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Awesome-LLM-with-RAG

Enhancing Large Language Models with Retrieval Augmented Generation.

Paper

  • 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]

_Paper

  • 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]

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