07.26] [Arxiv]

• Multi-Task Retrieval-Augmented Text Generation with Relevance Sampling. [2022.07.06] [Arxiv]

• Learning Test-time Augmentation for Content-based Image Retrieval. [2022.07.05] [Arxiv]

• BashExplainer: Retrieval-Augmented Bash Code Comment Generation based on Fine-tuned CodeBERT. [2022.06.27] [Arxiv]

• Neuro-Symbolic Language Modeling with Automaton-augmented Retrieval. [2022.06.09] [Arxiv]

• Improving Contrastive Learning of Sentence Embeddings with Case-Augmented Positives and Retrieved Negatives. [2022.06.06] [Arxiv]

• Retrieval-Augmented Multilingual Keyphrase Generation with Retriever-Generator Iterative Training. [2022.06.01] [Arxiv]

• ZusammenQA: Data Augmentation with Specialized Models for Cross-lingual Open-retrieval Question Answering System. [2022.05.30] [Arxiv]

• Cache-Augmented Inbatch Importance Resampling for Training Recommender Retriever. [2022.05.30] [Arxiv]

• Retrieval-Augmented Reinforcement Learning. [2022.05.24] [Arxiv]

• Convex Augmentation for Total Variation Based Phase Retrieval. [2022.04.21] [Arxiv]

• Mention Memory: incorporating textual knowledge into Transformers through entity mention attention. [2022.04.19] [Arxiv]

• End-to-End Table Question Answering via Retrieval-Augmented Generation. [2022.03.30] [Arxiv]

• Teaching language models to support answers with verified quotes. [2022.03.21] [Arxiv]

• Augmenting Document Representations for Dense Retrieval with Interpolation and Perturbation. [2022.03.16] [Arxiv]

• Memorizing Transformers. [2022.03.16] [Arxiv]

• ReACC: A Retrieval-Augmented Code Completion Framework. [2022.03.15] [Arxiv]

• Novelty Controlled Paraphrase Generation with Retrieval Augmented Conditional Prompt Tuning. [2022.03.12] [Arxiv]

• Controllable Semantic Parsing via Retrieval Augmentation. [2022.02.23] [Arxiv]

• Retrieval Augmented Classification for Long-Tail Visual Recognition. [2022.02.22] [Arxiv]

• A Survey on Retrieval-Augmented Text Generation. [2022.02.13] [Arxiv]

• InPars: Data Augmentation for Information Retrieval using Large Language Models. [2022.02.10] [Arxiv]

• Improving language models by retrieving from trillions of tokens. [2022.02.07] [Arxiv]

• Efficient Nearest Neighbor Language Models. [2021.11.15] [Arxiv]

• One Question Answering Model for Many Languages with Cross-lingual Dense Passage Retrieval. [2021.10.28] [Arxiv]

• Noise-Augmented Privacy-Preserving Empirical Risk Minimization with Dual-purpose Regularizer and Privacy Budget Retrieval and Recycling. [2021.10.16] [Arxiv]

• RETRONLU: Retrieval Augmented Task-Oriented Semantic Parsing. [2021.09.21] [Arxiv]

• Robust Retrieval Augmented Generation for Zero-shot Slot Filling. [2021.09.13] [Arxiv]

• Retrieval Augmented Code Generation and Summarization. [2021.09.10] [Arxiv]

• Two-pronged Strategy: Lightweight Augmented Graph Network Hashing for Scalable Image Retrieval. [2021.08.09] [Arxiv]

• Generation-Augmented Retrieval for Open-domain Question Answering. [2021.08.06] [Arxiv]

• Retrieval-Augmented Transformer-XL for Close-Domain Dialog Generation. [2021.05.19] [Arxiv]

• Retrieval-Augmented Generation for Code Summarization via Hybrid GNN. [2021.05.12] [Arxiv]

• Retrieval Augmentation for Deep Neural Networks. [2021.04.26] [Arxiv]

• Cross-Modal Retrieval Augmentation for Multi-Modal Classification. [2021.04.16] [Arxiv]

• Retrieval Augmentation Reduces Hallucination in Conversation. [2021.04.15] [Arxiv]

• Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks. [2021.04.12] [Arxiv]

• Efficient Retrieval Augmented Generation from Unstructured Knowledge for Task-Oriented Dialog. [2021.02.08] [Arxiv]

• Memory Augmented Sequential Paragraph Retrieval for Multi-hop Question Answering. [2021.02.07] [Arxiv]

• Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data Augmentation. [2020.11.24] [Arxiv]

• Entities as Experts: Sparse Memory Access with Entity Supervision. [2020.10.06] [Arxiv]

• Augmenting Machine Learning with Information Retrieval to Recommend Real Cloned Code Methods for Code Completion. [2020.10.02] [Arxiv]

• Dense Passage Retrieval for Open-Domain Question Answering. [2020.09.30] [Arxiv]

• Neural Retrieval for Question Answering with Cross-Attention Supervised Data Augmentation. [2020.09.29] [Arxiv]

• Retrieve Synonymous keywords for Frequent Queries in Sponsored Search in a Data Augmentation Way. [2020.08.05] [Arxiv]

• Tree-Augmented Cross-Modal Encoding for Complex-Query Video Retrieval. [2020.07.05] [Arxiv]

• On-The-Fly Information Retrieval Augmentation for Language Models. [2020.07.03] [Arxiv]

• Generalization through Memorization: Nearest Neighbor Language Models. [2020.02.15] [Arxiv]

• REALM: Retrieval-Augmented Language Model Pre-Training. [2020.02.10] [Arxiv]

• Web Table Extraction, Retrieval and Augmentation: A Survey. [2020.02.05] [Arxiv]

• Multi-Modal Music Information Retrieval: Augmenting Audio-Analysis with Visual Computing for Improved Music Video Analysis. [2020.02.01] [Arxiv]

• GRAPHENE: A Precise Biomedical Literature Retrieval Engine with Graph Augmented Deep Learning and External Knowledge Empowerment. [2019.11.20] [Arxiv]

• Discriminative Learning of Open-Vocabulary Object Retrieval and Localization by Negative Phrase Augmentation. [2018.09.04] [Arxiv]

• Neural Argument Generation Augmented with Externally Retrieved Evidence. [2018.05.25] [Arxiv]

• Gradient Augmented Information Retrieval with Autoencoders and Semantic Hashing. [2018.03.12] [Arxiv]

• Retrieval-Augmented Convolutional Neural Networks for Improved Robustness against Adversarial Examples. [2018.02.26] [Arxiv]

• Automatic Hallucination Assessment for Aligned Large Language Models via Transferable Adversarial Attacks. [2023.10.19] [Arxiv]
• Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection. [2023.10.17] [Arxiv]
• Towards reducing hallucination in extracting information from financial reports using Large Language Models. [2023.10.16] [Arxiv]
• In-Context Pretraining: Language Modeling Beyond Document Boundaries. [2023.10.18] [Arxiv]
• MechGPT, a language-based strategy for mechanics and materials modeling that connects knowledge across scales, disciplines and modalities. [2023.10.16] [Arxiv]
• CarExpert: Leveraging Large Language Models for In-Car Conversational Question Answering. [2023.10.14] [Arxiv]
• Towards Example-Based NMT with Multi-Levenshtein Transformers. [2023.10.13] [Arxiv]
• GenTKG: Generative Forecasting on Temporal Knowledge Graph. [2023.10.11] [Arxiv]
• Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity. [2023.10.18] [Arxiv]
• The Solution for the CVPR2023 NICE Image Captioning Challenge. [2023.10.10] [Arxiv]
• GPT-4 as an Agronomist Assistant? Answering Agriculture Exams Using Large Language Models. [2023.10.12] [Arxiv]
• Glitter or Gold? Deriving Structured Insights from Sustainability Reports via Large Language Models. [2023.10.09] [Arxiv]
• LLM4VV: Developing LLM-Driven Testsuite for Compiler Validation. [2023.10.07] [Arxiv]
• Retrieval meets Long Context Large Language Models. [2023.10.04] [Arxiv]
• Chatmap : Large Language Model Interaction with Cartographic Data. [2023.09.28] [Arxiv]
• Attention Sorting Combats Recency Bias In Long Context Language Models. [2023.09.28] [Arxiv]
• PDFTriage: Question Answering over Long, Structured Documents. [2023.09.16] [Arxiv]
• PACE-LM: Prompting and Augmentation for Calibrated Confidence Estimation with GPT-4 in Cloud Incident Root Cause Analysis. [2023.09.29] [Arxiv]
• Kani: A Lightweight and Highly Hackable Framework for Building Language Model Applications. [2023.09.11] [Arxiv]
• Scaling Autoregressive Multi-Modal Models: Pretraining and Instruction Tuning. [2023.09.05] [Arxiv]
• A Study on the Implementation of Generative AI Services Using an Enterprise Data-Based LLM Application Architecture. [2023.09.18] [Arxiv]
• MEMORY-VQ: Compression for Tractable Internet-Scale Memory. [2023.08.28] [Arxiv]
• American Stories: A Large-Scale Structured Text Dataset of Historical U.S. Newspapers. [2023.08.23] [Arxiv]
• Domain Adaptive Code Completion via Language Models and Decoupled Domain Databases. [2023.09.20] [Arxiv]
• Answering Unseen Questions With Smaller Language Models Using Rationale Generation and Dense Retrieval. [2023.10.12] [Arxiv]
• Teaching Smaller Language Models To Generalise To Unseen Compositional Questions. [2023.08.20] [Arxiv]
• Evaluating Correctness and Faithfulness of Instruction-Following Models for Question Answering. [2023.07.31] [Arxiv]
• Alleviating the Long-Tail Problem in Conversational Recommender Systems. [2023.07.21] [Arxiv]
• Meta-training with Demonstration Retrieval for Efficient Few-shot Learning. [2023.06.30] [Arxiv]
• RAPGen: An Approach for Fixing Code Inefficiencies in Zero-Shot. [2023.06.29] [Arxiv]
• Long-range Language Modeling with Self-retrieval. [2023.06.23] [Arxiv]
• Encyclopedic VQA: Visual questions about detailed properties of fine-grained categories. [2023.07.24] [Arxiv]
• PoET: A generative model of protein families as sequences-of-sequences. [2023.06.09] [Arxiv]
• TimelineQA: A Benchmark for Question Answering over Timelines. [2023.06.01] [Arxiv]
• Knowledge Graph-Augmented Language Models for Knowledge-Grounded Dialogue Generation. [2023.05.30] [Arxiv]
• Multimodal Relation Extraction with Cross-Modal Retrieval and Synthesis. [2023.05.25] [Arxiv]
• Learning Answer Generation using Supervision from Automatic Question Answering Evaluators. [2023.05.24] [Arxiv]
• Adapting Language Models to Compress Contexts. [2023.05.24] [Arxiv]
• KNN-LM Does Not Improve Open-ended Text Generation. [2023.05.23] [Arxiv]
• FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation. [2023.10.11] [Arxiv]
• Adaptive Chameleon or Stubborn Sloth: Revealing the Behavior of Large Language Models in Knowledge Conflicts. [2023.10.02] [Arxiv]
• Knowledge-Retrieval Task-Oriented Dialog Systems with Semi-Supervision. [2023.05.22] [Arxiv]
• The Web Can Be Your Oyster for Improving Large Language Models. [2023.05.24] [Arxiv]
• RL4F: Generating Natural Language Feedback with Reinforcement Learning for Repairing Model Outputs. [2023.07.11] [Arxiv]
• Huatuo-26M, a Large-scale Chinese Medical QA Dataset. [2023.05.02] [Arxiv]
• LaMP: When Large Language Models Meet Personalization. [2023.05.19] [Arxiv]
• GeneGPT: Augmenting Large Language Models with Domain Tools for Improved Access to Biomedical Information. [2023.05.16] [Arxiv]
• BRENT: Bidirectional Retrieval Enhanced Norwegian Transformer. [2023.04.19] [Arxiv]
• Shall We Pretrain Autoregressive Language Models with Retrieval? A Comprehensive Study. [2023.10.19] [Arxiv]
• Improving Image Recognition by Retrieving from Web-Scale Image-Text Data. [2023.04.11] [Arxiv]
• RepoCoder: Repository-Level Code Completion Through Iterative Retrieval and Generation. [2023.04.03] [Arxiv]
• On the Generalization Ability of Retrieval-Enhanced Transformers. [2023.02.23] [Arxiv]
• $k$NN-Adapter: Efficient Domain Adaptation for Black-Box Language Models. [2023.02.21] [Arxiv]
• Why do Nearest Neighbor Language Models Work?. [2023.01.17] [Arxiv]
• You Truly Understand What I Need: Intellectual and Friendly Dialogue Agents grounding Knowledge and Persona. [2023.01.06] [Arxiv]
• Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP. [2023.01.23] [Arxiv]
• Parallel Context Windows for Large Language Models. [2023.08.01] [Arxiv]
• When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric Memories. [2023.07.02] [Arxiv]
• Empowering Sentence Encoders with Prompting and Label Retrieval for Zero-shot Text Classification. [2023.05.19] [Arxiv]
• FiDO: Fusion-in-Decoder optimized for stronger performance and faster inference. [2023.06.02] [Arxiv]
• Neural Machine Translation with Contrastive Translation Memories. [2022.12.06] [Arxiv]
• ClueWeb22: 10 Billion Web Documents with Visual and Semantic Information. [2022.12.01] [Arxiv]
• Large Language Models Struggle to Learn Long-Tail Knowledge. [2023.07.27] [Arxiv]
• CELLS: A Parallel Corpus for Biomedical Lay Language Generation. [2022.11.07] [Arxiv]
• An Efficient Memory-Augmented Transformer for Knowledge-Intensive NLP Tasks. [2022.10.30] [Arxiv]
• Schema-aware Reference as Prompt Improves Data-Efficient Knowledge Graph Construction. [2023.09.18] [Arxiv]
• COFAR: Commonsense and Factual Reasoning in Image Search. [2022.10.16] [Arxiv]
• Variational Open-Domain Question Answering. [2023.05.31] [Arxiv]
• Decoupled Context Processing for Context Augmented Language Modeling. [2022.10.11] [Arxiv]
• CORE: A Retrieve-then-Edit Framework for Counterfactual Data Generation. [2022.11.01] [Arxiv]
• Recitation-Augmented Language Models. [2023.02.16] [Arxiv]
• Zemi: Learning Zero-Shot Semi-Parametric Language Models from Multiple Tasks. [2023.05.22] [Arxiv]
• Multimedia Generative Script Learning for Task Planning. [2023.07.10] [Arxiv]
• Can large language models reason about medical questions?. [2023.01.24] [Arxiv]
• Memory-Based Model Editing at Scale. [2022.06.13] [Arxiv]
• kNN-Prompt: Nearest Neighbor Zero-Shot Inference. [2022.11.01] [Arxiv]
• Long-term Control for Dialogue Generation: Methods and Evaluation. [2022.05.15] [Arxiv]
• Efficient Machine Translation Domain Adaptation. [2022.04.26] [Arxiv]
• A Corpus for Understanding and Generating Moral Stories. [2022.04.20] [Arxiv]
• Augmenting Pre-trained Language Models with QA-Memory for Open-Domain Question Answering. [2023.01.23] [Arxiv]
• KGI: An Integrated Framework for Knowledge Intensive Language Tasks. [2022.09.21] [Arxiv]
• $k$NN-NER: Named Entity Recognition with Nearest Neighbor Search. [2022.03.31] [Arxiv]
• Evidentiality-guided Generation for Knowledge-Intensive NLP Tasks. [2022.05.14] [Arxiv]
• Reason first, then respond: Modular Generation for Knowledge-infused Dialogue. [2021.11.09] [Arxiv]
• End-to-End Learning of Flowchart Grounded Task-Oriented Dialogs. [2021.12.07] [Arxiv]
• Memory and Knowledge Augmented Language Models for Inferring Salience in Long-Form Stories. [2021.09.14] [Arxiv]
• Beyond Goldfish Memory: Long-Term Open-Domain Conversation. [2021.07.15] [Arxiv]
• Fine-tune the Entire RAG Architecture (including DPR retriever) for Question-Answering. [2021.06.21] [Arxiv]
• End-to-End Training of Multi-Document Reader and Retriever for Open-Domain Question Answering. [2021.12.04] [Arxiv]
• Zero-shot Slot Filling with DPR and RAG. [2021.04.17] [Arxiv]
• Lingke: A Fine-grained Multi-turn Chatbot for Customer Service. [2018.08.10] [Arxiv]
• Retrieval-Augmented Convolutional Neural Networks for Improved Robustness against Adversarial Examples. [2018.02.26] [Arxiv]

• https://github.com/Wang-Shuo/A-Guide-to-Retrieval-Augmented-LLM
• https://www.anyscale.com/blog/a-comprehensive-guide-for-building-rag-based-llm-applications-part-1
• https://blog.langchain.dev/semi-structured-multi-modal-rag/
• https://acl2023-retrieval-lm.github.io/