# Generative Information Retrieval - [Autoregressive Search Engines: Generating Substrings as Document Identifiers](NeurIPS-2022-autoregressive-search-engines-generating-substrings-as-document-identifiers-Paper-Conference.pdf) - [Transformer Memory as a Differentiable Search Index](NeurIPS-2022-transformer-memory-as-a-differentiable-search-index-Paper-Conference.pdf) - [Scalable and Effective Generative Information Retrieval](2311.09134.pdf) # Retrieval-Augmented Generation - [Retrieval-Augmented Generation for Large Language Models: A Survey](2312.10997v3.pdf) - [Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks](2005.11401v4.pdf) - [When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric Memories](2212.10511.pdf) - [DEMONSTRATE–SEARCH–PREDICT: Composing retrieval and language models for knowledge-intensive NLP](2212.14024.pdf) ## Hallucination Reduction - [CHAIN-OF-NOTE: ENHANCING ROBUSTNESS IN RETRIEVAL-AUGMENTED LANGUAGE MODELS](2311.09210.pdf) - [CHAIN-OF-VERIFICATION REDUCES HALLUCINATION IN LARGE LANGUAGE MODELS](2309.11495.pdf) ## Applying RAG to Structured Data - [TabR: Unlocking the Power of Retrieval-Augmented Tabular Deep Learning](2307.14338.pdf) ## Summarization - [From Sparse to Dense: GPT-4 Summarization with Chain of Density Prompting](2309.04269.pdf) - [Bloated Disclosures: Can ChatGPT Help Investors Process Financial Information?](2306.10224.pdf) # Copilots/Agents - [Cognitive Architectures for Language Agents](2309.02427.pdf) - [A Survey on Large Language Model based Autonomous Agents](2308.11432v1.pdf) # Recommender Systems - [LLM-Rec: Personalized Recommendation via Prompting Large Language Models](2307.15780.pdf) - [RecMind: Large Language Model Powered Agent For Recommendation](2308.14296.pdf) - [Personalized News Recommendation: Methods and Challenges](2106.08934.pdf) - [Personality-aware Product Recommendation System based on User Interests Mining and Meta-path Discovery](FinalVerion.pdf) - [A Survey of Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions](2109.03792.pdf) # Graph Representation Learning - [Relational Deep Learning: Graph Representation Learning on Relational Databases](paper.pdf) - [Knowledge Graph Prompting for Multi-Document Question Answering](2308.11730.pdf) - [Neural Graph Reasoning: Complex Logical Query Answering Meets Graph Databases](2303.14617.pdf) - [Building a trust-based doctor recommendation system on top of multilayer graph database](Building%20a%20trust-based%20doctor%20recommendation%20system%20on%20top%20of%20multilayer%20graph%20database%20-%202020.pdf) - [UNDERSTANDING GRAPH EMBEDDING METHODS AND THEIR APPLICATIONS](2012.08019.pdf) # Generative Text Classification - [Prompt Tuned Embedding Classification for Multi-Label Industry Sector Allocation](2309.12075.pdf) # Generative Named Entity Recognition & Disambiguation - [AUTOREGRESSIVE ENTITY RETRIEVAL](2010.00904.pdf) - [Highly Parallel Autoregressive Entity Linking with Discriminative Correction](2109.03792.pdf)